Efficient response surface method for high-dimensional structural reliability analysis. (September 2017)

• Record Type: Journal Article
• Authors: Hadidi, Ali; Azar, Bahman Farahmand; Rafiee, Amin
• Is Part Of: Structural safety. Volume 68(2017)
• Page Start: 15
• Page End: 27
• Publication Date: 2017-09
• Subjects: High-dimensional structural reliability -- Exponential response surface -- Reliability-based design optimization -- Failure probability; Structural stability -- Periodicals; Safety factor in engineering -- Periodicals; Reliability (Engineering) -- Periodicals; Constructions -- Stabilité -- Périodiques; Coefficient de sécurité en ingénierie -- Périodiques; Fiabilité -- Périodiques; 620.86
• DOI: 10.1016/j.strusafe.2017.03.006
• Languages: English
• ISSNs: 0167-4730

Abstract

Highlights: A novel approach for selection of locations of experimental points is suggested. Exponential response surface is used to reduce the number of required experiments. Experiment updating scheme is proposed to reduce the number of required experiments. Examples show high accuracy of proposed method for estimation of failure probability. Examples show high efficiency of proposed method for high dimensional problems. Abstract: In common response surface method (RSM) for structural reliability analysis, performances of several experimental points must be evaluated via finite element analysis. The number of required experimental points is proportional to the number of random variables. Hence, for a high-dimensional structural reliability problem, computational cost is high, especially for structures with computationally intensive finite element models. On the other hand, the accuracy of classical RSM in estimating the probability of failure depends on the locations of experimental points. This paper proposes an efficient and accurate RSM. The efficiency is increased by using exponential surrogate model instead of quadratic one and by using experiment updating technique. In this way, the number of required experimental points is significantly reduced. Meanwhile, the accuracy of RSM is improved by choosing locations of experimental points judiciously, such that, to be close to the actual limit state surface. Five examples are solved to demonstrate the high efficiency and accuracy of the proposed method.