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Brief Overview of Stochastic Solvers for the Propagation of Uncertainties

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Uncertainty Quantification

Part of the book series: Interdisciplinary Applied Mathematics ((IAM,volume 47))

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Abstract

The course is focused on the stochastic modeling of uncertainties and their identification by solving statistical inverse problems. The course is not devoted to the mathematical developments related to the stochastic solvers (there are many textbooks devoted to this subject). In this context, this chapter is limited to a list of principal approaches and to a brief description of the Galerkin method (spectral approach) and to the Monte Carlo method.

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Authors and Affiliations

  1. Laboratoire Modélisation et Simulation Multi-Echelle (MSME), Université Paris-Est Marne-la-Vallée (UPEM), Marne-la-Vallée, France

    Christian Soize

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  1. Christian Soize
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Soize, C. (2017). Brief Overview of Stochastic Solvers for the Propagation of Uncertainties. In: Uncertainty Quantification. Interdisciplinary Applied Mathematics, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-54339-0_6

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