Identification of Scatter Sources and Significant Reduction of Scatter Occurrence with DIFFCRASH

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Identification of scatter sources and significant

reduction of scatter occurrence with

DIFFCRASH

Marian Bulla (Altair Germany) Dominik Borsotto (Fraunhofer SCAI)

Clemens A. Thole (Fraunhofer SCAI)

Innovation Intelligence®

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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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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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Introduction: Reasons for scatter due to

physics

Reasons

Contact / no contact 90° contact buckling

Element failures friction

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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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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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Analysis methods: Scatter visualization

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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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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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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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Analysis methods:

Principle Component Analysis (PCA)

Covariance Matrix:

Eigenvalues/Eigenvectors of the Covariance matrix:

Vectors in the space of coefficients

L2 Norm of

Number of determines the upper bound of the essential size of the

solution space

jiji XXXXA,00 ,

ii ,2

i )(0 iXX

i

i

0

10

20

30

40

50

1 11 21 31 41 51 61 71 81 91

λi (Importance measures)

0

0.05

0.1

0.15

0.2

0.25

0 20 40 60 80 100

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Example of the two most important modes

for the Ford Taurus

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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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T = 00.00 ms T = 80.00 ms

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Target area

T = 00.00 ms T = 80.00 ms

Overall intrusion in dashboard

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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.

What is the Source (in time and space) of

this results Dispersion ?

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“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

investigation e.g. with the help of MultiDomain .

Blue: Original scatter modes

Green: Without scatter of

engine/Subframe

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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.

Identification of Scatter Sources and Significant Reduction of Scatter Occurrence with DIFFCRASH

Technology

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