If you think that there is an error in how your package is being tested or represented, please file an issue at NewPkgEval.jl , making sure to read the FAQ first.
Results with Julia v1.2.0
Testing was successful .
Last evaluation was ago and took 13 minutes, 53 seconds.
Click here to download the log file.
Click here to show the log contents.
Resolving package versions...
Installed Missings ──────────────────── v0.4.3
Installed DataAPI ───────────────────── v1.1.0
Installed ConstructionBase ──────────── v1.0.0
Installed TableTraits ───────────────── v1.0.0
Installed BinaryProvider ────────────── v0.5.8
Installed DiffEqBase ────────────────── v6.7.0
Installed DataFrames ────────────────── v0.19.4
Installed DataValueInterfaces ───────── v1.0.0
Installed Requires ──────────────────── v0.5.2
Installed PooledArrays ──────────────── v0.5.2
Installed InvertedIndices ───────────── v1.0.0
Installed Compat ────────────────────── v2.2.0
Installed DocStringExtensions ───────── v0.8.1
Installed Reexport ──────────────────── v0.2.0
Installed OrderedCollections ────────── v1.1.0
Installed FunctionWrappers ──────────── v1.0.0
Installed Tables ────────────────────── v0.2.11
Installed DataStructures ────────────── v0.17.6
Installed TreeViews ─────────────────── v0.3.0
Installed RecipesBase ───────────────── v0.7.0
Installed Roots ─────────────────────── v0.8.3
Installed IterativeSolvers ──────────── v0.8.1
Installed DiffEqDiffTools ───────────── v1.5.0
Installed JSON ──────────────────────── v0.21.0
Installed Parsers ───────────────────── v0.3.10
Installed ArrayInterface ────────────── v2.0.0
Installed RecursiveFactorization ────── v0.1.0
Installed RecursiveArrayTools ───────── v1.2.0
Installed StaticArrays ──────────────── v0.12.1
Installed Parameters ────────────────── v0.12.0
Installed ModiaMath ─────────────────── v0.5.2
Installed MuladdMacro ───────────────── v0.2.1
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed CategoricalArrays ─────────── v0.7.3
Installed SortingAlgorithms ─────────── v0.3.1
Installed Unitful ───────────────────── v0.18.0
Installed MacroTools ────────────────── v0.5.2
Installed Sundials ──────────────────── v3.8.1
Installed Modia3D ───────────────────── v0.4.0
Updating `~/.julia/environments/v1.2/Project.toml`
[07f2c1e0] + Modia3D v0.4.0
Updating `~/.julia/environments/v1.2/Manifest.toml`
[4fba245c] + ArrayInterface v2.0.0
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.3
[34da2185] + Compat v2.2.0
[187b0558] + ConstructionBase v1.0.0
[9a962f9c] + DataAPI v1.1.0
[a93c6f00] + DataFrames v0.19.4
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[2b5f629d] + DiffEqBase v6.7.0
[01453d9d] + DiffEqDiffTools v1.5.0
[ffbed154] + DocStringExtensions v0.8.1
[069b7b12] + FunctionWrappers v1.0.0
[41ab1584] + InvertedIndices v1.0.0
[42fd0dbc] + IterativeSolvers v0.8.1
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[1914dd2f] + MacroTools v0.5.2
[e1d29d7a] + Missings v0.4.3
[07f2c1e0] + Modia3D v0.4.0
[67ccffd1] + ModiaMath v0.5.2
[46d2c3a1] + MuladdMacro v0.2.1
[bac558e1] + OrderedCollections v1.1.0
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.10
[2dfb63ee] + PooledArrays v0.5.2
[3cdcf5f2] + RecipesBase v0.7.0
[731186ca] + RecursiveArrayTools v1.2.0
[f2c3362d] + RecursiveFactorization v0.1.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v0.5.2
[f2b01f46] + Roots v0.8.3
[a2af1166] + SortingAlgorithms v0.3.1
[90137ffa] + StaticArrays v0.12.1
[c3572dad] + Sundials v3.8.1
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[a2a6695c] + TreeViews v0.3.0
[1986cc42] + Unitful v0.18.0
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Sundials → `~/.julia/packages/Sundials/MllUG/deps/build.log`
Testing Modia3D
Status `/tmp/jl_Puic9M/Manifest.toml`
[4fba245c] ArrayInterface v2.0.0
[b99e7846] BinaryProvider v0.5.8
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[187b0558] ConstructionBase v1.0.0
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[2b5f629d] DiffEqBase v6.7.0
[01453d9d] DiffEqDiffTools v1.5.0
[ffbed154] DocStringExtensions v0.8.1
[069b7b12] FunctionWrappers v1.0.0
[41ab1584] InvertedIndices v1.0.0
[42fd0dbc] IterativeSolvers v0.8.1
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[07f2c1e0] Modia3D v0.4.0
[67ccffd1] ModiaMath v0.5.2
[46d2c3a1] MuladdMacro v0.2.1
[bac558e1] OrderedCollections v1.1.0
[d96e819e] Parameters v0.12.0
[69de0a69] Parsers v0.3.10
[2dfb63ee] PooledArrays v0.5.2
[3cdcf5f2] RecipesBase v0.7.0
[731186ca] RecursiveArrayTools v1.2.0
[f2c3362d] RecursiveFactorization v0.1.0
[189a3867] Reexport v0.2.0
[ae029012] Requires v0.5.2
[f2b01f46] Roots v0.8.3
[a2af1166] SortingAlgorithms v0.3.1
[90137ffa] StaticArrays v0.12.1
[c3572dad] Sundials v3.8.1
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[a2a6695c] TreeViews v0.3.0
[1986cc42] Unitful v0.18.0
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
Importing Modia3D Version 0.4.0 (2019-09-27)
Importing ModiaMath Version 0.5.2 (2019-07-10)
PyPlot not available (plot commands will be ignored).
Try to install PyPlot. See hints here:
https://github.com/ModiaSim/ModiaMath.jl/wiki/Installing-PyPlot-in-a-robust-way.
┌ Warning:
│ Environment variable "DLR_VISUALIZATION" not defined.
│ Include ENV["DLR_VISUALIZATION"] = <path-to-Visualization/Extras/SimVis> into your HOME/.julia/config/startup.jl file.
│
│ No Renderer is used in Modia3D (so, animation is switched off).
└ @ Modia3D.DLR_Visualization ~/.julia/packages/Modia3D/r9s9x/src/renderer/DLR_Visualization/renderer.jl:87
... success of test_solidProperties.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
progress: integrated up to time = 0.002 s
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 9.1 s (init: 8.2 s, integration: 0.9 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ControllerDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DamperMacro.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Simulate_FourBar.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... pos_angle2(time=0.5) = 2.24
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.08 s (init: 0.0016 s, integration: 0.079 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 206
nResidues = 267 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 23
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 1.2e-08 s
hMin = 1.2e-08 s
hMax = 0.049 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithFixedJoint.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_2Rev_ZylZ_BarX.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_3Rev_ZylZ_BarX_BarY.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_InertiaTensor.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_KinematicRevoluteJoints.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_zAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_xAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_yAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_noMacros.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal1Assembly.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal4Assemblies.jl!
WARNING: replacing module test_massComputation.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... success of volume_computation3D_obj.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Move_Pendulum.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Visualize_Beam.jl!
...test_Examples finished!
WARNING: replacing module TestExamples.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_Billiards_OneBall!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: BouncingBall1
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼────────┼─────────┼───────┼─────────┤
│ 1 │ h │ 0.2 │ 0 │ 0.2 │
│ 2 │ v │ 0.0 │ 0 │ 1.0 │
... h0 = 0.2
flying = true
-h = -0.2 (became <= 0)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.2019275108811498 s (z[1] > 0)
-h = 1.6181500583911657e-14 (became > 0)
... v = 1.3866362172208557
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.484626025952448 s (z[1] > 0)
-h = 2.71657696337968e-14 (became > 0)
... v = 0.9706453509400057
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.682514985967628 s (z[1] > 0)
-h = 1.3320941572025902e-14 (became > 0)
... v = 0.6794517427662368
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.8210372566626214 s (z[1] > 0)
-h = 6.938893903907228e-18 (became > 0)
... v = 0.47561621292614215
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9180028433604212 s (z[1] > 0)
-h = 2.3418766925686896e-17 (became > 0)
... v = 0.3329313347031544
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9858787506124347 s (z[1] > 0)
-h = 3.80034545499619e-15 (became > 0)
... v = 0.23305186965963645
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 1.0 s
BouncingBall model is terminated (flying = true)
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 1.1 s (init: 0.94 s, integration: 0.19 s)
startTime = 0.0 s
stopTime = 1.0 s
interval = 0.02 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 63
nSteps = 125
nResidues = 345 (includes residue calls for Jacobian)
nZeroCrossings = 237
nJac = 110
nTimeEvents = 0
nStateEvents = 6
nRestartEvents = 6
nErrTestFails = 0
h0 = 7.2e-07 s
hMin = 7.2e-07 s
hMax = 0.27 s
orderMax = 3
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_BouncingBall.jl
... success of examples/collisions/Simulate_NewtonsCradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_SlidingAndRollingBall.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_TwoCollidingBalls.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: YouBot
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────────────────┼─────────┼───────┼─────────┤
│ 1 │ link1.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ link1.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ link2.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ link2.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 5 │ link3.rev.rev.phi │ 1.5708 │ 1 │ 1.5708 │
│ 6 │ link3.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 7 │ link4.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 8 │ link4.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 9 │ link5.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 10 │ link5.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 11 │ gripper.prism.prism.s │ 0.0 │ 1 │ 1.0 │
│ 12 │ gripper.prism.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 13 │ sphere.r[1] │ -0.125 │ 1 │ 1.0 │
│ 14 │ sphere.r[2] │ 0.0 │ 1 │ 1.0 │
│ 15 │ sphere.r[3] │ 0.03 │ 1 │ 1.0 │
│ 16 │ link1.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 17 │ link2.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 18 │ link3.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 19 │ link4.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 20 │ link5.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 21 │ gripper.prism.prism.v │ 0.0 │ 1 │ 1.0 │
│ 22 │ sphere.v[1] │ 0.0 │ 1 │ 1.0 │
│ 23 │ sphere.v[2] │ 0.0 │ 1 │ 1.0 │
│ 24 │ sphere.v[3] │ 0.0 │ 1 │ 1.0 │
│ 25 │ sphere.q[1] │ 0.0 │ 0 │ 1.0 │
│ 26 │ sphere.q[2] │ 0.0 │ 0 │ 1.0 │
│ 27 │ sphere.q[3] │ 0.0 │ 0 │ 1.0 │
│ 28 │ sphere.q[4] │ 1.0 │ 0 │ 1.0 │
│ 29 │ sphere.w[1] │ 0.0 │ 1 │ 1.0 │
│ 30 │ sphere.w[2] │ 0.0 │ 1 │ 1.0 │
│ 31 │ sphere.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 7.261196339086959e-5 s (z[2] < 0)
distance(table.plate,sphere) = -2.0000000037447373e-8 became < 0
contact normal = [4.51e-08,6.28e-08,1], contact position = [0.585,-1.57e-09,0.375], c_res=1.24e+06, d_res=1e+03
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.417313819072049 s (z[2] < 0)
distance(sphere,gripper.gripper_right_finger) = -2.0000000393229984e-8 became < 0
contact normal = [-1,-0.00507,-2.05e-05], contact position = [0.56,-0.000127,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.4173142226300918 s (z[2] < 0)
distance(sphere,gripper.gripper_left_finger) = -2.0000006971107646e-8 became < 0
contact normal = [-1,0.00702,2.02e-05], contact position = [0.56,0.000175,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
State event (zero-crossing) at time = 0.42197539326597844 s (z[1] > 0)
distance(sphere,gripper.gripper_left_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.421976224209762 s (z[1] > 0)
distance(sphere,gripper.gripper_right_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
progress: integrated up to time = 0.92 s
progress: integrated up to time = 2.1 s
progress: integrated up to time = 2.2 s
progress: integrated up to time = 2.2 s
progress: integrated up to time = 2.3 s
progress: integrated up to time = 2.4 s
progress: integrated up to time = 2.4 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
State event (zero-crossing) at time = 3.544805661448877 s (z[1] > 0)
distance(table.plate,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.772099387510426 s (z[2] < 0)
distance(ground,sphere) = -2.0000000104326316e-8 became < 0
contact normal = [-5.5e-07,-3e-06,1], contact position = [0.939,-0.000237,-3.46e-06], c_res=1.24e+06, d_res=0.32
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 3.8 s
State event (zero-crossing) at time = 3.787117001624274 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.125658766045461 s (z[2] < 0)
distance(ground,sphere) = -2.000011756920415e-8 became < 0
contact normal = [-5.51e-07,-3e-06,1], contact position = [1.03,-0.000263,-3.4e-06], c_res=1.24e+06, d_res=0.519
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.142357296028154 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.2 s
State event (zero-crossing) at time = 4.347238032219403 s (z[2] < 0)
distance(ground,sphere) = -2.0000000248254154e-8 became < 0
contact normal = [-5.52e-07,-3e-06,1], contact position = [1.09,-0.00028,-3.37e-06], c_res=1.24e+06, d_res=0.857
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.366036388703918 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.485371689085727 s (z[2] < 0)
distance(ground,sphere) = -2.000002838776016e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.13,-0.000291,-3.34e-06], c_res=1.24e+06, d_res=1.47
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.50711993227886 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.570603069658777 s (z[2] < 0)
distance(ground,sphere) = -2.000001311286435e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.15,-0.000298,-3.33e-06], c_res=1.24e+06, d_res=2.77
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.6 s
State event (zero-crossing) at time = 4.5979981506589205 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.621567133614952 s (z[2] < 0)
distance(ground,sphere) = -2.000000589083613e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.17,-0.000302,-3.32e-06], c_res=1.24e+06, d_res=7.5
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.9 s
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 2.2e+02 s (init: 0.41 s, integration: 2.2e+02 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-5
nEquations = 31 (includes 1 constraints)
nResults = 5035
nSteps = 6038
nResidues = 144452 (includes residue calls for Jacobian)
nZeroCrossings = 11202
nJac = 4234
nTimeEvents = 0
nStateEvents = 17
nRestartEvents = 17
nErrTestFails = 1721
h0 = 1.8e-09 s
hMin = 1.8e-09 s
hMax = 0.053 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_YouBot.jl
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Collision_3Elements.jl!
