Distribution-free polynomial chaos expansion surrogate models for efficient structural reliability analysis

HyeongUk Lim and Lance Manuel

Reliability Engineering and System Safety, 2021, vol. 205, issue C

Abstract: In complex stochastic high-dimensional reliability studies, polynomial chaos expansion (PCE) has been widely used to build surrogate models in lieu of prohibitively expensive Monte Carlo simulation (MCS). PCE relies on parametric distributions for associated variables and appropriate basis functions. However, incomplete or imperfect information on the stochastic variables can limit its use; accepted parametric forms for variable distributions, for instance, may not be justified when variables display multimodal character or mixed discrete-continuous support. Also, the dependency structure among the random variables may be complex, which can make probabilistic mapping or transformation to independent variables needed for PCE cumbersome. Nonlinearities in such transformations can affect the accuracy of PCE surrogate models and lead to slower convergence relative to “truth†system computations of desired QoIs (quantities of interest). To address these challenges, a distribution-free PCE approach is proposed. We compute joint raw moments of underlying random input variables for Gram-Schmidt orthogonalization in developing surrogate models. Using illustrative examples, we demonstrate the proposed approach as an efficient and accurate surrogate model-building alternative to traditional PCE.

Keywords: Structural reliability; MCS; PCE (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832020307560
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:205:y:2021:i:c:s0951832020307560

DOI: 10.1016/j.ress.2020.107256

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().