A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach

Journal of Computational Physics

Volumn 227, Issue 9, 2008, Pages 4697-4735

  Zabaras, N ^a   Ganapathysubramanian, B ^a  

^a School of Operations Research and Industrial Engineering   (United States)

Author keywords

Collocation methods; Inverse problems; Scalable algorithms; Sparse grids; Stochastic optimization; Stochastic partial differential equations

Indexed keywords

DIFFERENTIAL EQUATIONS; HEAT CONDUCTION; LEGACY SYSTEMS; OPTIMIZATION; SENSITIVITY ANALYSIS; STOCHASTIC SYSTEMS; UNCERTAINTY ANALYSIS;

COLLOCATION METHOD; MULTIPLE SOURCE; SCALABLE ALGORITHMS; SOURCES OF UNCERTAINTY; SPARSE GRID; STOCHASTIC INVERSE PROBLEMS; STOCHASTIC OPTIMIZATIONS; STOCHASTIC PARTIAL DIFFERENTIAL EQUATION; STOCHASTICS; UNCERTAINTY;

INVERSE PROBLEMS;

EID: 40849151822     PISSN: 00219991     EISSN: 10902716     Source Type: Journal    
DOI: 10.1016/j.jcp.2008.01.019     Document Type: Article

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