The investigations described here are related to the unstable behavior of crash-results due to minor changes in the model. As an outcome the received crash-results become in some way unpredictable and the causes can be various, e.g. modeling failure, contact issues, numerical instabilities, physical instabilities, etc. To identify and separate these scatter sources the results are analyzed by means of visualizing the standard deviation of scatter itself and computing scatter modes for selected parts of interest. These computations are based on the principle component analysis (PCA), a dimension reduction technique. Afterwards, new virtual crash results representing the most extreme values of these modes are computed and help identifying the original reasons which cause the scatter. Then correction can be applied resulting in substantial reduction of the original scatter.

1. Identification of scatter sources and significant
reduction of scatter occurrence with
DIFFCRASH
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Marian Bulla (Altair Germany) Dominik Borsotto (Fraunhofer SCAI)
Clemens A. Thole (Fraunhofer SCAI)
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2. Agenda
 Introduction
 Reasons for scatter
 Analysis methods
 Basic analysis methods
 Correlation based methods
 PCA based methods
 Example Case
 Analysis of a Chrysler NEON model (RADIOSS)
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3. Introduction: Reasons for scatter
 Potential scatter of simulation results is still a challenging issue
 For the design and optimization of car models it is very helpful to deal
with a simulation model, which generates similar results even if slight
changes of the model are performed.
 Keyword: Predictability
 Reasons for scatter are various.
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4. Introduction: Reasons for scatter due to
physics
Reasons
Contact / no contact 90° contact buckling
Element failures friction
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5. Analysis methods: Stability analysis with
DIFFCRASH
 Postprocessing tool: Identification and separation of multiple sources of
scatter: location and time
 Statistical Analysis of full simulation models
 Basic analysis methods
 Correlation based methods
 PCA based methods
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5

6. Analysis methods: Basic analysis
methods
 Functionals (per Node):
 PD3MX (max. scatter in 3D)
 PD3AV (avg. scatter in 3D)
 PDXMX (max. scatter in X-direction)
 PDYMX (max. scatter in Y-direction)
 PDZMX (max. scatter in Z-direction)
 PD3IJ (Simulation runs with max. distance)
 Relies on different positions of the same node in multiple simulations
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7. Analysis methods: Scatter visualization
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8. Analysis methods: Correlation based methods
 Correlation analysis
 Find strong correlation in data -> causal chains (backtracking of
instabilities)
 Elimination of a detected source from the set of results
(Orthogonal projection)
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9. Analysis methods: PCA based methods
 Data Reduction for simulation results: 20 – 200 runs
 Parameter changes (Material properties, thicknesses, barrier loc.)
 2.000.000 nodes/elements
 150 states (time steps in the results)
 Dimension: 1 Billion 200 Billion values
 PCA Analysis
 Small number of modes representing the results
 Find the dominating components in the result data, which have the
strongest impact on the simulation results
 Subspace comparison to identify buckling
 Modes consist of a linear combination of all simulation runs
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10. Analysis methods: PCA based methods
 Global PCA
 Computation of scatter modes for the whole model
 Visualization as an virtual computed simulation result
 Local PCA
 Computation of scatter modes for single parts or groups of parts out
of the model
 Difference PCA
 Different origins of scatter can be identified and physically meaningful
components can be determined
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11. Analysis methods:
Principle Component Analysis (PCA)
 Covariance Matrix: A Xi X0, X j X0 i, j
2
 Eigenvalues/Eigenvectors of the Covariance matrix: ,
i i
i Vectors in the space of coefficients
i L2 Norm of X0 X( i)
Number of i determines the upper bound of the essential size of the
solution space
λi (Importance measures)
50
0.25
40
0.2
30
0.15
20 0.1
10 0.05
0 0
1 11 21 31 41 51 61 71 81 91 0 20 40 60 80 100
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12. Example of the two most important modes
for the Ford Taurus
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13. Example case: Chrysler Neon
Frontal Impact on Rigid wall
Model Unit: mm, s, Ton
Initial Velocity: 12.3 m/s
Total Mass : 1.219 Ton
Random Noise: 1.0 E-6 mm
Seed variation (0.00 to 0.9)
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14. T = 00.00 ms T = 80.00 ms
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15. Target area
T = 00.00 ms T = 80.00 ms
Overall intrusion in dashboard
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16. Scatter propagation
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17. Scatter propagation
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18. Scatter propagation
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19. Scatter propagation
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20. Scatter propagation
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21. Scatter propagation
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22. Scatter propagation
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23. Scatter propagation
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24. Scatter propagation
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25. Scatter propagation
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26. Scatter propagation
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27. Scatter propagation
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28. Scatter propagation
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29. Scatter propagation
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30. Scatter propagation
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31. Scatter propagation
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32. Scatter propagation
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33. Scatter propagation
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34. Scatter propagation
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35. Scatter propagation
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36. Scatter propagation
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37. What is the Source (in time and space) of
this results Dispersion ?
MDSplot
Points represent simulation results
X-Axis: Contribution of most important mode
Y-Axis: Contribution of 2nd important mode.
virtual derived simulationresultsd to
visualize the dominating effect.
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38. What is the Source (in time and space) of
this result dispersion ?
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39. What is the Source (in time and space) of
this result Dispersion ?
Sub frame does NOT hit
Sub frame hits Engine at ~ 40 ms
Engine at ~ 40 ms
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40. What is the Source (in time and space) of
this result Dispersion ?
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41. What is the Source (in time and space) of
this result Dispersion ?
Blue: Original scatter modes
Green: Without scatter of
engine/Subframe
“Switching OFF” this scatter source (analytically in DiffCrash) indicates
a significant reduction of displacement scatter in Dashboard area.
 Issue area has to be analyzed further, by local
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investigation e.g. with the help of MultiDomain .

42. Summary
 DIFFCRASH allows us to identify and quantify major sources of scatter
 The methods allow to devise design and modeling suggestions to reduce
scatter of simulation results
 Next steps e.g.:
 Applying the multidomain - technique to get a modeling of the critical
region in more detail.
 Geometrical changes can force a deterministic behavior in a next
step.
 First results of an adapted Chrysler NEON model look very promising
regarding the reduction of scatter at the front wall
 OUTLOOK:
 Postprocessor interface for GNS Animator (1st prototype ) and
others.
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43. Thank you very much for your attention...!
Innovation Intelligence®
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