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Uncertainty Analysis for Parallel Car-crash Simulation Results

In: Current Trends in High Performance Computing and Its Applications

Author

Listed:
  • Liquan Mei

    (Xi’an Jiaotong University, School of Science)

  • C.A. Thole

    (Schloss Birlinghoven, Fraunhofer Institute for Algorithms and Scientific Computing)

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.

Suggested Citation

  • Liquan Mei & C.A. Thole, 2005. "Uncertainty Analysis for Parallel Car-crash Simulation Results," Springer Books, in: Wu Zhang & Weiqin Tong & Zhangxin Chen & Roland Glowinski (ed.), Current Trends in High Performance Computing and Its Applications, pages 393-398, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27912-9_50
    DOI: 10.1007/3-540-27912-1_50
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