... success of Test_Collision.jl!
... success of Test_Collision_moreRevolutes.jl!
... success of Test_Collision_StarSetting.jl!
... success of Test_MiniBsp.jl!
... success of Test_Solids.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ContactBoxOnTable.jl!
WARNING: replacing module Simulate_YouBot.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_YouBotBoxOnTable.jl!
... success of collision_2_boxes.jl!
... success of collision_ballWithBall.jl!
... success of collision_ballWithBox.jl!
... success of collision_ballWithBox_45Deg.jl!
... success of collision_BallWithBox_Prismatic.jl!
WARNING: replacing module collision_ballWithBox_45Deg.
... success of collision_ballWithBox_45Deg.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: NewtonsCradle
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ -1.0472 │ 1 │ 1.0472 │
│ 2 │ rev2.phi │ -1.0472 │ 1 │ 1.0472 │
│ 3 │ rev3.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev4.phi │ 1.0472 │ 1 │ 1.0472 │
│ 5 │ rev5.phi │ 1.0472 │ 1 │ 1.0472 │
│ 6 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 7 │ rev2.w │ 0.0 │ 1 │ 1.0 │
│ 8 │ rev3.w │ 0.0 │ 1 │ 1.0 │
│ 9 │ rev4.w │ 0.0 │ 1 │ 1.0 │
│ 10 │ rev5.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 1.0878031474718333 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000077594062304e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.11
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000077260995397e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.11
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0908094518650024 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0938480230542378 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000232248129635e-8 became < 0
contact normal = [0,1,-0.000784], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.0667
distance(pendulum5.sphere,pendulum4.sphere) = -2.000023202608503e-8 became < 0
contact normal = [0,-1,-0.000784], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.0667
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0958883290568509 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0985275695684327 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000000211517488e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.169
distance(pendulum3.sphere,pendulum2.sphere) = -1.9999999101294463e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.169
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.1018053667261674 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1750114228447495 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9999989109287242e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.262
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000766629e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.262
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1785879880615164 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1930977548240014 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000009426368592e-8 became < 0
contact normal = [0,1,-0.00063], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.147
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000012757037666e-8 became < 0
contact normal = [0,-1,-0.00063], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.147
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1954887018752087 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.2073414785973235 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.999992316203958e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.347
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.347
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.211125697316102 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.306987610498805 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000038292167233e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.537
distance(pendulum3.sphere,pendulum2.sphere) = -1.9998782851970986e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.537
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.311116540157841 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.3389794846640575 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000039291367955e-8 became < 0
contact normal = [0,1,-0.00065], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.336
distance(pendulum5.sphere,pendulum4.sphere) = -1.99989548255175e-8 became < 0
contact normal = [0,-1,-0.00065], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.336
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.341800682588432 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.371038706105848 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000006983877938e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.886
distance(pendulum3.sphere,pendulum2.sphere) = -1.9988123378666955e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.886
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.375601280236619 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.586849755374663 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9609640355966462e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.37
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000080924731378e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.37
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.591827089433919 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.623516942618943 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -1.96331674251482e-8 became < 0
contact normal = [0,1,-0.000809], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.73
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,-0.000809], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.73
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.626809172298678 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.651102476406292 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.694994378187431e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.68
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000034739453554e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.68
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.656286321908144 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
progress: integrated up to time = 9.5 s
Simulation is terminated at time = 10.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 5.2 s (init: 0.0048 s, integration: 5.2 s)
startTime = 0.0 s
stopTime = 10.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 10 (includes 0 constraints)
nResults = 10049
nSteps = 3394
nResidues = 11111 (includes residue calls for Jacobian)
nZeroCrossings = 13578
nJac = 644
nTimeEvents = 0
nStateEvents = 24
nRestartEvents = 24
nErrTestFails = 183
h0 = 3.7e-10 s
hMin = 3.7e-10 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... success of collision_newtons_cradle.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │ 1 │ [1.0, 0.0, 0.15] │
│ 2 │ x[4:6] │ boxMoving.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │
│ 2 │ x[4:6] │ boxMoving.v │
│ 3 │ x[7:10] │ boxMoving.q │
│ 4 │ x[11:13] │ boxMoving.w │
│ 5 │ derx[4:6] │ boxMoving.a │
│ 6 │ derx[7:10] │ boxMoving.derq │
│ 7 │ derx[11:13] │ boxMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.v │ residue[1:3] │
│ 2 │ boxMoving.residue_w │ residue[4:6] │
│ 3 │ boxMoving.residue_f │ residue[7:9] │
│ 4 │ boxMoving.residue_t │ residue[10:12] │
│ 5 │ boxMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.r │ result[2:4] │ [1.0, 0.0, 0.15] │
│ 3 │ boxMoving.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.r[1] │ 1.0 │ 1 │ 1.0 │
│ 2 │ boxMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ boxMoving.r[3] │ 0.15 │ 1 │ 1.0 │
│ 4 │ boxMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.45 s (init: 0.0043 s, integration: 0.45 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2001
nSteps = 22
nResidues = 282 (includes residue calls for Jacobian)
nZeroCrossings = 2022
nJac = 20
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 0
h0 = 1e-06 s
hMin = 1e-06 s
hMax = 0.95 s
orderMax = 2
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ -6.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 2.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ 4.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ -6.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 2.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ 4.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes_Prismatic.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.box.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.box.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.box.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.box.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.box.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.box.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.box.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.box.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.box.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.box.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.box.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │ 1 │ [0.3, 0.3, 0.4] │
│ 2 │ x[4:6] │ boxMoving.box.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.box.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.box.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │
│ 2 │ x[4:6] │ boxMoving.box.v │
│ 3 │ x[7:10] │ boxMoving.box.q │
│ 4 │ x[11:13] │ boxMoving.box.w │
│ 5 │ derx[4:6] │ boxMoving.box.a │
│ 6 │ derx[7:10] │ boxMoving.box.derq │
│ 7 │ derx[11:13] │ boxMoving.box.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.box.v │ residue[1:3] │
│ 2 │ boxMoving.box.residue_w │ residue[4:6] │
│ 3 │ boxMoving.box.residue_f │ residue[7:9] │
│ 4 │ boxMoving.box.residue_t │ residue[10:12] │
│ 5 │ boxMoving.box.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.box.r │ result[2:4] │ [0.3, 0.3, 0.4] │
│ 3 │ boxMoving.box.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.box.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.box.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.box.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.box.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.box.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.box.r[1] │ 0.3 │ 1 │ 1.0 │
│ 2 │ boxMoving.box.r[2] │ 0.3 │ 1 │ 1.0 │
│ 3 │ boxMoving.box.r[3] │ 0.4 │ 1 │ 1.0 │
│ 4 │ boxMoving.box.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.box.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.box.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.box.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.box.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.box.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.box.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.box.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.box.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.box.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.24731005616100146 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000004734248907e-8 became < 0
contact normal = [-2.26e-06,-1.71e-06,1], contact position = [0.201,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball7) = -2.000004734248875e-8 became < 0
contact normal = [1.71e-06,-2.26e-06,1], contact position = [0.399,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball6) = -2.0000047342489175e-8 became < 0
contact normal = [-1.71e-06,2.26e-06,1], contact position = [0.201,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball5) = -2.000004734248875e-8 became < 0
contact normal = [2.26e-06,1.71e-06,1], contact position = [0.399,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.2481125660571883 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5331965901457278 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000053728345527e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball7) = -2.0000053624109652e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball6) = -2.000005195633312e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball5) = -2.0000051852097245e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5340932489465137 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6981642558349872 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000002109193716e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball7) = -1.999937767744656e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball6) = -1.999991893897259e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball5) = -1.999927552411946e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6991670990157088 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7933203793651138 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.9931744958305092e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball7) = -1.9990694560827858e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball6) = -1.994106593038438e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball5) = -2.0000015532540382e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7944441644217183 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8481668040359734 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000002958918e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball7) = -1.7374601686311956e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball6) = -1.958497377417097e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball5) = -1.69595754552709e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.849431030287405 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797326988491254 s (z[2] < 0)
distance(box,boxMoving.ball7) = -1.1392672904124347e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball5) = -2.0000000041587432e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797328451973824 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.1392636220617333e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball6) = -2.000000362194742e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811664389977623 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811666117163817 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978452972372389 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000029646597e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978456759745383 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000002716729238e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978476432172747 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000002047353616e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978480219461057 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000002620679725e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995008133684923 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995012373267285 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995034443000441 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.899503869685549 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081689816942726 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.000000001049624e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081713339213505 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000016912727e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.908183562872571 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.000000105050595e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081859133992267 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000001066602754e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101766591463938 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101791167805899 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101920196719218 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101945102341994 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139672883052976 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000483431793e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=57.7
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139713502815872 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000000023380247e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=57.6
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139925997600851 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000467229747e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=57
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139966276478274 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000000467456328e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=56.9
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.94 s
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 6 s (init: 0.0042 s, integration: 6 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2069
nSteps = 3016
nResidues = 14021 (includes residue calls for Jacobian)
nZeroCrossings = 5291
nJac = 746
nTimeEvents = 0
nStateEvents = 34
nRestartEvents = 34
nErrTestFails = 136
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 0.52 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes2.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────┼─────────┼───────┼─────────┤
│ 1 │ sphereMoving.r[1] │ 0.0 │ 1 │ 1.0 │
│ 2 │ sphereMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ sphereMoving.r[3] │ 0.0 │ 1 │ 1.0 │
│ 4 │ sphereMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ sphereMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ sphereMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ sphereMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ sphereMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ sphereMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ sphereMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ sphereMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ sphereMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ sphereMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.6772856461815322 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000103221454e-8 became < 0
contact normal = [1,3.29e-07,6.38e-08], contact position = [-2.5,-8.23e-08,-1.59e-08], c_res=1.1e+11, d_res=0.103
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6805673217281598 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.604523859549157 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000042421506716e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.31e-06,2.28e-07], c_res=1.1e+11, d_res=0.151
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.608067986620904 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.2377170487446953 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000021744128692e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.86e-06,5.39e-07], c_res=1.1e+11, d_res=0.222
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.241547117509829 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.670000719849833 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000017185844653e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.13e-06,6.87e-07], c_res=1.1e+11, d_res=0.326
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.6741432074212255 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.9650010850231467 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000052294577e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.26e-06,7.61e-07], c_res=1.1e+11, d_res=0.481
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.969487415670937 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.1661841009957588 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000007723373e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.33e-06,8.01e-07], c_res=1.1e+11, d_res=0.711
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.171053307859464 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3032414214915753 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000010420225165e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.37e-06,8.24e-07], c_res=1.1e+11, d_res=1.06
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3085451316993217 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3964536389386515 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000003210248078e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.39e-06,8.39e-07], c_res=1.1e+11, d_res=1.59
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.40226611806008 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.4596684178013386 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000182727477e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.41e-06,8.48e-07], c_res=1.1e+11, d_res=2.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.466109471122685 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5023347462234047 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000017570597e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.42e-06,8.54e-07], c_res=1.1e+11, d_res=3.86
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5096330034147374 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5308804788237578 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000119224454e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.58e-07], c_res=1.1e+11, d_res=6.58
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.539639348752486 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5495862810383714 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000035617481e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.6e-07], c_res=1.1e+11, d_res=14.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
Simulation is terminated at time = 6.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 3.5 s (init: 0.0055 s, integration: 3.5 s)
startTime = 0.0 s
stopTime = 6.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 6047
nSteps = 3785
nResidues = 14026 (includes residue calls for Jacobian)
nZeroCrossings = 9998
nJac = 653
nTimeEvents = 0
nStateEvents = 23
nRestartEvents = 23
nErrTestFails = 122
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 1.1 s
orderMax = 5
sparseSolver = false
... success of contactForceLaw_Ball.jl!
