GUAN Xingyu,OU Erfeng,ZHANG Xuxu,et al.Implementation and Application of Non‑Intrusive Stochastic Finite Element Method Based on Stochastic Response Surface Method[J].Journal of Disaster Prevention and Mitigation Engineering,2025,45(01):233-239.
GUAN Xingyu,OU Erfeng,ZHANG Xuxu,et al.Implementation and Application of Non‑Intrusive Stochastic Finite Element Method Based on Stochastic Response Surface Method[J].Journal of Disaster Prevention and Mitigation Engineering,2025,45(01):233-239. DOI: 10.13409/j.cnki.jdpme.20230715001.
Implementation and Application of Non‑Intrusive Stochastic Finite Element Method Based on Stochastic Response Surface Method
With the continued development of reliability theory
solving the structural reliability under implicit performance functions has become a challenge. Currently
the non-intrusive stochastic finite element method is an important approach to address this issue. This paper develops a non-intrusive stochastic finite element method based on the stochastic response surface method. Using MATLAB and ANSYS for coupled simulation
a computational program for this method was developed. The program performed deterministic mechanical analysis through ANSYS
and it could automatically invoke ANSYS in MATLAB to continuously solve output response results under different parameter configurations. It could read the results to calculate the unknown coefficients of the random polynomials. This method obtained structural output results through finite element software without the need to analyze the performance functions
providing an effective approach for reliability calculation in complex structures. The effectiveness of this method in structural reliability analysis was verified through three examples. The results showed that both the stochastic response surface method and the non-intrusive stochastic finite element method based on the stochastic response surface method exhibited small errors when calculating structural failure probability and had significantly higher computational efficiency compared to the Monte Carlo method. It demonstrates clear advantages in solving failure probability without explicit performance functions.
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