Data analysis for parallel car-crash simulation results and model optimization |
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| Affiliation: | 1. College of Science, Xi’an Jiaotong University Xi’an, 710049, PR China;2. Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53754 St. Augustin, Germany;1. Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy;2. School of Science and Technology, University of Camerino, Camerino, Italy;1. Laboratory of Biocomposite Technology, Institute of Tropical Forestry and Forest Products (INTROP), University Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia;2. Faculty of Information Sciences and Engineering, Management Science & University, Seksyen 13, 40100 Shah Alam, Selangor, Malaysia;3. Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia;4. Aerospace Manufacturing Research Centre (AMRC), Department of Aerospace Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia;5. Faculty of Engineering, International Islamic University Malaysia, 53100 Jalan Gombak, Kuala Lumpur, Malaysia;1. School of Aeronautics and Astronautics, Purdue University, 701 West Stadium Avenue, West Lafayette, IN 47907, USA;2. School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907, USA;3. School of Materials Engineering, Purdue University, 701 West Stadium Avenue, West Lafayette, IN 47907, USA;1. Institute of Mathematics, Lodz University of Technology, Lodz, Poland;2. Department of Vehicles and Fundamentals of Machine Design, Lodz University of Technology, Lodz, Poland;3. Institute of Social Sciences and Management of Technologies, Lodz University of Technology, Lodz, Poland |
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| Abstract: | The paper discusses automotive crash simulation in a stochastic context, whereby the uncertainties in numerical simulation results generated by parallel computing. Since crash is a non-repeatable phenomenon, qualification for crashworthiness based on a single test is not meaningful, and should be replaced by stochastic simulation. But the stochastic simulations may generate different results on parallel machines, if the same application is executed more than once. For a benchmark car model, differences between the position of a node in two simulation runs of PAMCRASH or LS-DYNA of up to 10 cm were observed, just as a result of round-off differences in the case of parallel computing. In this paper, some data mining algorithms are described to measure the scatter of parallel simulation results of car-crash and then provide hints to overcome this scatter to get more stable car model. |
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