... success of contactForceLaw_ballWithBall.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ sphereMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ sphereMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ sphereMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ sphereMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ sphereMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ sphereMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ sphereMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ sphereMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ sphereMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ sphereMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ sphereMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │ 1 │ [0.0, 0.0, 0.0] │
│ 2 │ x[4:6] │ sphereMoving.v │ 1 │ [2.0, 0.0, -3.0] │
│ 3 │ x[7:10] │ sphereMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ sphereMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼───────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │
│ 2 │ x[4:6] │ sphereMoving.v │
│ 3 │ x[7:10] │ sphereMoving.q │
│ 4 │ x[11:13] │ sphereMoving.w │
│ 5 │ derx[4:6] │ sphereMoving.a │
│ 6 │ derx[7:10] │ sphereMoving.derq │
│ 7 │ derx[11:13] │ sphereMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - sphereMoving.v │ residue[1:3] │
│ 2 │ sphereMoving.residue_w │ residue[4:6] │
│ 3 │ sphereMoving.residue_f │ residue[7:9] │
│ 4 │ sphereMoving.residue_t │ residue[10:12] │
│ 5 │ sphereMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼───────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ sphereMoving.r │ result[2:4] │ [0.0, 0.0, 0.0] │
│ 3 │ sphereMoving.v │ result[5:7] │ [2.0, 0.0, -3.0] │
│ 4 │ sphereMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ sphereMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ sphereMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ sphereMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ sphereMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_45Deg.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ 2.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 0.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ -3.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ 2.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 0.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ -3.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: TwoBoxes
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ prisX.s │ 0.0 │ 1 │ 1.0 │
│ 2 │ prisY.s │ 0.0 │ 1 │ 1.0 │
│ 3 │ prisZ.s │ 0.0 │ 1 │ 1.0 │
│ 4 │ prisX.v │ 2.0 │ 1 │ 2.0 │
│ 5 │ prisY.v │ 0.0 │ 1 │ 1.0 │
│ 6 │ prisZ.v │ -3.0 │ 1 │ 3.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.43731521721763345 s (z[2] < 0)
distance(box,boxMoving) = -2.0000005749098553e-8 became < 0
contact normal = [1.72e-08,-7.57e-08,1], contact position = [0.875,1.89e-08,-2.5], c_res=1.1e+11, d_res=0.0941
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.4425862085910631 s (z[1] > 0)
distance(box,boxMoving) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 0.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.27 s (init: 0.0019 s, integration: 0.27 s)
startTime = 0.0 s
stopTime = 0.5 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 6 (includes 0 constraints)
nResults = 505
nSteps = 461
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 982
nJac = 96
nTimeEvents = 0
nStateEvents = 2
nRestartEvents = 2
nErrTestFails = 15
h0 = 3.4e-10 s
hMin = 3.4e-10 s
hMax = 0.18 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_Prismatic.jl!
... success of contactForceLaw_newtons_cradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion1_directHit.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion4_arbitraryHit.jl!
...test_Examples_Collision finished!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: DoublePendulumWithDampers
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev2.phi │ 0.0 │ 1 │ 1.0 │
│ 3 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev2.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.36 s (init: 0.011 s, integration: 0.35 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-6
nEquations = 4 (includes 0 constraints)
nResults = 5001
nSteps = 837
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 56
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 20
h0 = 2.3e-09 s
hMin = 2.3e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulumWithDampers.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_FallingBall1.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.093 s (init: 0.00091 s, integration: 0.092 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────┼─────────┼───────┼─────────┤
│ 1 │ revolute.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ revolute.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.11 s (init: 0.001 s, integration: 0.11 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2501
nSteps = 262
nResidues = 370 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 1
h0 = 8.3e-09 s
hMin = 8.3e-09 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithController
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ c.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.15 s (init: 0.039 s, integration: 0.11 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 3 (includes 0 constraints)
nResults = 2501
nSteps = 376
nResidues = 568 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 25
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 7.1e-07 s
hMin = 7.1e-07 s
hMax = 0.044 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithController.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithDamper
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.022 s (init: 0.012 s, integration: 0.01 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.1 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 51
nSteps = 136
nResidues = 230 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 5.8e-07 s
hMin = 5.8e-07 s
hMax = 0.085 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Move_DoublePendulum.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar.jl!
... Revolute joint connecting Fourbar2.bar3.frame2 with Fourbar2.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Move2
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────────┼─────────┼───────┼─────────┤
│ 1 │ fourbar.rev2.phi │ -1.5708 │ 1 │ 1.5708 │
│ 2 │ fourbar.rev3.phi │ 1.10715 │ 1 │ 1.10715 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 3.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.076 s (init: 0.018 s, integration: 0.058 s)
startTime = 0.0 s
stopTime = 3.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 2 (includes 2 constraints)
nResults = 1501
nSteps = 112
nResidues = 219 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 19
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 4
h0 = 2e-06 s
hMin = 2e-06 s
hMax = 0.056 s
orderMax = 5
sparseSolver = false
... success of Move_FourBar2.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalAngle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalTorque.jl!
... success of Move_AllVisualObjects.jl!
... success of Move_SolidFileMesh.jl!
... success of Visualize_AllVisualObjects.jl!
... success of Visualize_Assembly.jl!
... success of Visualize_GeometriesWithMaterial.jl!
... success of Visualize_GeometriesWithoutMaterial.jl!
... success of Visualize_SolidFileMesh.jl!
... success of Visualize_Solids.jl!
... success of Visualize_Text.jl!
... success of Visualize_TextFonts.jl!
... success of runexamples.jl
... success of all tests!
Test Summary: | Pass Total
Test Modia3D | 57 57
Testing Modia3D tests passed
Results with Julia v1.3.0
Testing was successful .
Last evaluation was ago and took 13 minutes, 51 seconds.
Click here to download the log file.
Click here to show the log contents.
Resolving package versions...
Installed SortingAlgorithms ─────────── v0.3.1
Installed Roots ─────────────────────── v0.8.3
Installed Unitful ───────────────────── v0.18.0
Installed DataStructures ────────────── v0.17.6
Installed StaticArrays ──────────────── v0.12.1
Installed Sundials ──────────────────── v3.8.1
Installed ModiaMath ─────────────────── v0.5.2
Installed CategoricalArrays ─────────── v0.7.3
Installed Compat ────────────────────── v2.2.0
Installed DocStringExtensions ───────── v0.8.1
Installed BinaryProvider ────────────── v0.5.8
Installed InvertedIndices ───────────── v1.0.0
Installed Parsers ───────────────────── v0.3.10
Installed Missings ──────────────────── v0.4.3
Installed TableTraits ───────────────── v1.0.0
Installed Parameters ────────────────── v0.12.0
Installed TreeViews ─────────────────── v0.3.0
Installed MacroTools ────────────────── v0.5.2
Installed FunctionWrappers ──────────── v1.0.0
Installed OrderedCollections ────────── v1.1.0
Installed ConstructionBase ──────────── v1.0.0
Installed JSON ──────────────────────── v0.21.0
Installed RecipesBase ───────────────── v0.7.0
Installed DataAPI ───────────────────── v1.1.0
Installed DataValueInterfaces ───────── v1.0.0
Installed ArrayInterface ────────────── v2.0.0
Installed DiffEqDiffTools ───────────── v1.5.0
Installed Tables ────────────────────── v0.2.11
Installed Requires ──────────────────── v0.5.2
Installed DiffEqBase ────────────────── v6.7.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed MuladdMacro ───────────────── v0.2.1
Installed RecursiveArrayTools ───────── v1.2.0
Installed PooledArrays ──────────────── v0.5.2
Installed Reexport ──────────────────── v0.2.0
Installed DataFrames ────────────────── v0.19.4
Installed RecursiveFactorization ────── v0.1.0
Installed IterativeSolvers ──────────── v0.8.1
Installed Modia3D ───────────────────── v0.4.0
Updating `~/.julia/environments/v1.3/Project.toml`
[07f2c1e0] + Modia3D v0.4.0
Updating `~/.julia/environments/v1.3/Manifest.toml`
[4fba245c] + ArrayInterface v2.0.0
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.3
[34da2185] + Compat v2.2.0
[187b0558] + ConstructionBase v1.0.0
[9a962f9c] + DataAPI v1.1.0
[a93c6f00] + DataFrames v0.19.4
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[2b5f629d] + DiffEqBase v6.7.0
[01453d9d] + DiffEqDiffTools v1.5.0
[ffbed154] + DocStringExtensions v0.8.1
[069b7b12] + FunctionWrappers v1.0.0
[41ab1584] + InvertedIndices v1.0.0
[42fd0dbc] + IterativeSolvers v0.8.1
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[1914dd2f] + MacroTools v0.5.2
[e1d29d7a] + Missings v0.4.3
[07f2c1e0] + Modia3D v0.4.0
[67ccffd1] + ModiaMath v0.5.2
[46d2c3a1] + MuladdMacro v0.2.1
[bac558e1] + OrderedCollections v1.1.0
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.10
[2dfb63ee] + PooledArrays v0.5.2
[3cdcf5f2] + RecipesBase v0.7.0
[731186ca] + RecursiveArrayTools v1.2.0
[f2c3362d] + RecursiveFactorization v0.1.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v0.5.2
[f2b01f46] + Roots v0.8.3
[a2af1166] + SortingAlgorithms v0.3.1
[90137ffa] + StaticArrays v0.12.1
[c3572dad] + Sundials v3.8.1
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[a2a6695c] + TreeViews v0.3.0
[1986cc42] + Unitful v0.18.0
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Sundials → `~/.julia/packages/Sundials/MllUG/deps/build.log`
Testing Modia3D
Status `/tmp/jl_TyG93f/Manifest.toml`
[4fba245c] ArrayInterface v2.0.0
[b99e7846] BinaryProvider v0.5.8
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[187b0558] ConstructionBase v1.0.0
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[2b5f629d] DiffEqBase v6.7.0
[01453d9d] DiffEqDiffTools v1.5.0
[ffbed154] DocStringExtensions v0.8.1
[069b7b12] FunctionWrappers v1.0.0
[41ab1584] InvertedIndices v1.0.0
[42fd0dbc] IterativeSolvers v0.8.1
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[07f2c1e0] Modia3D v0.4.0
[67ccffd1] ModiaMath v0.5.2
[46d2c3a1] MuladdMacro v0.2.1
[bac558e1] OrderedCollections v1.1.0
[d96e819e] Parameters v0.12.0
[69de0a69] Parsers v0.3.10
[2dfb63ee] PooledArrays v0.5.2
[3cdcf5f2] RecipesBase v0.7.0
[731186ca] RecursiveArrayTools v1.2.0
[f2c3362d] RecursiveFactorization v0.1.0
[189a3867] Reexport v0.2.0
[ae029012] Requires v0.5.2
[f2b01f46] Roots v0.8.3
[a2af1166] SortingAlgorithms v0.3.1
[90137ffa] StaticArrays v0.12.1
[c3572dad] Sundials v3.8.1
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[a2a6695c] TreeViews v0.3.0
[1986cc42] Unitful v0.18.0
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
Importing Modia3D Version 0.4.0 (2019-09-27)
Importing ModiaMath Version 0.5.2 (2019-07-10)
PyPlot not available (plot commands will be ignored).
Try to install PyPlot. See hints here:
https://github.com/ModiaSim/ModiaMath.jl/wiki/Installing-PyPlot-in-a-robust-way.
┌ Warning:
│ Environment variable "DLR_VISUALIZATION" not defined.
│ Include ENV["DLR_VISUALIZATION"] = <path-to-Visualization/Extras/SimVis> into your HOME/.julia/config/startup.jl file.
│
│ No Renderer is used in Modia3D (so, animation is switched off).
└ @ Modia3D.DLR_Visualization ~/.julia/packages/Modia3D/r9s9x/src/renderer/DLR_Visualization/renderer.jl:87
... success of test_solidProperties.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
progress: integrated up to time = 0.002 s
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 9.5 s (init: 8 s, integration: 1.5 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ControllerDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DamperMacro.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Simulate_FourBar.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... pos_angle2(time=0.5) = 2.24
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.11 s (init: 0.00088 s, integration: 0.11 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 206
nResidues = 267 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 23
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 1.2e-08 s
hMin = 1.2e-08 s
hMax = 0.049 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithFixedJoint.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_2Rev_ZylZ_BarX.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_3Rev_ZylZ_BarX_BarY.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_InertiaTensor.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_KinematicRevoluteJoints.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_zAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_xAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_yAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_noMacros.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal1Assembly.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal4Assemblies.jl!
WARNING: replacing module test_massComputation.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... success of volume_computation3D_obj.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Move_Pendulum.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Visualize_Beam.jl!
...test_Examples finished!
