TY - JOUR

T1 - Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm

AU - Yuan, Xiukai

AU - Valdebenito, Marcos A.

AU - Zhang, Baoqiang

AU - Faes, Matthias G.R.

AU - Beer, Michael

N1 - Funding Information: Xiukai Yuan would like to acknowledge financial support from the Aeronautical Science Foundation of China (Grant No. ASFC-20170968002). Baoqiang Zhang acknowledges the financial support from National Science and Technology Major Project (Grant No. 2019-I-0006-0006), Special Project on the Integration of Industry, Education and Research of AECC (Grant No. HFZL2020CXY004 and HFZL2020CXY009).

PY - 2023/5

Y1 - 2023/5

N2 - This paper presents a novel decoupling approach to efficiently solve a class of reliability-based design optimization (RBDO) problems by means of augmented Line Sampling. The proposed approach can fully decouple the original RBDO by replacing the probabilistic constraint with the failure probability function (FPF), which is an explicit function of the design variables. One attractive feature is that the main numerical cost associated with this decoupling comes with only one implementation of augmented Line Sampling, which is actually highly efficient. And for the sake of accuracy, the proposed approach incorporates decoupling with the sequential optimization framework to solve the RBDO problem iteratively. On top of that, an optimal combination algorithm is proposed to reuse the information through aggregating the local estimates of FPF obtained in different iterations to produce an improved estimate, resulting in a more accurate and stable solution. Examples are given to show the effectiveness and efficiency of the proposed approach.

AB - This paper presents a novel decoupling approach to efficiently solve a class of reliability-based design optimization (RBDO) problems by means of augmented Line Sampling. The proposed approach can fully decouple the original RBDO by replacing the probabilistic constraint with the failure probability function (FPF), which is an explicit function of the design variables. One attractive feature is that the main numerical cost associated with this decoupling comes with only one implementation of augmented Line Sampling, which is actually highly efficient. And for the sake of accuracy, the proposed approach incorporates decoupling with the sequential optimization framework to solve the RBDO problem iteratively. On top of that, an optimal combination algorithm is proposed to reuse the information through aggregating the local estimates of FPF obtained in different iterations to produce an improved estimate, resulting in a more accurate and stable solution. Examples are given to show the effectiveness and efficiency of the proposed approach.

KW - Augmented line sampling

KW - Decoupling

KW - Reliability-based design optimization

KW - Sequential optimization

UR - http://www.scopus.com/inward/record.url?scp=85149360237&partnerID=8YFLogxK

U2 - 10.1016/j.compstruc.2023.107003

DO - 10.1016/j.compstruc.2023.107003

M3 - Article

AN - SCOPUS:85149360237

VL - 280

JO - Computers and Structures

JF - Computers and Structures

SN - 0045-7949

M1 - 107003

ER -