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A comprehensive metric for comparing time histories in validation of simulation models with emphasis on vehicle safety applications
Department of Mechanical Engineering, University of Michigan.
Department of Mechanical Engineering, University of Michigan.
Department of Mechanical Engineering, University of Michigan.
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2009 (English)In: Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - 2008: presented at 2008 ASME International Design Engineering Conferences and Computers and Information in Engineering Conference, August 3 - 6, 2008, New York City, New York, USA, New York: American Society of Mechanical Engineers , 2009, Vol. 1 Part B, p. 1275-1286Conference paper, Published paper (Refereed)
Abstract [en]

Computer modeling and simulation are the cornerstones of product design and development in the automotive industry. Computer-aided engineering tools have improved to the extent that virtual testing may lead to significant reduction in prototype building and testing of vehicle designs. In order to make this a reality, we need to assess our confidence in the predictive capabilities of simulation models. As a first step in this direction, this paper deals with developing a metric to compare time histories that are outputs of simulation models to time histories from experimental tests with emphasis on vehicle safety applications. We focus on quantifying discrepancy between time histories as the latter constitute the predominant form of responses of interest in vehicle safety considerations. First we evaluate popular measures used to quantify discrepancy between time histories in fields such as statistics, computational mechanics, signal processing, and data mining. Then we propose a structured combination of some of these measures and define a comprehensive metric that encapsulates the important aspects of time history comparison. The new metric classifies error components associated with three physically meaningful characteristics (phase, magnitude and topology), and utilizes norms, cross-correlation measures and algorithms such as dynamic time warping to quantify discrepancies. Two case studies demonstrate that the proposed metric seems to be more consistent than existing metrics. It is also shown how the metric can be used in conjunction with ratings from subject matter experts to build regression-based validation models

Place, publisher, year, edition, pages
New York: American Society of Mechanical Engineers , 2009. Vol. 1 Part B, p. 1275-1286
Identifiers
URN: urn:nbn:se:ltu:diva-33112Local ID: 7e569de0-39e8-4b32-95d3-2f4ac11df071ISBN: 9780791843253 (print)OAI: oai:DiVA.org:ltu-33112DiVA, id: diva2:1006348
Conference
ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference : 03/08/2008 - 06/08/2008
Note
Upprättat; 2011; 20110325 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
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More languages
Output format
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  • asciidoc
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