WARNING: replacing module TestExamples.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_Billiards_OneBall!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: BouncingBall1
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼────────┼─────────┼───────┼─────────┤
│ 1 │ h │ 0.2 │ 0 │ 0.2 │
│ 2 │ v │ 0.0 │ 0 │ 1.0 │
... h0 = 0.2
flying = true
-h = -0.2 (became <= 0)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.2019275108811498 s (z[1] > 0)
-h = 1.6181500583911657e-14 (became > 0)
... v = 1.3866362172208557
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.484626025952448 s (z[1] > 0)
-h = 2.71657696337968e-14 (became > 0)
... v = 0.9706453509400057
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.682514985967628 s (z[1] > 0)
-h = 1.3320941572025902e-14 (became > 0)
... v = 0.6794517427662368
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.8210372566626214 s (z[1] > 0)
-h = 6.938893903907228e-18 (became > 0)
... v = 0.47561621292614215
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9180028433604212 s (z[1] > 0)
-h = 2.3418766925686896e-17 (became > 0)
... v = 0.3329313347031544
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9858787506124347 s (z[1] > 0)
-h = 3.80034545499619e-15 (became > 0)
... v = 0.23305186965963645
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 1.0 s
BouncingBall model is terminated (flying = true)
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.93 s (init: 0.71 s, integration: 0.23 s)
startTime = 0.0 s
stopTime = 1.0 s
interval = 0.02 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 63
nSteps = 125
nResidues = 345 (includes residue calls for Jacobian)
nZeroCrossings = 237
nJac = 110
nTimeEvents = 0
nStateEvents = 6
nRestartEvents = 6
nErrTestFails = 0
h0 = 7.2e-07 s
hMin = 7.2e-07 s
hMax = 0.27 s
orderMax = 3
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_BouncingBall.jl
... success of examples/collisions/Simulate_NewtonsCradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_SlidingAndRollingBall.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_TwoCollidingBalls.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: YouBot
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────────────────┼─────────┼───────┼─────────┤
│ 1 │ link1.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ link1.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ link2.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ link2.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 5 │ link3.rev.rev.phi │ 1.5708 │ 1 │ 1.5708 │
│ 6 │ link3.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 7 │ link4.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 8 │ link4.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 9 │ link5.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 10 │ link5.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 11 │ gripper.prism.prism.s │ 0.0 │ 1 │ 1.0 │
│ 12 │ gripper.prism.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 13 │ sphere.r[1] │ -0.125 │ 1 │ 1.0 │
│ 14 │ sphere.r[2] │ 0.0 │ 1 │ 1.0 │
│ 15 │ sphere.r[3] │ 0.03 │ 1 │ 1.0 │
│ 16 │ link1.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 17 │ link2.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 18 │ link3.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 19 │ link4.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 20 │ link5.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 21 │ gripper.prism.prism.v │ 0.0 │ 1 │ 1.0 │
│ 22 │ sphere.v[1] │ 0.0 │ 1 │ 1.0 │
│ 23 │ sphere.v[2] │ 0.0 │ 1 │ 1.0 │
│ 24 │ sphere.v[3] │ 0.0 │ 1 │ 1.0 │
│ 25 │ sphere.q[1] │ 0.0 │ 0 │ 1.0 │
│ 26 │ sphere.q[2] │ 0.0 │ 0 │ 1.0 │
│ 27 │ sphere.q[3] │ 0.0 │ 0 │ 1.0 │
│ 28 │ sphere.q[4] │ 1.0 │ 0 │ 1.0 │
│ 29 │ sphere.w[1] │ 0.0 │ 1 │ 1.0 │
│ 30 │ sphere.w[2] │ 0.0 │ 1 │ 1.0 │
│ 31 │ sphere.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 7.261196339086959e-5 s (z[2] < 0)
distance(table.plate,sphere) = -2.0000000037447373e-8 became < 0
contact normal = [4.51e-08,6.28e-08,1], contact position = [0.585,-1.57e-09,0.375], c_res=1.24e+06, d_res=1e+03
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.417313819072049 s (z[2] < 0)
distance(sphere,gripper.gripper_right_finger) = -2.0000000393229984e-8 became < 0
contact normal = [-1,-0.00507,-2.05e-05], contact position = [0.56,-0.000127,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.4173142226300918 s (z[2] < 0)
distance(sphere,gripper.gripper_left_finger) = -2.0000006971107646e-8 became < 0
contact normal = [-1,0.00702,2.02e-05], contact position = [0.56,0.000175,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
State event (zero-crossing) at time = 0.42197539326597844 s (z[1] > 0)
distance(sphere,gripper.gripper_left_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.421976224209762 s (z[1] > 0)
distance(sphere,gripper.gripper_right_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
progress: integrated up to time = 0.9 s
progress: integrated up to time = 2 s
progress: integrated up to time = 2.2 s
progress: integrated up to time = 2.2 s
progress: integrated up to time = 2.3 s
progress: integrated up to time = 2.4 s
progress: integrated up to time = 2.4 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 3.2 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
State event (zero-crossing) at time = 3.544805661448877 s (z[1] > 0)
distance(table.plate,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 3.5 s
State event (zero-crossing) at time = 3.772099387510426 s (z[2] < 0)
distance(ground,sphere) = -2.0000000104326316e-8 became < 0
contact normal = [-5.5e-07,-3e-06,1], contact position = [0.939,-0.000237,-3.46e-06], c_res=1.24e+06, d_res=0.32
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.787117001624274 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.125658766045461 s (z[2] < 0)
distance(ground,sphere) = -2.000011756920415e-8 became < 0
contact normal = [-5.51e-07,-3e-06,1], contact position = [1.03,-0.000263,-3.4e-06], c_res=1.24e+06, d_res=0.519
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.1 s
State event (zero-crossing) at time = 4.142357296028154 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.347238032219403 s (z[2] < 0)
distance(ground,sphere) = -2.0000000248254154e-8 became < 0
contact normal = [-5.52e-07,-3e-06,1], contact position = [1.09,-0.00028,-3.37e-06], c_res=1.24e+06, d_res=0.857
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.366036388703918 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.485371689085727 s (z[2] < 0)
distance(ground,sphere) = -2.000002838776016e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.13,-0.000291,-3.34e-06], c_res=1.24e+06, d_res=1.47
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.5 s
State event (zero-crossing) at time = 4.50711993227886 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.570603069658777 s (z[2] < 0)
distance(ground,sphere) = -2.000001311286435e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.15,-0.000298,-3.33e-06], c_res=1.24e+06, d_res=2.77
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.5979981506589205 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.6 s
State event (zero-crossing) at time = 4.621567133614952 s (z[2] < 0)
distance(ground,sphere) = -2.000000589083613e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.17,-0.000302,-3.32e-06], c_res=1.24e+06, d_res=7.5
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 2.2e+02 s (init: 0.36 s, integration: 2.2e+02 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-5
nEquations = 31 (includes 1 constraints)
nResults = 5035
nSteps = 6038
nResidues = 144452 (includes residue calls for Jacobian)
nZeroCrossings = 11202
nJac = 4234
nTimeEvents = 0
nStateEvents = 17
nRestartEvents = 17
nErrTestFails = 1721
h0 = 1.8e-09 s
hMin = 1.8e-09 s
hMax = 0.053 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_YouBot.jl
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Collision_3Elements.jl!
... success of Test_Collision.jl!
... success of Test_Collision_moreRevolutes.jl!
... success of Test_Collision_StarSetting.jl!
... success of Test_MiniBsp.jl!
... success of Test_Solids.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ContactBoxOnTable.jl!
WARNING: replacing module Simulate_YouBot.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_YouBotBoxOnTable.jl!
... success of collision_2_boxes.jl!
... success of collision_ballWithBall.jl!
... success of collision_ballWithBox.jl!
... success of collision_ballWithBox_45Deg.jl!
... success of collision_BallWithBox_Prismatic.jl!
WARNING: replacing module collision_ballWithBox_45Deg.
... success of collision_ballWithBox_45Deg.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: NewtonsCradle
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ -1.0472 │ 1 │ 1.0472 │
│ 2 │ rev2.phi │ -1.0472 │ 1 │ 1.0472 │
│ 3 │ rev3.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev4.phi │ 1.0472 │ 1 │ 1.0472 │
│ 5 │ rev5.phi │ 1.0472 │ 1 │ 1.0472 │
│ 6 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 7 │ rev2.w │ 0.0 │ 1 │ 1.0 │
│ 8 │ rev3.w │ 0.0 │ 1 │ 1.0 │
│ 9 │ rev4.w │ 0.0 │ 1 │ 1.0 │
│ 10 │ rev5.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 1.0878031474718333 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000077594062304e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.11
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000077260995397e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.11
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0908094518650024 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0938480230542378 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000232248129635e-8 became < 0
contact normal = [0,1,-0.000784], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.0667
distance(pendulum5.sphere,pendulum4.sphere) = -2.000023202608503e-8 became < 0
contact normal = [0,-1,-0.000784], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.0667
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0958883290568509 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0985275695684327 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000000211517488e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.169
distance(pendulum3.sphere,pendulum2.sphere) = -1.9999999101294463e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.169
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.1018053667261674 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1750114228447495 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9999989109287242e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.262
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000766629e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.262
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1785879880615164 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1930977548240014 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000009426368592e-8 became < 0
contact normal = [0,1,-0.00063], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.147
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000012757037666e-8 became < 0
contact normal = [0,-1,-0.00063], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.147
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1954887018752087 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.2073414785973235 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.999992316203958e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.347
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.347
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.211125697316102 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.306987610498805 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000038292167233e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.537
distance(pendulum3.sphere,pendulum2.sphere) = -1.9998782851970986e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.537
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.311116540157841 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.3389794846640575 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000039291367955e-8 became < 0
contact normal = [0,1,-0.00065], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.336
distance(pendulum5.sphere,pendulum4.sphere) = -1.99989548255175e-8 became < 0
contact normal = [0,-1,-0.00065], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.336
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.341800682588432 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.371038706105848 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000006983877938e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.886
distance(pendulum3.sphere,pendulum2.sphere) = -1.9988123378666955e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.886
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.375601280236619 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.586849755374663 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9609640355966462e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.37
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000080924731378e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.37
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.591827089433919 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.623516942618943 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -1.96331674251482e-8 became < 0
contact normal = [0,1,-0.000809], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.73
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,-0.000809], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.73
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.626809172298678 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.651102476406292 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.694994378187431e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.68
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000034739453554e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.68
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.656286321908144 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
progress: integrated up to time = 8.6 s
Simulation is terminated at time = 10.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 5.6 s (init: 0.0062 s, integration: 5.6 s)
startTime = 0.0 s
stopTime = 10.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 10 (includes 0 constraints)
nResults = 10049
nSteps = 3394
nResidues = 11111 (includes residue calls for Jacobian)
nZeroCrossings = 13578
nJac = 644
nTimeEvents = 0
nStateEvents = 24
nRestartEvents = 24
nErrTestFails = 183
h0 = 3.7e-10 s
hMin = 3.7e-10 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... success of collision_newtons_cradle.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │ 1 │ [1.0, 0.0, 0.15] │
│ 2 │ x[4:6] │ boxMoving.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │
│ 2 │ x[4:6] │ boxMoving.v │
│ 3 │ x[7:10] │ boxMoving.q │
│ 4 │ x[11:13] │ boxMoving.w │
│ 5 │ derx[4:6] │ boxMoving.a │
│ 6 │ derx[7:10] │ boxMoving.derq │
│ 7 │ derx[11:13] │ boxMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.v │ residue[1:3] │
│ 2 │ boxMoving.residue_w │ residue[4:6] │
│ 3 │ boxMoving.residue_f │ residue[7:9] │
│ 4 │ boxMoving.residue_t │ residue[10:12] │
│ 5 │ boxMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.r │ result[2:4] │ [1.0, 0.0, 0.15] │
│ 3 │ boxMoving.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.r[1] │ 1.0 │ 1 │ 1.0 │
│ 2 │ boxMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ boxMoving.r[3] │ 0.15 │ 1 │ 1.0 │
│ 4 │ boxMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.46 s (init: 0.005 s, integration: 0.45 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2001
nSteps = 22
nResidues = 282 (includes residue calls for Jacobian)
nZeroCrossings = 2022
nJac = 20
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 0
h0 = 1e-06 s
hMin = 1e-06 s
hMax = 0.95 s
orderMax = 2
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ -6.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 2.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ 4.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ -6.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 2.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ 4.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes_Prismatic.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.box.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.box.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.box.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.box.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.box.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.box.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.box.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.box.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.box.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.box.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.box.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │ 1 │ [0.3, 0.3, 0.4] │
│ 2 │ x[4:6] │ boxMoving.box.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.box.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.box.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │
│ 2 │ x[4:6] │ boxMoving.box.v │
│ 3 │ x[7:10] │ boxMoving.box.q │
│ 4 │ x[11:13] │ boxMoving.box.w │
│ 5 │ derx[4:6] │ boxMoving.box.a │
│ 6 │ derx[7:10] │ boxMoving.box.derq │
│ 7 │ derx[11:13] │ boxMoving.box.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.box.v │ residue[1:3] │
│ 2 │ boxMoving.box.residue_w │ residue[4:6] │
│ 3 │ boxMoving.box.residue_f │ residue[7:9] │
│ 4 │ boxMoving.box.residue_t │ residue[10:12] │
│ 5 │ boxMoving.box.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.box.r │ result[2:4] │ [0.3, 0.3, 0.4] │
│ 3 │ boxMoving.box.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.box.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.box.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.box.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.box.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.box.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.box.r[1] │ 0.3 │ 1 │ 1.0 │
│ 2 │ boxMoving.box.r[2] │ 0.3 │ 1 │ 1.0 │
│ 3 │ boxMoving.box.r[3] │ 0.4 │ 1 │ 1.0 │
│ 4 │ boxMoving.box.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.box.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.box.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.box.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.box.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.box.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.box.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.box.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.box.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.box.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.24731005616100146 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000004734248907e-8 became < 0
contact normal = [-2.26e-06,-1.71e-06,1], contact position = [0.201,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball7) = -2.000004734248875e-8 became < 0
contact normal = [1.71e-06,-2.26e-06,1], contact position = [0.399,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball6) = -2.0000047342489175e-8 became < 0
contact normal = [-1.71e-06,2.26e-06,1], contact position = [0.201,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball5) = -2.000004734248875e-8 became < 0
contact normal = [2.26e-06,1.71e-06,1], contact position = [0.399,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.2481125660571883 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5331965901457278 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000053728345527e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball7) = -2.0000053624109652e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball6) = -2.000005195633312e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball5) = -2.0000051852097245e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5340932489465137 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6981642558349872 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000002109193716e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball7) = -1.999937767744656e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball6) = -1.999991893897259e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball5) = -1.999927552411946e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6991670990157088 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7933203793651138 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.9931744958305092e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball7) = -1.9990694560827858e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball6) = -1.994106593038438e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball5) = -2.0000015532540382e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7944441644217183 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8481668040359734 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000002958918e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball7) = -1.7374601686311956e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball6) = -1.958497377417097e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball5) = -1.69595754552709e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.849431030287405 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797326988491254 s (z[2] < 0)
distance(box,boxMoving.ball7) = -1.1392672904124347e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball5) = -2.0000000041587432e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797328451973824 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.1392636220617333e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball6) = -2.000000362194742e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811664389977623 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811666117163817 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978452972372389 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000029646597e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978456759745383 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000002716729238e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978476432172747 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000002047353616e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978480219461057 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000002620679725e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995008133684923 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995012373267285 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995034443000441 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.899503869685549 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081689816942726 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.000000001049624e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081713339213505 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000016912727e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.908183562872571 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.000000105050595e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081859133992267 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000001066602754e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101766591463938 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101791167805899 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101920196719218 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101945102341994 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139672883052976 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000483431793e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=57.7
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139713502815872 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000000023380247e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=57.6
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139925997600851 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000467229747e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=57
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139966276478274 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000000467456328e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=56.9
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.93 s
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 6 s (init: 0.0037 s, integration: 6 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2069
nSteps = 3016
nResidues = 14021 (includes residue calls for Jacobian)
nZeroCrossings = 5291
nJac = 746
nTimeEvents = 0
nStateEvents = 34
nRestartEvents = 34
nErrTestFails = 136
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 0.52 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes2.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────┼─────────┼───────┼─────────┤
│ 1 │ sphereMoving.r[1] │ 0.0 │ 1 │ 1.0 │
│ 2 │ sphereMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ sphereMoving.r[3] │ 0.0 │ 1 │ 1.0 │
│ 4 │ sphereMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ sphereMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ sphereMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ sphereMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ sphereMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ sphereMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ sphereMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ sphereMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ sphereMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ sphereMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.6772856461815322 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000103221454e-8 became < 0
contact normal = [1,3.29e-07,6.38e-08], contact position = [-2.5,-8.23e-08,-1.59e-08], c_res=1.1e+11, d_res=0.103
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6805673217281598 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.604523859549157 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000042421506716e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.31e-06,2.28e-07], c_res=1.1e+11, d_res=0.151
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.608067986620904 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.2377170487446953 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000021744128692e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.86e-06,5.39e-07], c_res=1.1e+11, d_res=0.222
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.241547117509829 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.670000719849833 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000017185844653e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.13e-06,6.87e-07], c_res=1.1e+11, d_res=0.326
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.6741432074212255 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.9650010850231467 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000052294577e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.26e-06,7.61e-07], c_res=1.1e+11, d_res=0.481
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.969487415670937 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.1661841009957588 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000007723373e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.33e-06,8.01e-07], c_res=1.1e+11, d_res=0.711
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.171053307859464 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3032414214915753 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000010420225165e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.37e-06,8.24e-07], c_res=1.1e+11, d_res=1.06
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3085451316993217 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3964536389386515 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000003210248078e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.39e-06,8.39e-07], c_res=1.1e+11, d_res=1.59
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.40226611806008 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.4596684178013386 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000182727477e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.41e-06,8.48e-07], c_res=1.1e+11, d_res=2.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.466109471122685 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5023347462234047 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000017570597e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.42e-06,8.54e-07], c_res=1.1e+11, d_res=3.86
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5096330034147374 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5308804788237578 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000119224454e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.58e-07], c_res=1.1e+11, d_res=6.58
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.539639348752486 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5495862810383714 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000035617481e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.6e-07], c_res=1.1e+11, d_res=14.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
Simulation is terminated at time = 6.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 3.9 s (init: 0.0045 s, integration: 3.9 s)
startTime = 0.0 s
stopTime = 6.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 6047
nSteps = 3785
nResidues = 14026 (includes residue calls for Jacobian)
nZeroCrossings = 9998
nJac = 653
nTimeEvents = 0
nStateEvents = 23
nRestartEvents = 23
nErrTestFails = 122
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 1.1 s
orderMax = 5
sparseSolver = false
... success of contactForceLaw_Ball.jl!
