Xue-Qin Li¹, Lu-Kai Song^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 665-684, 2024, DOI:10.32604/cmes.2024.048445

Abstract Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function, leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy. In this case, by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory, a random forest (RF) model is presented to enhance the computing efficiency of reliability degree; moreover, by embedding the RF model into multilevel optimization model, an efficient RF-assisted fatigue reliability-based design optimization framework is developed. Regarding the low-cycle fatigue reliability-based design optimization of… More >

Debiao Meng^1,2,*, Yipeng Guo^1,2, Yihe Xu³, Shiyuan Yang^1,2,*, Yongqiang Guo⁴, Lidong Pan⁴, Xinkai Guo²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2329-2359, 2024, DOI:10.32604/cmes.2024.047507

Abstract The escalating need for reliability analysis (RA) and reliability-based design optimization (RBDO) within engineering challenges has prompted the advancement of saddlepoint approximation methods (SAM) tailored for such problems. This article offers a detailed overview of the general SAM and summarizes the method characteristics first. Subsequently, recent enhancements in the SAM theoretical framework are assessed. Notably, the mean value first-order saddlepoint approximation (MVFOSA) bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation (MVSOSA); the latter serves as an auxiliary approach to the former. Their distinction is rooted in the varying expansion orders of the performance function as… More >

Xiaoyi Wang¹, Xinyue Chang², Wenxuan Wang^1,*, Zijie Qiao³, Feng Zhang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1775-1796, 2024, DOI:10.32604/cmes.2023.043913

Abstract The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested loop reliability optimization model is… More >