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Debiao Meng,Hong-Zhong Huang,Zhonglai Wang,Ning-Cong Xiao,Xiao-Ling Zhang 대한기계학회 2014 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.28 No.10
Reliability-based multidisciplinary design optimization (RBMDO) has received increasing attention in engineering design for achievinghigh 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 reliabilityanalysis under aleatory uncertainty in RBMDO. Similar to the mean-value first-order second moment (MVFOSM) method, MVFOSAapproximated the performance function with the first-order Taylor expansion at the mean values of random variables. MVFOSA usessaddlepoint approximation rather than the first two moments of the random variables to estimate the probability density and cumulativedistribution functions. MVFOSA-based CO (MVFOSA-CO) is also formulated and proposed. Two examples are provided to show theaccuracy and efficiency of the MVFOSA-CO method.
Hong-Zhong Huang,Xudong Zhang,Yu Liu,Debiao Meng,Zhonglai Wang 대한기계학회 2012 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.26 No.7
Reliability-based design optimization (RBDO) has been receiving increasing attention for achieving high safety and reliability in engineering design. Sequential optimization and reliability assessment (SORA), as one of the efficient single-loop methods, decouples an RBDO problem into sequential deterministic optimization and reliability analysis. An enhanced SORA (ESORA) method is proposed with the aim of further improving the computational efficiency for RBDO, considering both cases of constant and varying variances of random design inputs while keeping the single-loop framework. Vehicle side impact example is used to test and compare the efficiency of the proposed method with existing approaches.
Hong-Zhong Huang,Xudong Zhang,Debiao Meng,Zhonglai Wang,Yu Liu 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.6
Reliability based design optimization (RBDO) has been widely implemented in engineering practices for high safety and reliability. It is an important challenge to improve computational efficiency. Sequential optimization and reliability assessment (SORA) has made great efforts to improve computational efficiency by decoupling a RBDO problem into sequential deterministic optimization and reliability analysis as a single-loop method. In this paper, in order to further improve computational efficiency and extend the application of the current SORA method, an enhanced SORA (ESORA) is proposed by considering constant and varying variances of random design variables while keeping the sequential framework. Some mathematical examples and an engineering case are given to illustrate the proposed method and validate the efficiency.