... success of contactForceLaw_ballWithBall.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ sphereMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ sphereMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ sphereMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ sphereMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ sphereMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ sphereMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ sphereMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ sphereMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ sphereMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ sphereMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ sphereMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │ 1 │ [0.0, 0.0, 0.0] │
│ 2 │ x[4:6] │ sphereMoving.v │ 1 │ [2.0, 0.0, -3.0] │
│ 3 │ x[7:10] │ sphereMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ sphereMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼───────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │
│ 2 │ x[4:6] │ sphereMoving.v │
│ 3 │ x[7:10] │ sphereMoving.q │
│ 4 │ x[11:13] │ sphereMoving.w │
│ 5 │ derx[4:6] │ sphereMoving.a │
│ 6 │ derx[7:10] │ sphereMoving.derq │
│ 7 │ derx[11:13] │ sphereMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - sphereMoving.v │ residue[1:3] │
│ 2 │ sphereMoving.residue_w │ residue[4:6] │
│ 3 │ sphereMoving.residue_f │ residue[7:9] │
│ 4 │ sphereMoving.residue_t │ residue[10:12] │
│ 5 │ sphereMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼───────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ sphereMoving.r │ result[2:4] │ [0.0, 0.0, 0.0] │
│ 3 │ sphereMoving.v │ result[5:7] │ [2.0, 0.0, -3.0] │
│ 4 │ sphereMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ sphereMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ sphereMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ sphereMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ sphereMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_45Deg.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ 2.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 0.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ -3.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ 2.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 0.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ -3.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: TwoBoxes
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ prisX.s │ 0.0 │ 1 │ 1.0 │
│ 2 │ prisY.s │ 0.0 │ 1 │ 1.0 │
│ 3 │ prisZ.s │ 0.0 │ 1 │ 1.0 │
│ 4 │ prisX.v │ 2.0 │ 1 │ 2.0 │
│ 5 │ prisY.v │ 0.0 │ 1 │ 1.0 │
│ 6 │ prisZ.v │ -3.0 │ 1 │ 3.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.43731521721763345 s (z[2] < 0)
distance(box,boxMoving) = -2.0000005749098553e-8 became < 0
contact normal = [1.72e-08,-7.57e-08,1], contact position = [0.875,1.89e-08,-2.5], c_res=1.1e+11, d_res=0.0941
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.4425862085910631 s (z[1] > 0)
distance(box,boxMoving) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 0.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.36 s (init: 0.0027 s, integration: 0.36 s)
startTime = 0.0 s
stopTime = 0.5 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 6 (includes 0 constraints)
nResults = 505
nSteps = 461
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 982
nJac = 96
nTimeEvents = 0
nStateEvents = 2
nRestartEvents = 2
nErrTestFails = 15
h0 = 3.4e-10 s
hMin = 3.4e-10 s
hMax = 0.18 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_Prismatic.jl!
... success of contactForceLaw_newtons_cradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion1_directHit.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion4_arbitraryHit.jl!
...test_Examples_Collision finished!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: DoublePendulumWithDampers
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev2.phi │ 0.0 │ 1 │ 1.0 │
│ 3 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev2.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.44 s (init: 0.014 s, integration: 0.42 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-6
nEquations = 4 (includes 0 constraints)
nResults = 5001
nSteps = 837
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 56
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 20
h0 = 2.3e-09 s
hMin = 2.3e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulumWithDampers.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_FallingBall1.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.12 s (init: 0.001 s, integration: 0.12 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────┼─────────┼───────┼─────────┤
│ 1 │ revolute.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ revolute.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.16 s (init: 0.0022 s, integration: 0.16 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2501
nSteps = 262
nResidues = 370 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 1
h0 = 8.3e-09 s
hMin = 8.3e-09 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithController
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ c.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.17 s (init: 0.038 s, integration: 0.13 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 3 (includes 0 constraints)
nResults = 2501
nSteps = 376
nResidues = 568 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 25
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 7.1e-07 s
hMin = 7.1e-07 s
hMax = 0.044 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithController.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithDamper
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.019 s (init: 0.0098 s, integration: 0.0095 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.1 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 51
nSteps = 136
nResidues = 230 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 5.8e-07 s
hMin = 5.8e-07 s
hMax = 0.085 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Move_DoublePendulum.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar.jl!
... Revolute joint connecting Fourbar2.bar3.frame2 with Fourbar2.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Move2
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────────┼─────────┼───────┼─────────┤
│ 1 │ fourbar.rev2.phi │ -1.5708 │ 1 │ 1.5708 │
│ 2 │ fourbar.rev3.phi │ 1.10715 │ 1 │ 1.10715 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 3.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.071 s (init: 0.013 s, integration: 0.057 s)
startTime = 0.0 s
stopTime = 3.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 2 (includes 2 constraints)
nResults = 1501
nSteps = 112
nResidues = 219 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 19
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 4
h0 = 2e-06 s
hMin = 2e-06 s
hMax = 0.056 s
orderMax = 5
sparseSolver = false
... success of Move_FourBar2.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalAngle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalTorque.jl!
... success of Move_AllVisualObjects.jl!
... success of Move_SolidFileMesh.jl!
... success of Visualize_AllVisualObjects.jl!
... success of Visualize_Assembly.jl!
... success of Visualize_GeometriesWithMaterial.jl!
... success of Visualize_GeometriesWithoutMaterial.jl!
... success of Visualize_SolidFileMesh.jl!
... success of Visualize_Solids.jl!
... success of Visualize_Text.jl!
... success of Visualize_TextFonts.jl!
... success of runexamples.jl
... success of all tests!
Test Summary: | Pass Total
Test Modia3D | 57 57
Testing Modia3D tests passed
Results with Julia v1.3.1-pre-7704df0a5a
Testing was successful .
Last evaluation was ago and took 13 minutes, 36 seconds.
Click here to download the log file.
Click here to show the log contents.
Resolving package versions...
Installed FunctionWrappers ──────────── v1.0.0
Installed Tables ────────────────────── v0.2.11
Installed ConstructionBase ──────────── v1.0.0
Installed Unitful ───────────────────── v0.18.0
Installed DataStructures ────────────── v0.17.6
Installed IterativeSolvers ──────────── v0.8.1
Installed DataFrames ────────────────── v0.19.4
Installed Compat ────────────────────── v2.2.0
Installed MacroTools ────────────────── v0.5.2
Installed Missings ──────────────────── v0.4.3
Installed StaticArrays ──────────────── v0.12.1
Installed TableTraits ───────────────── v1.0.0
Installed Roots ─────────────────────── v0.8.3
Installed PooledArrays ──────────────── v0.5.2
Installed BinaryProvider ────────────── v0.5.8
Installed Sundials ──────────────────── v3.8.1
Installed InvertedIndices ───────────── v1.0.0
Installed DocStringExtensions ───────── v0.8.1
Installed Requires ──────────────────── v0.5.2
Installed Parameters ────────────────── v0.12.0
Installed ArrayInterface ────────────── v2.0.0
Installed MuladdMacro ───────────────── v0.2.1
Installed RecursiveFactorization ────── v0.1.0
Installed RecursiveArrayTools ───────── v1.2.0
Installed DataValueInterfaces ───────── v1.0.0
Installed Reexport ──────────────────── v0.2.0
Installed ModiaMath ─────────────────── v0.5.2
Installed CategoricalArrays ─────────── v0.7.3
Installed DiffEqBase ────────────────── v6.7.0
Installed RecipesBase ───────────────── v0.7.0
Installed DataAPI ───────────────────── v1.1.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed OrderedCollections ────────── v1.1.0
Installed JSON ──────────────────────── v0.21.0
Installed Parsers ───────────────────── v0.3.10
Installed TreeViews ─────────────────── v0.3.0
Installed DiffEqDiffTools ───────────── v1.5.0
Installed SortingAlgorithms ─────────── v0.3.1
Installed Modia3D ───────────────────── v0.4.0
Updating `~/.julia/environments/v1.3/Project.toml`
[07f2c1e0] + Modia3D v0.4.0
Updating `~/.julia/environments/v1.3/Manifest.toml`
[4fba245c] + ArrayInterface v2.0.0
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.3
[34da2185] + Compat v2.2.0
[187b0558] + ConstructionBase v1.0.0
[9a962f9c] + DataAPI v1.1.0
[a93c6f00] + DataFrames v0.19.4
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[2b5f629d] + DiffEqBase v6.7.0
[01453d9d] + DiffEqDiffTools v1.5.0
[ffbed154] + DocStringExtensions v0.8.1
[069b7b12] + FunctionWrappers v1.0.0
[41ab1584] + InvertedIndices v1.0.0
[42fd0dbc] + IterativeSolvers v0.8.1
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[1914dd2f] + MacroTools v0.5.2
[e1d29d7a] + Missings v0.4.3
[07f2c1e0] + Modia3D v0.4.0
[67ccffd1] + ModiaMath v0.5.2
[46d2c3a1] + MuladdMacro v0.2.1
[bac558e1] + OrderedCollections v1.1.0
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.10
[2dfb63ee] + PooledArrays v0.5.2
[3cdcf5f2] + RecipesBase v0.7.0
[731186ca] + RecursiveArrayTools v1.2.0
[f2c3362d] + RecursiveFactorization v0.1.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v0.5.2
[f2b01f46] + Roots v0.8.3
[a2af1166] + SortingAlgorithms v0.3.1
[90137ffa] + StaticArrays v0.12.1
[c3572dad] + Sundials v3.8.1
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[a2a6695c] + TreeViews v0.3.0
[1986cc42] + Unitful v0.18.0
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Sundials → `~/.julia/packages/Sundials/MllUG/deps/build.log`
Testing Modia3D
Status `/tmp/jl_z9zmuN/Manifest.toml`
[4fba245c] ArrayInterface v2.0.0
[b99e7846] BinaryProvider v0.5.8
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[187b0558] ConstructionBase v1.0.0
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[2b5f629d] DiffEqBase v6.7.0
[01453d9d] DiffEqDiffTools v1.5.0
[ffbed154] DocStringExtensions v0.8.1
[069b7b12] FunctionWrappers v1.0.0
[41ab1584] InvertedIndices v1.0.0
[42fd0dbc] IterativeSolvers v0.8.1
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[07f2c1e0] Modia3D v0.4.0
[67ccffd1] ModiaMath v0.5.2
[46d2c3a1] MuladdMacro v0.2.1
[bac558e1] OrderedCollections v1.1.0
[d96e819e] Parameters v0.12.0
[69de0a69] Parsers v0.3.10
[2dfb63ee] PooledArrays v0.5.2
[3cdcf5f2] RecipesBase v0.7.0
[731186ca] RecursiveArrayTools v1.2.0
[f2c3362d] RecursiveFactorization v0.1.0
[189a3867] Reexport v0.2.0
[ae029012] Requires v0.5.2
[f2b01f46] Roots v0.8.3
[a2af1166] SortingAlgorithms v0.3.1
[90137ffa] StaticArrays v0.12.1
[c3572dad] Sundials v3.8.1
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[a2a6695c] TreeViews v0.3.0
[1986cc42] Unitful v0.18.0
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
Importing Modia3D Version 0.4.0 (2019-09-27)
Importing ModiaMath Version 0.5.2 (2019-07-10)
PyPlot not available (plot commands will be ignored).
