Details
| Original language | English |
|---|---|
| Article number | 107003 |
| Journal | Computers and Structures |
| Volume | 280 |
| Early online date | 3 Mar 2023 |
| Publication status | Published - May 2023 |
Abstract
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.
Keywords
- Augmented line sampling, Decoupling, Reliability-based design optimization, Sequential optimization
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
- Mathematics(all)
- Modelling and Simulation
- Materials Science(all)
- General Materials Science
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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In: Computers and Structures, Vol. 280, 107003, 05.2023.
Research output: Contribution to journal › Article › Research › peer review
}
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 -