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1.5.0-DEV-e0740fe5a6.log
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1.5.0-DEV-e0740fe5a6.log
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Julia Version 1.5.0-DEV.147
Commit e0740fe5a6 (2020-01-24 14:13 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
JULIA_NUM_THREADS = 2
Resolving package versions...
Installed Requires ──────────────────── v1.0.0
Installed PooledArrays ──────────────── v0.5.3
Installed ChainRulesCore ────────────── v0.5.5
Installed TableTraits ───────────────── v1.0.0
Installed Unitful ───────────────────── v0.18.0
Installed MuladdMacro ───────────────── v0.2.2
Installed Sundials ──────────────────── v3.8.1
Installed RecipesBase ───────────────── v0.7.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed Missings ──────────────────── v0.4.3
Installed Compat ────────────────────── v2.2.0
Installed OrderedCollections ────────── v1.1.0
Installed ArrayInterface ────────────── v2.3.1
Installed IterativeSolvers ──────────── v0.8.1
Installed Tables ────────────────────── v0.2.11
Installed InvertedIndices ───────────── v1.0.0
Installed JSON ──────────────────────── v0.21.0
Installed DiffEqBase ────────────────── v6.13.0
Installed RecursiveArrayTools ───────── v2.0.4
Installed Reexport ──────────────────── v0.2.0
Installed Roots ─────────────────────── v0.8.4
Installed DocStringExtensions ───────── v0.8.1
Installed MacroTools ────────────────── v0.5.3
Installed DataStructures ────────────── v0.17.9
Installed DataAPI ───────────────────── v1.1.0
Installed DataValueInterfaces ───────── v1.0.0
Installed FunctionWrappers ──────────── v1.0.0
Installed StaticArrays ──────────────── v0.12.1
Installed BinaryProvider ────────────── v0.5.8
Installed CategoricalArrays ─────────── v0.7.7
Installed Parsers ───────────────────── v0.3.10
Installed ConstructionBase ──────────── v1.0.0
Installed SortingAlgorithms ─────────── v0.3.1
Installed ZygoteRules ───────────────── v0.2.0
Installed TreeViews ─────────────────── v0.3.0
Installed Parameters ────────────────── v0.12.0
Installed RecursiveFactorization ────── v0.1.0
Installed ModiaMath ─────────────────── v0.5.2
Installed DataFrames ────────────────── v0.20.0
Installed Modia3D ───────────────────── v0.4.0
Updating `~/.julia/environments/v1.5/Project.toml`
[07f2c1e0] + Modia3D v0.4.0
Updating `~/.julia/environments/v1.5/Manifest.toml`
[4fba245c] + ArrayInterface v2.3.1
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.7
[d360d2e6] + ChainRulesCore v0.5.5
[34da2185] + Compat v2.2.0
[187b0558] + ConstructionBase v1.0.0
[9a962f9c] + DataAPI v1.1.0
[a93c6f00] + DataFrames v0.20.0
[864edb3b] + DataStructures v0.17.9
[e2d170a0] + DataValueInterfaces v1.0.0
[2b5f629d] + DiffEqBase v6.13.0
[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 v0.5.3
[e1d29d7a] + Missings v0.4.3
[07f2c1e0] + Modia3D v0.4.0
[67ccffd1] + ModiaMath v0.5.2
[46d2c3a1] + MuladdMacro v0.2.2
[bac558e1] + OrderedCollections v1.1.0
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.10
[2dfb63ee] + PooledArrays v0.5.3
[3cdcf5f2] + RecipesBase v0.7.0
[731186ca] + RecursiveArrayTools v2.0.4
[f2c3362d] + RecursiveFactorization v0.1.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v1.0.0
[f2b01f46] + Roots v0.8.4
[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
[700de1a5] + ZygoteRules v0.2.0
[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`
Updating `/tmp/jl_25aJXm/Project.toml`
[no changes]
Updating `/tmp/jl_25aJXm/Manifest.toml`
[no changes]
Testing Modia3D
Updating `/tmp/jl_PJK9h7/Project.toml`
[no changes]
Updating `/tmp/jl_PJK9h7/Manifest.toml`
[no changes]
Running sandbox
Status `/tmp/jl_PJK9h7/Project.toml`
[a93c6f00] DataFrames v0.20.0
[864edb3b] DataStructures v0.17.9
[682c06a0] JSON v0.21.0
[07f2c1e0] Modia3D v0.4.0
[67ccffd1] ModiaMath v0.5.2
[90137ffa] StaticArrays v0.12.1
[1986cc42] Unitful v0.18.0
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[de0858da] Printf
[8dfed614] Test
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 = 8 s (init: 6.9 s, integration: 1.2 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 = 0.077 s (init: 0.00087 s, integration: 0.076 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 = 0.9 s (init: 0.75 s, integration: 0.16 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) = -2.000000003744737e-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 = 0.4173138190720484 s (z[2] < 0)
distance(sphere,gripper.gripper_right_finger) = -2.0000000031077077e-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 = 0.4173142226300906 s (z[2] < 0)
distance(sphere,gripper.gripper_left_finger) = -2.0000005203813682e-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 = 0.421975283679707 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 = 0.42197611448867994 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 = 0.82 s
progress: integrated up to time = 1.8 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 = 2.3 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 = 3.4 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 = 3.544617622188206 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 = 3.772200055689489 s (z[2] < 0)
distance(ground,sphere) = -2.0000000125895976e-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 = 3.7872166075457345 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 s
State event (zero-crossing) at time = 4.1257567277726865 s (z[2] < 0)
distance(ground,sphere) = -2.000007642161648e-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 = 4.1424548393819105 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 = 4.347262213017979 s (z[2] < 0)
distance(ground,sphere) = -2.000000016462577e-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=0.858
determine consistent DAE variables x,der(x) (with analytical integral over time instant)
restart = Restart
State event (zero-crossing) at time = 4.36606207058098 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 = 4.4 s
State event (zero-crossing) at time = 4.485362669299116 s (z[2] < 0)
distance(ground,sphere) = -2.0000000202700083e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.13,-0.00029,-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 = 4.507110210077004 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 = 4.57059029797964 s (z[2] < 0)
distance(ground,sphere) = -2.0000014307970196e-8 became < 0
contact normal = [-5.53e-07,-2.99e-06,1], contact position = [1.15,-0.000297,-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 = 4.597984915155498 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 = 4.621542207497235 s (z[2] < 0)
distance(ground,sphere) = -2.000000008959269e-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=7.51
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 = 2.4e+02 s (init: 0.22 s, integration: 2.4e+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 = 6101
nResidues = 146739 (includes residue calls for Jacobian)
nZeroCrossings = 11263
nJac = 4306
nTimeEvents = 0
nStateEvents = 17
nRestartEvents = 17
nErrTestFails = 1741
h0 = 9e-09 s
hMin = 9e-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 = 9.4 s
Simulation is terminated at time = 10.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_LinearDerivativesAndConstraints
cpuTime = 5.2 s (init: 0.0033 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 = 0.47 s (init: 0.004 s, integration: 0.47 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] │