Uncertainty quantification under dependent random variables by a generalized polynomial dimensional decomposition

• Published in: Computer methods in applied mechanics and engineering Vol. 344; pp. 910 - 937
• Main Author: Rahman, Sharif
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.02.2019; Elsevier BV
• Subjects: ANOVA; Boundary value problems; Complex systems; Decomposition; Dependence; Dependent variables; Eigenvalues; Error analysis; Formulas (mathematics); Independent variables; Linear equations; Multivariate orthogonal polynomials; Non-product-type probability measures; Polynomials; Random variables; Statistical analysis; Thermal expansion; Uncertainty analysis; Variance; Multivariate orthogonal polynomials; ANOVA; Non-product-type probability measures

This paper is concerned with uncertainty quantification analysis of complex systems subject to dependent input random variables. The analysis focuses on a new, generalized version of polynomial dimensional decomposition (PDD), referred to as GPDD, entailing hierarchically ordered measure-consistent...