Inscrição na biblioteca: Guest
Portal Digital Begell Biblioteca digital da Begell eBooks Diários Referências e Anais Coleções de pesquisa
International Journal for Uncertainty Quantification
Fator do impacto: 3.259 FI de cinco anos: 2.547 SJR: 0.531 SNIP: 0.8 CiteScore™: 1.52

ISSN Imprimir: 2152-5080
ISSN On-line: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2011003306
pages 1-23

POLYNOMIAL CHAOS FOR SEMIEXPLICIT DIFFERENTIAL ALGEBRAIC EQUATIONS OF INDEX 1

Roland Pulch
Department of Mathematics and Computer Science University of Greifswald Domstraße 11, 17489 Greifswald, Germany

RESUMO

Mathematical modeling of technical applications often yields systems of differential algebraic equations. Uncertainties of physical parameters can be considered by the introduction of random variables. A corresponding uncertainty quantification requires one to solve the stochastic model. We focus on semiexplicit systems of nonlinear differential algebraic equations with index 1. The stochastic model is solved using the expansion of the generalised polynomial chaos. We investigate both the stochastic collocation technique and the stochastic Galerkin method to determine the unknown coefficient functions. In particular, we analyze the index of the larger coupled systems, which result from the stochastic Galerkin method. Numerical simulations of test examples are presented, where the two approaches are compared with respect to their efficiency.


Articles with similar content:

STOCHASTIC GALERKIN METHODS AND MODEL ORDER REDUCTION FOR LINEAR DYNAMICAL SYSTEMS
International Journal for Uncertainty Quantification, Vol.5, 2015, issue 3
E. Jan W. ter Maten, Roland Pulch
POLYNOMIAL CHAOS FOR LINEAR DIFFERENTIAL ALGEBRAIC EQUATIONS WITH RANDOM PARAMETERS
International Journal for Uncertainty Quantification, Vol.1, 2011, issue 3
Roland Pulch
ON THE ROBUSTNESS OF STRUCTURAL RISK OPTIMIZATION WITH RESPECT TO EPISTEMIC UNCERTAINTIES
International Journal for Uncertainty Quantification, Vol.2, 2012, issue 1
W. J. S. Gomes, F. A. V. Bazan, Andre T. Beck
TIME AND FREQUENCY DOMAIN METHODS FOR BASIS SELECTION IN RANDOM LINEAR DYNAMICAL SYSTEMS
International Journal for Uncertainty Quantification, Vol.8, 2018, issue 6
John D. Jakeman, Roland Pulch
ASSESSMENT OF COLLOCATION AND GALERKIN APPROACHES TO LINEAR DIFFUSION EQUATIONS WITH RANDOM DATA
International Journal for Uncertainty Quantification, Vol.1, 2011, issue 1
Raymond S. Tuminaro, Eric T. Phipps, Christopher W. Miller, Howard C. Elman