Combined parametric-nonparametric uncertainty quantification using random matrix theory and polynomial chaos expansion

Pascual, B. and Adhikari, S. (2012) Combined parametric-nonparametric uncertainty quantification using random matrix theory and polynomial chaos expansion. Computers and Structures, 112, pp. 364-379. (doi: 10.1016/j.compstruc.2012.08.008)

Abstract

Propagation of combined parametric and nonparametric uncertainties in elliptic partial differential equations is considered. Two cases, namely, (a) both uncertainties are over the entire domain, and (b) different types of uncertainties are over non-overlapping subdomains are proposed. Parametric uncertainty is modelled by a random field and is discretised using the Karhunen–Loève (KL) expansion. The nonparametric uncertainty is modelled by Wishart random matrix. Both uncertainties are considered independent, and the two first moments of the response are calculated using polynomial chaos expansion and analytical random matrix theory results. Closed-form analytical expressions of the first two moments are derived for both cases.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Adhikari, Professor Sondipon
• Authors: Pascual, B., and Adhikari, S.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Computers and Structures
• Publisher: Elsevier
• ISSN: 0045-7949
• ISSN (Online): 1879-2243