Uncertainty quantification by polynomial chaos expansion for geotechnical reliability-based analysis

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Sónia Marques (Author) FEUP; António Topa Gomes (Author) FEUP; António Abel Henriques (Author) FEUP

Conference proceedings International

Title: Geotechnical Safety and Risk IV - Proceedings of the 4th International Symposium on Geotechnical Safety and Risk, ISGSR 2013

Pages: 145-150

4th International Symposium on Geotechnical Safety and Risk, ISGSR 2013

Hong Kong, 4 December 2013 through 6 December 2013

Indexing

Scopus - 0 Citations

COMPENDEX

Scientific classification

FOS: Engineering and technology > Civil engineering

CORDIS: Technological sciences > Engineering > Civil engineering > Geotechnics ; Technological sciences > Engineering > Civil engineering

Other information

Authenticus ID: P-00G-2DC

DOI: 10.1201/b16058-17

Abstract (EN): Uncertainty quantification is the process of determining the effect of input uncertainties on response metrics of interest. Many approximate methods have been developed so far for the purpose, and among these methods the polynomial chaos expansion is considered a technique with strong mathematical basis and ability to produce functional representation of stochastic variability. The approach has proven to be an efficient methodology to study several stochastic problems, considered the original form where optimal convergence for orthogonal Hermite polynomials is only achieved for gaussian stochastic processes. Regarding the developments in the stochastic response surface methodology and some heuristic and optimisation concepts, results for a design example with correlated nonnormal random variables are presented in the light of the quality of the approximate metamodels. Considered truncated full and sparse polynomial chaos expansions, the efficiency and accuracy provided by different schemes of experimental design are analysed and the convergence process is lastly discussed. © 2014 Taylor & Francis Group, London.

Language: English

Type (Professor's evaluation): Scientific