A stochastic collocation method for elliptic partial differential equations with random input data

SIAM Journal on Numerical Analysis

Volumn 45, Issue 3, 2007, Pages 1005-1034

  Babuška, Ivo ^a   Nobile, Fabio ^b   Tempone, Raúl ^c  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b POLITECNICO DI MILANO   (Italy)

^c FLORIDA STATE UNIVERSITY   (United States)

Author keywords

Collocation method; Exponential convergence; Finite elements; Stochastic partial differential equations; Uncertainty quantification

Indexed keywords

APPLIED MATHEMATICS; CONVERGENCE ANALYSIS; DETERMINISTIC PROBLEMS; DIFFUSIVITY; ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS; EXPONENTIAL CONVERGENCE; FINITE NUMBERS; FORCING TERMS; GALERKIN; GALERKIN APPROXIMATIONS; GAUSS POINTS; INPUT DATA; MONTE CARLO APPROACH; NUMERICAL EXAMPLES; ORTHOGONAL POLYNOMIALS; PROBABILITY SPACES; RANDOM COEFFICIENTS; RANDOM INPUT; SECOND MOMENTS; STOCHASTIC COLLOCATION; TENSOR PRODUCT (TP); WIDER RANGE;

CLUSTER ANALYSIS; COMPUTATIONAL FLUID DYNAMICS; CONVERGENCE OF NUMERICAL METHODS; DIFFERENCE EQUATIONS; DIFFERENTIAL EQUATIONS; DIFFERENTIATION (CALCULUS); ERROR ANALYSIS; FOURIER ANALYSIS; GALERKIN METHODS; IMAGE SEGMENTATION; NUMERICAL ANALYSIS; POLYNOMIAL APPROXIMATION; POLYNOMIALS; PROBABILITY; RANDOM PROCESSES; RANDOM VARIABLES; RISK ASSESSMENT; STOCHASTIC MODELS; STOCHASTIC PROGRAMMING; TENSORS;

PARTIAL DIFFERENTIAL EQUATIONS;

EID: 34548216854     PISSN: 00361429     EISSN: None     Source Type: Journal    
DOI: 10.1137/050645142     Document Type: Article

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