Reliability analysis involving high-dimensional, computationally expensive, highly nonlinear performance functions is a notoriously challenging problem. In this paper, we tackle this problem by proposing a new method, high-dimensional reliability analysis (HDRA), in which a surrogate model is built to approximate a performance function that is high dimensional, computationally expensive, implicit and unknown to the user. HDRA first employs the adaptive univariate dimension reduction (AUDR) method to build a global surrogate model by adaptively tracking the important dimensions or regions. Then, the sequential exploration-exploitation with dynamic trade-off (SEEDT) method is utilized to locally refine the surrogate model by identifying additional sample points that are close to the critical region (i.e., the limit-state function) with high prediction uncertainty. The HDRA method has three advantages: (i) alleviating the curse of dimensionality and adaptively detecting important dimensions; (ii) capturing the interactive effects among variables on the performance function; and (iii) flexibility in choosing the locations of sample points. The performance of the proposed method is tested through two mathematical examples, the results of which suggest that the method can achieve accurate and computationally efficient estimation of reliability even when the performance function exhibits high dimensionality, high nonlinearity, and strong interactions among variables.
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ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 6–9, 2017
Cleveland, Ohio, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-5813-4
PROCEEDINGS PAPER
High-Dimensional Reliability Analysis of Engineered Systems Involving Computationally Expensive Black-Box Simulations Available to Purchase
Mohammad Kazem Sadoughi,
Mohammad Kazem Sadoughi
Iowa State University, Ames, IA
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Cameron A. Mackenzie
Cameron A. Mackenzie
Iowa State University, Ames, IA
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Mohammad Kazem Sadoughi
Iowa State University, Ames, IA
Meng Li
Iowa State University, Ames, IA
Chao Hu
Iowa State University, Ames, IA
Cameron A. Mackenzie
Iowa State University, Ames, IA
Paper No:
DETC2017-68273, V02BT03A056; 10 pages
Published Online:
November 3, 2017
Citation
Sadoughi, MK, Li, M, Hu, C, & Mackenzie, CA. "High-Dimensional Reliability Analysis of Engineered Systems Involving Computationally Expensive Black-Box Simulations." Proceedings of the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2B: 43rd Design Automation Conference. Cleveland, Ohio, USA. August 6–9, 2017. V02BT03A056. ASME. https://doi.org/10.1115/DETC2017-68273
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