Reliability analysis based on the simulation model could be wrong if the simulation model were not validated. Various model bias correction approaches have been developed to improve the model credibility by adding the identified model bias to the baseline simulation model. However, little research has been conducted for simulation models with dynamic system responses. This paper presents such a framework for model bias correction of dynamic system responses for reliability analysis by addressing three technical components including: i) a validation metric for dynamic system responses, ii) an effective approach for dynamic model bias calibration and approximation, and iii) reliability analysis considering the dynamic model bias. Two case studies including a thermal problem and a corroded beam problem are employed to demonstrate the proposed approaches for simulation-based reliability analysis.
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ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 2–5, 2015
Boston, Massachusetts, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-5708-3
PROCEEDINGS PAPER
Stochastic Model Bias Correction of Dynamic System Responses for Simulation-Based Reliability Analysis
Zhimin Xi,
Zhimin Xi
University of Michigan Dearborn, Dearborn, MI
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Hao Pan,
Hao Pan
University of Michigan Dearborn, Dearborn, MI
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Ren-Jye Yang
Ren-Jye Yang
Ford Motor Company, Dearborn, MI
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Zhimin Xi
University of Michigan Dearborn, Dearborn, MI
Hao Pan
University of Michigan Dearborn, Dearborn, MI
Ren-Jye Yang
Ford Motor Company, Dearborn, MI
Paper No:
DETC2015-46938, V02BT03A056; 10 pages
Published Online:
January 19, 2016
Citation
Xi, Z, Pan, H, & Yang, R. "Stochastic Model Bias Correction of Dynamic System Responses for Simulation-Based Reliability Analysis." Proceedings of the ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2B: 41st Design Automation Conference. Boston, Massachusetts, USA. August 2–5, 2015. V02BT03A056. ASME. https://doi.org/10.1115/DETC2015-46938
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