TY - JOUR
T1 - An efficient strategy for multidisciplinary reliability design and optimization based on CSSO and PMA in SORA framework
AU - Li, Liansheng
AU - Liu, Ji Hong
AU - Liu, Shaohua
PY - 2014/2
Y1 - 2014/2
N2 - The conventional reliability-based multidisciplinary design optimization (RBMDO) integrates the reliability-based design optimization and multidisciplinary design optimization (MDO) directly, which leads to a triple-level nested optimization loop. Especially, the multidisciplinary reliability analysis in the middle layer dominates the whole efficiency of RBMDO. To tackle this problem, first of all, a sequential multidisciplinary reliability analysis (SMRA) approach that integrates the concurrent subspace optimization (CSSO) strategy and the performance measure approach is proposed, in which the multidisciplinary analysis, system sensitivity analysis and reliability analysis are decoupled and arranged sequentially, making a recursive loop. The multidisciplinary analysis and system sensitivity analysis provide the value and gradient information of limit-state function for reliability analysis respectively. As a result, a great number of repeated iterations of the whole reliability analysis are eliminated. Secondly, the CSSO has been integrated with the sequential optimization and reliability assessment (SORA) to decouple the triple-level nested RBMDO procedures into a sequence of cycles of deterministic MDO and multidisciplinary reliability analysis. Therefore, the expensive computation of the whole reliability analysis model in each iteration of RBMDO is avoided. And also, the CSSO is adopted in the deterministic MDO to deal with medium-scale and coupled multidisciplinary systems. The procedures of the proposed approaches are presented in detail. The effectiveness of the proposed strategies is demonstrated and verified with two design examples.
AB - The conventional reliability-based multidisciplinary design optimization (RBMDO) integrates the reliability-based design optimization and multidisciplinary design optimization (MDO) directly, which leads to a triple-level nested optimization loop. Especially, the multidisciplinary reliability analysis in the middle layer dominates the whole efficiency of RBMDO. To tackle this problem, first of all, a sequential multidisciplinary reliability analysis (SMRA) approach that integrates the concurrent subspace optimization (CSSO) strategy and the performance measure approach is proposed, in which the multidisciplinary analysis, system sensitivity analysis and reliability analysis are decoupled and arranged sequentially, making a recursive loop. The multidisciplinary analysis and system sensitivity analysis provide the value and gradient information of limit-state function for reliability analysis respectively. As a result, a great number of repeated iterations of the whole reliability analysis are eliminated. Secondly, the CSSO has been integrated with the sequential optimization and reliability assessment (SORA) to decouple the triple-level nested RBMDO procedures into a sequence of cycles of deterministic MDO and multidisciplinary reliability analysis. Therefore, the expensive computation of the whole reliability analysis model in each iteration of RBMDO is avoided. And also, the CSSO is adopted in the deterministic MDO to deal with medium-scale and coupled multidisciplinary systems. The procedures of the proposed approaches are presented in detail. The effectiveness of the proposed strategies is demonstrated and verified with two design examples.
KW - Concurrent subspace optimization (CSSO)
KW - Performance measure approach (PMA)
KW - Reliability-based multidisciplinary design optimization (RBMDO)
KW - Sequential multidisciplinary reliability analysis (SMRA)
KW - Sequential optimization and reliability assessment (SORA)
UR - https://www.scopus.com/pages/publications/84894238318
U2 - 10.1007/s00158-013-0966-x
DO - 10.1007/s00158-013-0966-x
M3 - 文章
AN - SCOPUS:84894238318
SN - 1615-147X
VL - 49
SP - 239
EP - 252
JO - Structural and Multidisciplinary Optimization
JF - Structural and Multidisciplinary Optimization
IS - 2
ER -