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Mean-value first-order saddlepoint approximation based collaborative optimization for multidisciplinary problems under aleatory uncertainty

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Abstract

Reliability-based multidisciplinary design optimization (RBMDO) has received increasing attention in engineering design for achieving high reliability and safety in complex and coupling systems (e.g., multidisciplinary systems). Mean-value first-order saddlepoint approximation (MVFOSA) is introduced in this paper and is combined with the collaborative optimization (CO) method for reliability analysis under aleatory uncertainty in RBMDO. Similar to the mean-value first-order second moment (MVFOSM) method, MVFOSA approximated the performance function with the first-order Taylor expansion at the mean values of random variables. MVFOSA uses saddlepoint approximation rather than the first two moments of the random variables to estimate the probability density and cumulative distribution functions. MVFOSA-based CO (MVFOSA-CO) is also formulated and proposed. Two examples are provided to show the accuracy and efficiency of the MVFOSA-CO method.

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Authors and Affiliations

  1. School of Mechanical, Electronic, and Industrial Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan, 611731, China

    Debiao Meng, Hong-Zhong Huang, Zhonglai Wang, Ning-Cong Xiao & Xiao-Ling Zhang

Authors
  1. Debiao Meng
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  2. Hong-Zhong Huang
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  3. Zhonglai Wang
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  4. Ning-Cong Xiao
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  5. Xiao-Ling Zhang
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Corresponding author

Correspondence to Hong-Zhong Huang.

Additional information

Debiao Meng is a Ph.D. student at the University of Electronic Science and Technology of China. He received his B.S. degree in Mechanical Engineering from Northwest A&F University. His main research interests include reliability-based design and optimization and reliability-based multidisciplinary design and optimization.

Hong-Zhong Huang is the Dean of the School of Mechanical, Electronic, and Industrial Engineering at the University of Electronic Science and Technology of China. He received his Ph.D. in Reliability Engineering from Shanghai Jiaotong University, China. He has published 150 journal papers and 5 books on reliability engineering. He has held visiting appointments at several universities in the United States, Canada, and Asia. He received the Golomski Award from the Institute of Industrial Engineers in 2006. His current research interests include system reliability analysis, warranty, maintenance planning and optimization, and computational intelligence in product design.

Zhonglai Wang received his Ph.D. in Mechatronics Engineering from the University of Electronic Science and Technology of China, where he is currently an associate professor. He was a visiting scholar in the Department of Mechanical and Aerospace Engineering of Missouri University of Science and Technology from 2007 to 2008. His research interests include reliability-based design and robust design.

Ning-Cong Xiao received his Ph.D. in Mechatronics Engineering from the University of Electronic Science and Technology of China, where he is currently a lecturer. He was a visiting scholar in the Department of Industrial and Systems Engineering of Rutgers University from 2011 to 2012. His research interests include reliability-based design and robust design.

Xiao-Ling Zhang received her Ph.D. in Mechatronics Engineering from the University of Electronic Science and Technology of China, where she is currently a lecturer. She was a visiting scholar in the Department of Mechanical and Aerospace Engineering of Rutgers University from 2009 to 2011. Her research interests include reliability-based multidisciplinary design and optimization.

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Meng, D., Huang, HZ., Wang, Z. et al. Mean-value first-order saddlepoint approximation based collaborative optimization for multidisciplinary problems under aleatory uncertainty. J MECH SCI TECHNOL 28, 3925–3935 (2014). https://doi.org/10.1007/s12206-014-0903-y

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  • DOI: https://doi.org/10.1007/s12206-014-0903-y

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