Uncertainty Analysis for Parallel Car-crash Simulation Results

Liquan Mei () and C.A. Thole
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Liquan Mei: Xi’an Jiaotong University, School of Science
C.A. Thole: Schloss Birlinghoven, Fraunhofer Institute for Algorithms and Scientific Computing

A chapter in Current Trends in High Performance Computing and Its Applications, 2005, pp 393-398 from Springer

Abstract: Abstract Small changes in parameters, load cases or model specifications for crash simulation may result in huge changes in the results, characterizing the crash behavior of an automotive design. For a BMW test case, differences between the position of a node in two simulation runs of up to 10 cm were observed, just as a result of round-off differences in the case of parallel computing. The paper shows that numerical properties of the simulation codes as well as bifurcations in the crash behavior in the certain parts of the design are reasons for scatter of simulation results. The tool DIFF-CRASHℳ was developed to compare simulation results and cluster those nodes of the car model, which show similar scatter among the simulation runs and then trace back to a certain part to remove the uncertain behavior. DIFF-CRASHℳ is the only activity using data mining technology for crash simulation uncertainty analysis.

Keywords: Uncertainty analysis; Crash Simulation; Data Mining; Clustering (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-27912-9_50

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DOI: 10.1007/3-540-27912-1_50

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