Try to install PyPlot. See hints here:
https://github.com/ModiaSim/ModiaMath.jl/wiki/Installing-PyPlot-in-a-robust-way.
┌ Warning:
│ Environment variable "DLR_VISUALIZATION" not defined.
│ Include ENV["DLR_VISUALIZATION"] = <path-to-Visualization/Extras/SimVis> into your HOME/.julia/config/startup.jl file.
│
│ No Renderer is used in Modia3D (so, animation is switched off).
└ @ Modia3D.DLR_Visualization ~/.julia/packages/Modia3D/r9s9x/src/renderer/DLR_Visualization/renderer.jl:87
... success of test_solidProperties.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
progress: integrated up to time = 0.002 s
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 9.3 s (init: 8.2 s, integration: 1.1 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ControllerDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DamperMacro.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Simulate_FourBar.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... pos_angle2(time=0.5) = 2.24
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.084 s (init: 0.0032 s, integration: 0.081 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 206
nResidues = 267 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 23
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 1.2e-08 s
hMin = 1.2e-08 s
hMax = 0.049 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithFixedJoint.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_2Rev_ZylZ_BarX.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_3Rev_ZylZ_BarX_BarY.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_InertiaTensor.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_KinematicRevoluteJoints.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Dynamic_Pendulum_zAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_xAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_yAxis.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Prismatic_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_xAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_yAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_zAxis.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint rev4 pushed on scene.cutJoints vector
... success of Move_FourBar_noMacros.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal1Assembly.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_Signal4Assemblies.jl!
WARNING: replacing module test_massComputation.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of test_massComputation.jl!
... success of volume_computation3D_obj.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Move_Pendulum.jl!
initAnalysis!(world::Object3D, scene::Scene)
... success of Visualize_Beam.jl!
...test_Examples finished!
WARNING: replacing module TestExamples.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_Billiards_OneBall!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: BouncingBall1
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼────────┼─────────┼───────┼─────────┤
│ 1 │ h │ 0.2 │ 0 │ 0.2 │
│ 2 │ v │ 0.0 │ 0 │ 1.0 │
... h0 = 0.2
flying = true
-h = -0.2 (became <= 0)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.2019275108811498 s (z[1] > 0)
-h = 1.6181500583911657e-14 (became > 0)
... v = 1.3866362172208557
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.484626025952448 s (z[1] > 0)
-h = 2.71657696337968e-14 (became > 0)
... v = 0.9706453509400057
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.682514985967628 s (z[1] > 0)
-h = 1.3320941572025902e-14 (became > 0)
... v = 0.6794517427662368
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.8210372566626214 s (z[1] > 0)
-h = 6.938893903907228e-18 (became > 0)
... v = 0.47561621292614215
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9180028433604212 s (z[1] > 0)
-h = 2.3418766925686896e-17 (became > 0)
... v = 0.3329313347031544
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.9858787506124347 s (z[1] > 0)
-h = 3.80034545499619e-15 (became > 0)
... v = 0.23305186965963645
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 1.0 s
BouncingBall model is terminated (flying = true)
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.95 s (init: 0.74 s, integration: 0.21 s)
startTime = 0.0 s
stopTime = 1.0 s
interval = 0.02 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 63
nSteps = 125
nResidues = 345 (includes residue calls for Jacobian)
nZeroCrossings = 237
nJac = 110
nTimeEvents = 0
nStateEvents = 6
nRestartEvents = 6
nErrTestFails = 0
h0 = 7.2e-07 s
hMin = 7.2e-07 s
hMax = 0.27 s
orderMax = 3
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_BouncingBall.jl
... success of examples/collisions/Simulate_NewtonsCradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_SlidingAndRollingBall.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_TwoCollidingBalls.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: YouBot
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────────────────┼─────────┼───────┼─────────┤
│ 1 │ link1.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ link1.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ link2.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ link2.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 5 │ link3.rev.rev.phi │ 1.5708 │ 1 │ 1.5708 │
│ 6 │ link3.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 7 │ link4.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 8 │ link4.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 9 │ link5.rev.rev.phi │ 0.0 │ 1 │ 1.0 │
│ 10 │ link5.rev.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 11 │ gripper.prism.prism.s │ 0.0 │ 1 │ 1.0 │
│ 12 │ gripper.prism.controller.PI_x │ 0.0 │ 0 │ 1.0 │
│ 13 │ sphere.r[1] │ -0.125 │ 1 │ 1.0 │
│ 14 │ sphere.r[2] │ 0.0 │ 1 │ 1.0 │
│ 15 │ sphere.r[3] │ 0.03 │ 1 │ 1.0 │
│ 16 │ link1.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 17 │ link2.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 18 │ link3.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 19 │ link4.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 20 │ link5.rev.rev.w │ 0.0 │ 1 │ 1.0 │
│ 21 │ gripper.prism.prism.v │ 0.0 │ 1 │ 1.0 │
│ 22 │ sphere.v[1] │ 0.0 │ 1 │ 1.0 │
│ 23 │ sphere.v[2] │ 0.0 │ 1 │ 1.0 │
│ 24 │ sphere.v[3] │ 0.0 │ 1 │ 1.0 │
│ 25 │ sphere.q[1] │ 0.0 │ 0 │ 1.0 │
│ 26 │ sphere.q[2] │ 0.0 │ 0 │ 1.0 │
│ 27 │ sphere.q[3] │ 0.0 │ 0 │ 1.0 │
│ 28 │ sphere.q[4] │ 1.0 │ 0 │ 1.0 │
│ 29 │ sphere.w[1] │ 0.0 │ 1 │ 1.0 │
│ 30 │ sphere.w[2] │ 0.0 │ 1 │ 1.0 │
│ 31 │ sphere.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 7.261196339086959e-5 s (z[2] < 0)
distance(table.plate,sphere) = -2.0000000037447373e-8 became < 0
contact normal = [4.51e-08,6.28e-08,1], contact position = [0.585,-1.57e-09,0.375], c_res=1.24e+06, d_res=1e+03
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
State event (zero-crossing) at time = 0.417313819072049 s (z[2] < 0)
distance(sphere,gripper.gripper_right_finger) = -2.0000000393229984e-8 became < 0
contact normal = [-1,-0.00507,-2.05e-05], contact position = [0.56,-0.000127,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.4173142226300918 s (z[2] < 0)
distance(sphere,gripper.gripper_left_finger) = -2.0000006971107646e-8 became < 0
contact normal = [-1,0.00702,2.02e-05], contact position = [0.56,0.000175,0.4], c_res=1.24e+06, d_res=9.39
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.42197539326597844 s (z[1] > 0)
distance(sphere,gripper.gripper_left_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.421976224209762 s (z[1] > 0)
distance(sphere,gripper.gripper_right_finger) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 0.42 s
progress: integrated up to time = 0.64 s
progress: integrated up to time = 1.8 s
progress: integrated up to time = 2.1 s
progress: integrated up to time = 2.2 s
progress: integrated up to time = 2.3 s
progress: integrated up to time = 2.3 s
progress: integrated up to time = 2.4 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.5 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.6 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 2.7 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.4 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
progress: integrated up to time = 3.5 s
State event (zero-crossing) at time = 3.544805661448877 s (z[1] > 0)
distance(table.plate,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.772099387510426 s (z[2] < 0)
distance(ground,sphere) = -2.0000000104326316e-8 became < 0
contact normal = [-5.5e-07,-3e-06,1], contact position = [0.939,-0.000237,-3.46e-06], c_res=1.24e+06, d_res=0.32
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.787117001624274 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 3.8 s
State event (zero-crossing) at time = 4.125658766045461 s (z[2] < 0)
distance(ground,sphere) = -2.000011756920415e-8 became < 0
contact normal = [-5.51e-07,-3e-06,1], contact position = [1.03,-0.000263,-3.4e-06], c_res=1.24e+06, d_res=0.519
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.142357296028154 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.347238032219403 s (z[2] < 0)
distance(ground,sphere) = -2.0000000248254154e-8 became < 0
contact normal = [-5.52e-07,-3e-06,1], contact position = [1.09,-0.00028,-3.37e-06], c_res=1.24e+06, d_res=0.857
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.4 s
State event (zero-crossing) at time = 4.366036388703918 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.485371689085727 s (z[2] < 0)
distance(ground,sphere) = -2.000002838776016e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.13,-0.000291,-3.34e-06], c_res=1.24e+06, d_res=1.47
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.50711993227886 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.570603069658777 s (z[2] < 0)
distance(ground,sphere) = -2.000001311286435e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.15,-0.000298,-3.33e-06], c_res=1.24e+06, d_res=2.77
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.6 s
State event (zero-crossing) at time = 4.5979981506589205 s (z[1] > 0)
distance(ground,sphere) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.621567133614952 s (z[2] < 0)
distance(ground,sphere) = -2.000000589083613e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.17,-0.000302,-3.32e-06], c_res=1.24e+06, d_res=7.5
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 4.9 s
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 2.2e+02 s (init: 0.32 s, integration: 2.2e+02 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-5
nEquations = 31 (includes 1 constraints)
nResults = 5035
nSteps = 6038
nResidues = 144452 (includes residue calls for Jacobian)
nZeroCrossings = 11202
nJac = 4234
nTimeEvents = 0
nStateEvents = 17
nRestartEvents = 17
nErrTestFails = 1721
h0 = 1.8e-09 s
hMin = 1.8e-09 s
hMax = 0.053 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of examples/collisions/Simulate_YouBot.jl
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Collision_3Elements.jl!
... success of Test_Collision.jl!
... success of Test_Collision_moreRevolutes.jl!
... success of Test_Collision_StarSetting.jl!
... success of Test_MiniBsp.jl!
... success of Test_Solids.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_ContactBoxOnTable.jl!
WARNING: replacing module Simulate_YouBot.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_YouBotBoxOnTable.jl!
... success of collision_2_boxes.jl!
... success of collision_ballWithBall.jl!
... success of collision_ballWithBox.jl!
... success of collision_ballWithBox_45Deg.jl!
... success of collision_BallWithBox_Prismatic.jl!
WARNING: replacing module collision_ballWithBox_45Deg.
