L-Moments-Based FORM Method for Structural Reliability Analysis Considering Correlated Input Random Variables

Leveraging the properties of the first three linear moments (L-moments), this study proposes an effective normal transformation for structural reliability analysis considering correlated input random variables, in which the admissible range of the initial correlation matrix when employing this transformation is also presented. Subsequently, a practical procedure for structural reliability analysis, grounded in the proposed transformation and first-order reliability method (FROM), is proposed, accommodating instances wherein the joint probability density functions (PDFs) or marginal PDFs of the relevant random variables remain unknown. In comparison to the technique premised on the first three central moments (C-moments), the proposed method, based on the first three L-moments, exhibits a more extensive applicability. Various practical scenarios showcase the method's effectiveness and precision in calculating the structural reliability index, considering diverse distributions, numerous variables, and complex structures.

Automated summary

Leveraging the properties of L-moments, this study proposes an effective normal transformation for structural reliability analysis considering correlated input random variables, and provides the admissible range of the initial correlation matrix. A practical procedure based on the proposed transformation and FROM is introduced to handle unknown joint PDFs or marginal PDFs. Compared to the method using C-moments, the proposed method based on L-moments shows broader applicability. Various practical scenarios demonstrate its effectiveness and precision in calculating the structural reliability index.