#5653. Structural uncertainty analysis with the multiplicative dimensional reduction–based polynomial chaos expansion approach

August 2026publication date
Proposal available till 22-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Control and Optimization;
Computer Graphics and Computer-Aided Design;
Computer Science Applications;
Control and Systems Engineering;
Software;
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Abstract:
This paper presents an efficient polynomial chaos expansion approach for structural uncertainty analysis in conjunction with the multiplicative dimensional reduction method. The development of a standard polynomial chaos expansion model needs to evaluate a large number of multivariate integrals for the expansion coefficient. The utility of the multiplicative dimensional reduction approach is able to approximate the multivariate integral as the product of univariate and bivariate expectations. Together with the standard Gauss-quadrature scheme for accurate low-variate integration results, an effective polynomial chaos expansion model is proposed to mimic the true performance function for structural uncertainty analysis.
Keywords:
Multiplicative dimensional reduction method; Polynomials chaos expansion; Reliability-based design optimization; The Gauss-quadrature scheme; Uncertainty analysis

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