... success of collision_ballWithBox_45Deg.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: NewtonsCradle
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ -1.0472 │ 1 │ 1.0472 │
│ 2 │ rev2.phi │ -1.0472 │ 1 │ 1.0472 │
│ 3 │ rev3.phi │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev4.phi │ 1.0472 │ 1 │ 1.0472 │
│ 5 │ rev5.phi │ 1.0472 │ 1 │ 1.0472 │
│ 6 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 7 │ rev2.w │ 0.0 │ 1 │ 1.0 │
│ 8 │ rev3.w │ 0.0 │ 1 │ 1.0 │
│ 9 │ rev4.w │ 0.0 │ 1 │ 1.0 │
│ 10 │ rev5.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 1.0878031474718333 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000077594062304e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.11
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000077260995397e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.11
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0908094518650024 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0938480230542378 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000232248129635e-8 became < 0
contact normal = [0,1,-0.000784], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.0667
distance(pendulum5.sphere,pendulum4.sphere) = -2.000023202608503e-8 became < 0
contact normal = [0,-1,-0.000784], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.0667
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0958883290568509 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.0985275695684327 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000000211517488e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.169
distance(pendulum3.sphere,pendulum2.sphere) = -1.9999999101294463e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.169
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 1.1018053667261674 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1750114228447495 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9999989109287242e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.262
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000766629e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.262
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1785879880615164 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1930977548240014 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000009426368592e-8 became < 0
contact normal = [0,1,-0.00063], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.147
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000012757037666e-8 became < 0
contact normal = [0,-1,-0.00063], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.147
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.1954887018752087 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.2073414785973235 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.999992316203958e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.347
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.347
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 3.211125697316102 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.306987610498805 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000038292167233e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.537
distance(pendulum3.sphere,pendulum2.sphere) = -1.9998782851970986e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.537
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.311116540157841 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.3389794846640575 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -2.0000039291367955e-8 became < 0
contact normal = [0,1,-0.00065], contact position = [0,-1.52,-4], c_res=1.1e+11, d_res=0.336
distance(pendulum5.sphere,pendulum4.sphere) = -1.99989548255175e-8 became < 0
contact normal = [0,-1,-0.00065], contact position = [0,1.52,-4], c_res=1.1e+11, d_res=0.336
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.341800682588432 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.371038706105848 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -2.0000006983877938e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=0.886
distance(pendulum3.sphere,pendulum2.sphere) = -1.9988123378666955e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=0.886
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 5.375601280236619 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.586849755374663 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.9609640355966462e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.37
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000080924731378e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.37
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.591827089433919 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.623516942618943 s (z[2] < 0)
distance(pendulum1.sphere,pendulum2.sphere) = -1.96331674251482e-8 became < 0
contact normal = [0,1,-0.000809], contact position = [0,-1.51,-4], c_res=1.1e+11, d_res=0.73
distance(pendulum5.sphere,pendulum4.sphere) = -2.0000000100495186e-8 became < 0
contact normal = [0,-1,-0.000809], contact position = [0,1.51,-4], c_res=1.1e+11, d_res=0.73
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.626809172298678 s (z[1] > 0)
distance(pendulum1.sphere,pendulum2.sphere) became > 0
distance(pendulum5.sphere,pendulum4.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.651102476406292 s (z[2] < 0)
distance(pendulum4.sphere,pendulum3.sphere) = -1.694994378187431e-8 became < 0
contact normal = [0,-1,-0.000313], contact position = [0,0.5,-4], c_res=1.1e+11, d_res=1.68
distance(pendulum3.sphere,pendulum2.sphere) = -2.0000034739453554e-8 became < 0
contact normal = [0,-1,0.000313], contact position = [0,-0.5,-4], c_res=1.1e+11, d_res=1.68
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 7.656286321908144 s (z[1] > 0)
distance(pendulum4.sphere,pendulum3.sphere) became > 0
distance(pendulum3.sphere,pendulum2.sphere) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
progress: integrated up to time = 9 s
Simulation is terminated at time = 10.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 5.3 s (init: 0.007 s, integration: 5.3 s)
startTime = 0.0 s
stopTime = 10.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 10 (includes 0 constraints)
nResults = 10049
nSteps = 3394
nResidues = 11111 (includes residue calls for Jacobian)
nZeroCrossings = 13578
nJac = 644
nTimeEvents = 0
nStateEvents = 24
nRestartEvents = 24
nErrTestFails = 183
h0 = 3.7e-10 s
hMin = 3.7e-10 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... success of collision_newtons_cradle.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │ 1 │ [1.0, 0.0, 0.15] │
│ 2 │ x[4:6] │ boxMoving.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────┤
│ 1 │ x[1:3] │ boxMoving.r │
│ 2 │ x[4:6] │ boxMoving.v │
│ 3 │ x[7:10] │ boxMoving.q │
│ 4 │ x[11:13] │ boxMoving.w │
│ 5 │ derx[4:6] │ boxMoving.a │
│ 6 │ derx[7:10] │ boxMoving.derq │
│ 7 │ derx[11:13] │ boxMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.v │ residue[1:3] │
│ 2 │ boxMoving.residue_w │ residue[4:6] │
│ 3 │ boxMoving.residue_f │ residue[7:9] │
│ 4 │ boxMoving.residue_t │ residue[10:12] │
│ 5 │ boxMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.r │ result[2:4] │ [1.0, 0.0, 0.15] │
│ 3 │ boxMoving.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.r[1] │ 1.0 │ 1 │ 1.0 │
│ 2 │ boxMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ boxMoving.r[3] │ 0.15 │ 1 │ 1.0 │
│ 4 │ boxMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.58 s (init: 0.0045 s, integration: 0.58 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2001
nSteps = 22
nResidues = 282 (includes residue calls for Jacobian)
nZeroCrossings = 2022
nJac = 20
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 0
h0 = 1e-06 s
hMin = 1e-06 s
hMax = 0.95 s
orderMax = 2
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ -6.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 2.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ 4.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ -6.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 2.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ 4.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes_Prismatic.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼─────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ boxMoving.box.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ boxMoving.box.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ boxMoving.box.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ boxMoving.box.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ boxMoving.box.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ boxMoving.box.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ boxMoving.box.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ boxMoving.box.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ boxMoving.box.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ boxMoving.box.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ boxMoving.box.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼─────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │ 1 │ [0.3, 0.3, 0.4] │
│ 2 │ x[4:6] │ boxMoving.box.v │ 1 │ [0.0, 0.0, 0.0] │
│ 3 │ x[7:10] │ boxMoving.box.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ boxMoving.box.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼────────────────────┤
│ 1 │ x[1:3] │ boxMoving.box.r │
│ 2 │ x[4:6] │ boxMoving.box.v │
│ 3 │ x[7:10] │ boxMoving.box.q │
│ 4 │ x[11:13] │ boxMoving.box.w │
│ 5 │ derx[4:6] │ boxMoving.box.a │
│ 6 │ derx[7:10] │ boxMoving.box.derq │
│ 7 │ derx[11:13] │ boxMoving.box.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - boxMoving.box.v │ residue[1:3] │
│ 2 │ boxMoving.box.residue_w │ residue[4:6] │
│ 3 │ boxMoving.box.residue_f │ residue[7:9] │
│ 4 │ boxMoving.box.residue_t │ residue[10:12] │
│ 5 │ boxMoving.box.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼────────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ boxMoving.box.r │ result[2:4] │ [0.3, 0.3, 0.4] │
│ 3 │ boxMoving.box.v │ result[5:7] │ [0.0, 0.0, 0.0] │
│ 4 │ boxMoving.box.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ boxMoving.box.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ boxMoving.box.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ boxMoving.box.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ boxMoving.box.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼────────────────────┼─────────┼───────┼─────────┤
│ 1 │ boxMoving.box.r[1] │ 0.3 │ 1 │ 1.0 │
│ 2 │ boxMoving.box.r[2] │ 0.3 │ 1 │ 1.0 │
│ 3 │ boxMoving.box.r[3] │ 0.4 │ 1 │ 1.0 │
│ 4 │ boxMoving.box.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ boxMoving.box.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ boxMoving.box.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ boxMoving.box.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ boxMoving.box.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ boxMoving.box.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ boxMoving.box.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ boxMoving.box.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ boxMoving.box.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ boxMoving.box.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.24731005616100146 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000004734248907e-8 became < 0
contact normal = [-2.26e-06,-1.71e-06,1], contact position = [0.201,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball7) = -2.000004734248875e-8 became < 0
contact normal = [1.71e-06,-2.26e-06,1], contact position = [0.399,0.201,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball6) = -2.0000047342489175e-8 became < 0
contact normal = [-1.71e-06,2.26e-06,1], contact position = [0.201,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
distance(box,boxMoving.ball5) = -2.000004734248875e-8 became < 0
contact normal = [2.26e-06,1.71e-06,1], contact position = [0.399,0.399,-8.94e-07], c_res=6.55e+09, d_res=0.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.2481125660571883 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5331965901457278 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000053728345527e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball7) = -2.0000053624109652e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball6) = -2.000005195633312e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
distance(box,boxMoving.ball5) = -2.0000051852097245e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=0.763
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.5340932489465137 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6981642558349872 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.000002109193716e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball7) = -1.999937767744656e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball6) = -1.999991893897259e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
distance(box,boxMoving.ball5) = -1.999927552411946e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=1.33
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6991670990157088 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7933203793651138 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.9931744958305092e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball7) = -1.9990694560827858e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball6) = -1.994106593038438e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
distance(box,boxMoving.ball5) = -2.0000015532540382e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=2.31
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.7944441644217183 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8481668040359734 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000002958918e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball7) = -1.7374601686311956e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball6) = -1.958497377417097e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
distance(box,boxMoving.ball5) = -1.69595754552709e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=4.05
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.849431030287405 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball6) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797326988491254 s (z[2] < 0)
distance(box,boxMoving.ball7) = -1.1392672904124347e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball5) = -2.0000000041587432e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8797328451973824 s (z[2] < 0)
distance(box,boxMoving.ball8) = -1.1392636220617333e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.3e-07], c_res=6.55e+09, d_res=7.18
distance(box,boxMoving.ball6) = -2.000000362194742e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=7.18
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811664389977623 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8811666117163817 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978452972372389 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000029646597e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978456759745383 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000002716729238e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978476432172747 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000002047353616e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8978480219461057 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000002620679725e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=13
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995008133684923 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995012373267285 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.8995034443000441 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.899503869685549 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081689816942726 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.000000001049624e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081713339213505 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000016912727e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=25.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.908183562872571 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.000000105050595e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9081859133992267 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000001066602754e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=25
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101766591463938 s (z[1] > 0)
distance(box,boxMoving.ball5) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101791167805899 s (z[1] > 0)
distance(box,boxMoving.ball7) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101920196719218 s (z[1] > 0)
distance(box,boxMoving.ball6) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9101945102341994 s (z[1] > 0)
distance(box,boxMoving.ball8) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139672883052976 s (z[2] < 0)
distance(box,boxMoving.ball8) = -2.0000000483431793e-8 became < 0
contact normal = [-2.24e-06,-4.19e-07,1], contact position = [0.201,0.201,-8.29e-07], c_res=6.55e+09, d_res=57.7
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139713502815872 s (z[2] < 0)
distance(box,boxMoving.ball6) = -2.0000000023380247e-8 became < 0
contact normal = [-4.19e-07,2.24e-06,1], contact position = [0.201,0.399,-8.29e-07], c_res=6.55e+09, d_res=57.6
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139925997600851 s (z[2] < 0)
distance(box,boxMoving.ball7) = -2.0000000467229747e-8 became < 0
contact normal = [4.19e-07,-2.24e-06,1], contact position = [0.399,0.201,-8.29e-07], c_res=6.55e+09, d_res=57
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.9139966276478274 s (z[2] < 0)
distance(box,boxMoving.ball5) = -2.0000000467456328e-8 became < 0
contact normal = [2.24e-06,4.19e-07,1], contact position = [0.399,0.399,-8.29e-07], c_res=6.55e+09, d_res=56.9
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
progress: integrated up to time = 1.1 s
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 5.7 s (init: 0.005 s, integration: 5.7 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 2069
nSteps = 3016
nResidues = 14021 (includes residue calls for Jacobian)
nZeroCrossings = 5291
nJac = 746
nTimeEvents = 0
nStateEvents = 34
nRestartEvents = 34
nErrTestFails = 136
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 0.52 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_2_boxes2.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: ThreeDFiles
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├────┼───────────────────┼─────────┼───────┼─────────┤
│ 1 │ sphereMoving.r[1] │ 0.0 │ 1 │ 1.0 │
│ 2 │ sphereMoving.r[2] │ 0.0 │ 1 │ 1.0 │
│ 3 │ sphereMoving.r[3] │ 0.0 │ 1 │ 1.0 │
│ 4 │ sphereMoving.v[1] │ 0.0 │ 1 │ 1.0 │
│ 5 │ sphereMoving.v[2] │ 0.0 │ 1 │ 1.0 │
│ 6 │ sphereMoving.v[3] │ 0.0 │ 1 │ 1.0 │
│ 7 │ sphereMoving.q[1] │ 0.0 │ 0 │ 1.0 │
│ 8 │ sphereMoving.q[2] │ 0.0 │ 0 │ 1.0 │
│ 9 │ sphereMoving.q[3] │ 0.0 │ 0 │ 1.0 │
│ 10 │ sphereMoving.q[4] │ 1.0 │ 0 │ 1.0 │
│ 11 │ sphereMoving.w[1] │ 0.0 │ 1 │ 1.0 │
│ 12 │ sphereMoving.w[2] │ 0.0 │ 1 │ 1.0 │
│ 13 │ sphereMoving.w[3] │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
State event (zero-crossing) at time = 0.6772856461815322 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000103221454e-8 became < 0
contact normal = [1,3.29e-07,6.38e-08], contact position = [-2.5,-8.23e-08,-1.59e-08], c_res=1.1e+11, d_res=0.103
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 0.6805673217281598 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.604523859549157 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000042421506716e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.31e-06,2.28e-07], c_res=1.1e+11, d_res=0.151
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 1.608067986620904 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.2377170487446953 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000021744128692e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,1.86e-06,5.39e-07], c_res=1.1e+11, d_res=0.222
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.241547117509829 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.670000719849833 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000017185844653e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.13e-06,6.87e-07], c_res=1.1e+11, d_res=0.326
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.6741432074212255 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.9650010850231467 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000052294577e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.26e-06,7.61e-07], c_res=1.1e+11, d_res=0.481
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 2.969487415670937 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.1661841009957588 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000007723373e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.33e-06,8.01e-07], c_res=1.1e+11, d_res=0.711
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.171053307859464 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3032414214915753 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000010420225165e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.37e-06,8.24e-07], c_res=1.1e+11, d_res=1.06
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3085451316993217 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.3964536389386515 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000003210248078e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.39e-06,8.39e-07], c_res=1.1e+11, d_res=1.59
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.40226611806008 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.4596684178013386 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000182727477e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.41e-06,8.48e-07], c_res=1.1e+11, d_res=2.44
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.466109471122685 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5023347462234047 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000017570597e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.42e-06,8.54e-07], c_res=1.1e+11, d_res=3.86
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5096330034147374 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5308804788237578 s (z[2] < 0)
distance(box,sphereMoving) = -2.0000000119224454e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.58e-07], c_res=1.1e+11, d_res=6.58
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.539639348752486 s (z[1] > 0)
distance(box,sphereMoving) became > 0
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 3.5495862810383714 s (z[2] < 0)
distance(box,sphereMoving) = -2.000000035617481e-8 became < 0
contact normal = [1,2.82e-07,1.59e-07], contact position = [-2.5,2.43e-06,8.6e-07], c_res=1.1e+11, d_res=14.1
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
Simulation is terminated at time = 6.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 3.7 s (init: 0.0055 s, integration: 3.7 s)
startTime = 0.0 s
stopTime = 6.0 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 13 (includes 1 constraints)
nResults = 6047
nSteps = 3785
nResidues = 14026 (includes residue calls for Jacobian)
nZeroCrossings = 9998
nJac = 653
nTimeEvents = 0
nStateEvents = 23
nRestartEvents = 23
nErrTestFails = 122
h0 = 1.8e-10 s
hMin = 1.8e-10 s
hMax = 1.1 s
orderMax = 5
sparseSolver = false
... success of contactForceLaw_Ball.jl!
