Toward a Unified Multiresolution Scheme in the Combined Physical/Stochastic Space for Stochastic Differential Equations
ABGRALL, Remi
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Institut de Mathématiques de Bordeaux [IMB]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Institut de Mathématiques de Bordeaux [IMB]
CONGEDO, Pietro Marco
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
GERACI, Gianluca
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
ABGRALL, Remi
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Institut de Mathématiques de Bordeaux [IMB]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Institut de Mathématiques de Bordeaux [IMB]
CONGEDO, Pietro Marco
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
GERACI, Gianluca
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
< Leer menos
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Idioma
en
Rapport
Este ítem está publicado en
2012-06-18
Resumen en inglés
In the present work, an innovative method for solving stochastic partial differential equations is presented. A multiresolution method permitting to compute statistics of the quantity of interest for a whatever form of the ...Leer más >
In the present work, an innovative method for solving stochastic partial differential equations is presented. A multiresolution method permitting to compute statistics of the quantity of interest for a whatever form of the probability density function is extended to permit an adaptation in both physical and stochastic spaces. The efficiency of this strategy, in terms of refinement/derefinement capabilities, is displayed for stochastic algebraic and differential equations with respect to other more classical techniques, like Monte Carlo (MC) and Polynomial Chaos (PC). Finally, the proposed strategy is applied to the heat equation, displaying very promising results in terms of accuracy, convergence and regularity.< Leer menos
Orígen
Importado de HalCentros de investigación