... success of contactForceLaw_ballWithBall.jl!
variables: . Omitted printing of 12 columns
│ Row │ name │ ValueType │ unit │
│ │ Symbol │ Symbol │ String │
├─────┼────────────────────────┼──────────────────────────────┼─────────┤
│ 1 │ time │ Float64 │ s │
│ 2 │ sphereMoving.r │ SArray{Tuple{3},Float64,1,3} │ m │
│ 3 │ sphereMoving.v │ SArray{Tuple{3},Float64,1,3} │ m/s │
│ 4 │ sphereMoving.a │ SArray{Tuple{3},Float64,1,3} │ m/s^2 │
│ 5 │ sphereMoving.q │ SArray{Tuple{4},Float64,1,4} │ │
│ 6 │ sphereMoving.derq │ SArray{Tuple{4},Float64,1,4} │ 1/s │
│ 7 │ sphereMoving.w │ SArray{Tuple{3},Float64,1,3} │ rad/s │
│ 8 │ sphereMoving.z │ SArray{Tuple{3},Float64,1,3} │ rad/s^2 │
│ 9 │ sphereMoving.residue_w │ SArray{Tuple{3},Float64,1,3} │ │
│ 10 │ sphereMoving.residue_f │ SArray{Tuple{3},Float64,1,3} │ │
│ 11 │ sphereMoving.residue_t │ SArray{Tuple{3},Float64,1,3} │ │
│ 12 │ sphereMoving.residue_q │ Float64 │ │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼──────────┼────────────────┼───────┼──────────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │ 1 │ [0.0, 0.0, 0.0] │
│ 2 │ x[4:6] │ sphereMoving.v │ 1 │ [2.0, 0.0, -3.0] │
│ 3 │ x[7:10] │ sphereMoving.q │ 0 │ [0.0, 0.0, 0.0, 1.0] │
│ 4 │ x[11:13] │ sphereMoving.w │ 1 │ [0.0, 0.0, 0.0] │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────────┼───────────────────┤
│ 1 │ x[1:3] │ sphereMoving.r │
│ 2 │ x[4:6] │ sphereMoving.v │
│ 3 │ x[7:10] │ sphereMoving.q │
│ 4 │ x[11:13] │ sphereMoving.w │
│ 5 │ derx[4:6] │ sphereMoving.a │
│ 6 │ derx[7:10] │ sphereMoving.derq │
│ 7 │ derx[11:13] │ sphereMoving.z │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼────────────────────────────┼────────────────┤
│ 1 │ derx[1:3] - sphereMoving.v │ residue[1:3] │
│ 2 │ sphereMoving.residue_w │ residue[4:6] │
│ 3 │ sphereMoving.residue_f │ residue[7:9] │
│ 4 │ sphereMoving.residue_t │ residue[10:12] │
│ 5 │ sphereMoving.residue_q │ residue[13] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼───────────────────┼───────────────┼──────────────────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ sphereMoving.r │ result[2:4] │ [0.0, 0.0, 0.0] │
│ 3 │ sphereMoving.v │ result[5:7] │ [2.0, 0.0, -3.0] │
│ 4 │ sphereMoving.a │ result[8:10] │ [0.0, 0.0, 0.0] │
│ 5 │ sphereMoving.q │ result[11:14] │ [0.0, 0.0, 0.0, 1.0] │
│ 6 │ sphereMoving.derq │ result[15:18] │ [0.0, 0.0, 0.0, 0.0] │
│ 7 │ sphereMoving.w │ result[19:21] │ [0.0, 0.0, 0.0] │
│ 8 │ sphereMoving.z │ result[22:24] │ [0.0, 0.0, 0.0] │
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_45Deg.jl!
variables: . Omitted printing of 9 columns
│ Row │ name │ ValueType │ unit │ numericType │ vec │ vecIndex │
│ │ Symbol │ Symbol │ String │ ModiaMat… │ Symbol │ Any │
├─────┼───────────────┼───────────┼────────┼─────────────┼─────────┼──────────┤
│ 1 │ time │ Float64 │ s │ TIME │ │ 0 │
│ 2 │ prisX.s │ Float64 │ m │ XD_EXP │ x │ 1 │
│ 3 │ prisX.v │ Float64 │ m/s │ XD_IMP │ x │ 4 │
│ 4 │ prisX.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 4 │
│ 5 │ prisX.f │ Float64 │ N │ WR │ │ 0 │
│ 6 │ prisX.residue │ Float64 │ │ FD_IMP │ residue │ 4 │
│ 7 │ prisX.P │ Float64 │ J │ WC │ │ 0 │
⋮
│ 12 │ prisY.residue │ Float64 │ │ FD_IMP │ residue │ 5 │
│ 13 │ prisY.P │ Float64 │ J │ WC │ │ 0 │
│ 14 │ prisZ.s │ Float64 │ m │ XD_EXP │ x │ 3 │
│ 15 │ prisZ.v │ Float64 │ m/s │ XD_IMP │ x │ 6 │
│ 16 │ prisZ.a │ Float64 │ m/s^2 │ DER_XD_IMP │ derx │ 6 │
│ 17 │ prisZ.f │ Float64 │ N │ WR │ │ 0 │
│ 18 │ prisZ.residue │ Float64 │ │ FD_IMP │ residue │ 6 │
│ 19 │ prisZ.P │ Float64 │ J │ WC │ │ 0 │
x vector:
│ Row │ x │ name │ fixed │ start │
│ │ Symbol │ Symbol │ Bool │ Union… │
├─────┼────────┼─────────┼───────┼────────┤
│ 1 │ x[1] │ prisX.s │ 1 │ 0.0 │
│ 2 │ x[2] │ prisY.s │ 1 │ 0.0 │
│ 3 │ x[3] │ prisZ.s │ 1 │ 0.0 │
│ 4 │ x[4] │ prisX.v │ 1 │ 2.0 │
│ 5 │ x[5] │ prisY.v │ 1 │ 0.0 │
│ 6 │ x[6] │ prisZ.v │ 1 │ -3.0 │
copy to variables:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼─────────┼─────────┤
│ 1 │ x[1] │ prisX.s │
│ 2 │ x[2] │ prisY.s │
│ 3 │ x[3] │ prisZ.s │
│ 4 │ x[4] │ prisX.v │
│ 5 │ x[5] │ prisY.v │
│ 6 │ x[6] │ prisZ.v │
│ 7 │ derx[4] │ prisX.a │
│ 8 │ derx[5] │ prisY.a │
│ 9 │ derx[6] │ prisZ.a │
copy to residue vector:
│ Row │ source │ target │
│ │ Symbol │ Symbol │
├─────┼───────────────────┼────────────┤
│ 1 │ derx[1] - prisX.v │ residue[1] │
│ 2 │ derx[2] - prisY.v │ residue[2] │
│ 3 │ derx[3] - prisZ.v │ residue[3] │
│ 4 │ prisX.residue │ residue[4] │
│ 5 │ prisY.residue │ residue[5] │
│ 6 │ prisZ.residue │ residue[6] │
copy to results:
│ Row │ source │ target │ start │
│ │ Symbol │ Symbol │ Union… │
├─────┼─────────┼────────────┼────────┤
│ 1 │ time │ result[1] │ 0.0 │
│ 2 │ prisX.s │ result[2] │ 0.0 │
│ 3 │ prisX.v │ result[3] │ 2.0 │
│ 4 │ prisX.a │ result[4] │ 0.0 │
│ 5 │ prisX.f │ result[5] │ 0.0 │
│ 6 │ prisX.P │ result[6] │ 0.0 │
│ 7 │ prisY.s │ result[7] │ 0.0 │
│ 8 │ prisY.v │ result[8] │ 0.0 │
│ 9 │ prisY.a │ result[9] │ 0.0 │
│ 10 │ prisY.f │ result[10] │ 0.0 │
│ 11 │ prisY.P │ result[11] │ 0.0 │
│ 12 │ prisZ.s │ result[12] │ 0.0 │
│ 13 │ prisZ.v │ result[13] │ -3.0 │
│ 14 │ prisZ.a │ result[14] │ 0.0 │
│ 15 │ prisZ.f │ result[15] │ 0.0 │
│ 16 │ prisZ.P │ result[16] │ 0.0 │
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: TwoBoxes
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ prisX.s │ 0.0 │ 1 │ 1.0 │
│ 2 │ prisY.s │ 0.0 │ 1 │ 1.0 │
│ 3 │ prisZ.s │ 0.0 │ 1 │ 1.0 │
│ 4 │ prisX.v │ 2.0 │ 1 │ 2.0 │
│ 5 │ prisY.v │ 0.0 │ 1 │ 1.0 │
│ 6 │ prisZ.v │ -3.0 │ 1 │ 3.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
State event (zero-crossing) at time = 0.43731521721763345 s (z[2] < 0)
distance(box,boxMoving) = -2.0000005749098553e-8 became < 0
contact normal = [1.72e-08,-7.57e-08,1], contact position = [0.875,1.89e-08,-2.5], c_res=1.1e+11, d_res=0.0941
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
State event (zero-crossing) at time = 0.4425862085910631 s (z[1] > 0)
distance(box,boxMoving) became > 0
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
restart = Restart
Simulation is terminated at time = 0.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.43 s (init: 0.0016 s, integration: 0.43 s)
startTime = 0.0 s
stopTime = 0.5 s
interval = 0.001 s
tolerance = 1.0e-8
nEquations = 6 (includes 0 constraints)
nResults = 505
nSteps = 461
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 982
nJac = 96
nTimeEvents = 0
nStateEvents = 2
nRestartEvents = 2
nErrTestFails = 15
h0 = 3.4e-10 s
hMin = 3.4e-10 s
hMax = 0.18 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of contactForceLaw_ballWithBox_Prismatic.jl!
... success of contactForceLaw_newtons_cradle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion1_directHit.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of BillardBall1_Cushion4_arbitraryHit.jl!
...test_Examples_Collision finished!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: DoublePendulumWithDampers
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────┼─────────┼───────┼─────────┤
│ 1 │ rev1.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev2.phi │ 0.0 │ 1 │ 1.0 │
│ 3 │ rev1.w │ 0.0 │ 1 │ 1.0 │
│ 4 │ rev2.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.37 s (init: 0.013 s, integration: 0.35 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.001 s
tolerance = 1.0e-6
nEquations = 4 (includes 0 constraints)
nResults = 5001
nSteps = 837
nResidues = 1322 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 56
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 20
h0 = 2.3e-09 s
hMin = 2.3e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_DoublePendulumWithDampers.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_FallingBall1.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 4.5 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.082 s (init: 0.0017 s, integration: 0.08 s)
startTime = 0.0 s
stopTime = 4.5 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2251
nSteps = 272
nResidues = 339 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 26
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 2
h0 = 5.8e-09 s
hMin = 5.8e-09 s
hMax = 0.021 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Pendulum
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────┼─────────┼───────┼─────────┤
│ 1 │ revolute.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ revolute.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.092 s (init: 0.0014 s, integration: 0.091 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 1.0e-6
nEquations = 2 (includes 0 constraints)
nResults = 2501
nSteps = 262
nResidues = 370 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 1
h0 = 8.3e-09 s
hMin = 8.3e-09 s
hMax = 0.046 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
WARNING: replacing module Simulate_Pendulum.
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_Pendulum.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithController
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ c.PI_x │ 0.0 │ 0 │ 1.0 │
│ 3 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.17 s (init: 0.035 s, integration: 0.13 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 3 (includes 0 constraints)
nResults = 2501
nSteps = 376
nResidues = 568 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 25
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 7.1e-07 s
hMin = 7.1e-07 s
hMax = 0.044 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithController.jl!
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: PendulumWithDamper
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼─────────┼─────────┼───────┼─────────┤
│ 1 │ rev.phi │ 0.0 │ 1 │ 1.0 │
│ 2 │ rev.w │ 0.0 │ 1 │ 1.0 │
for given x, determine consistent DAE variables der(x) (solving a linear equation system)
Simulation started
Simulation is terminated at time = 5.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.021 s (init: 0.011 s, integration: 0.0098 s)
startTime = 0.0 s
stopTime = 5.0 s
interval = 0.1 s
tolerance = 0.0001
nEquations = 2 (includes 0 constraints)
nResults = 51
nSteps = 136
nResidues = 230 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 7
h0 = 5.8e-07 s
hMin = 5.8e-07 s
hMax = 0.085 s
orderMax = 5
sparseSolver = false
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Simulate_PendulumWithDamper.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Move_DoublePendulum.jl!
... Revolute joint connecting Fourbar.bar3.frame2 with Fourbar.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... success of Move_FourBar.jl!
... Revolute joint connecting Fourbar2.bar3.frame2 with Fourbar2.bar2.frame2 is a cut-joint
... Cut-joint fourbar.rev4 pushed on scene.cutJoints vector
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: Move2
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼──────────────────┼─────────┼───────┼─────────┤
│ 1 │ fourbar.rev2.phi │ -1.5708 │ 1 │ 1.5708 │
│ 2 │ fourbar.rev3.phi │ 1.10715 │ 1 │ 1.10715 │
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
Simulation started
Simulation is terminated at time = 3.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 0.072 s (init: 0.014 s, integration: 0.058 s)
startTime = 0.0 s
stopTime = 3.0 s
interval = 0.002 s
tolerance = 0.0001
nEquations = 2 (includes 2 constraints)
nResults = 1501
nSteps = 112
nResidues = 219 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 19
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 4
h0 = 2e-06 s
hMin = 2e-06 s
hMax = 0.056 s
orderMax = 5
sparseSolver = false
... success of Move_FourBar2.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalAngle.jl!
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
... success of Test_SignalTorque.jl!
... success of Move_AllVisualObjects.jl!
... success of Move_SolidFileMesh.jl!
... success of Visualize_AllVisualObjects.jl!
... success of Visualize_Assembly.jl!
... success of Visualize_GeometriesWithMaterial.jl!
... success of Visualize_GeometriesWithoutMaterial.jl!
... success of Visualize_SolidFileMesh.jl!
... success of Visualize_Solids.jl!
... success of Visualize_Text.jl!
... success of Visualize_TextFonts.jl!
... success of runexamples.jl
... success of all tests!
Test Summary: | Pass Total
Test Modia3D | 57 57
Testing Modia3D tests passed