Layer methods for stochastic Navier–Stokes equations using simplest characteristics

We propose and study a layer method for stochastic Navier-Stokes equations (SNSE) with spatial periodic boundary conditions and additive noise. The method is constructed using conditional probabilistic representations of solutions to SNSE and exploiting ideas of the weak sense numerical integration...

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Main Authors: Milstein, G.N., Tretyakov, M.V.
Format: Article
Published: Elsevier 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/32272/
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author Milstein, G.N.
Tretyakov, M.V.
author_facet Milstein, G.N.
Tretyakov, M.V.
author_sort Milstein, G.N.
building Nottingham Research Data Repository
collection Online Access
description We propose and study a layer method for stochastic Navier-Stokes equations (SNSE) with spatial periodic boundary conditions and additive noise. The method is constructed using conditional probabilistic representations of solutions to SNSE and exploiting ideas of the weak sense numerical integration of stochastic differential equations. We prove some convergence results for the proposed method including its first mean-square order. Results of numerical experiments on two model problems are presented.
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institution University of Nottingham Malaysia Campus
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publishDate 2016
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spelling nottingham-322722020-05-04T18:06:56Z https://eprints.nottingham.ac.uk/32272/ Layer methods for stochastic Navier–Stokes equations using simplest characteristics Milstein, G.N. Tretyakov, M.V. We propose and study a layer method for stochastic Navier-Stokes equations (SNSE) with spatial periodic boundary conditions and additive noise. The method is constructed using conditional probabilistic representations of solutions to SNSE and exploiting ideas of the weak sense numerical integration of stochastic differential equations. We prove some convergence results for the proposed method including its first mean-square order. Results of numerical experiments on two model problems are presented. Elsevier 2016-08-15 Article PeerReviewed Milstein, G.N. and Tretyakov, M.V. (2016) Layer methods for stochastic Navier–Stokes equations using simplest characteristics. Journal of Computational and Applied Mathematics, 302 . pp. 1-23. ISSN 1879-1778 Navier-Stokes Equations Oseen-Stokes Equations Helmholtz-Hodge-Leray Decomposition Stochastic Partial Differential Equations Conditional Feynman-Kac Formula Weak Approximation of Stochastic Differential Equations and Layer Mathods http://www.sciencedirect.com/science/article/pii/S0377042716300310 doi:10.1016/j.cam.2016.01.051 doi:10.1016/j.cam.2016.01.051
spellingShingle Navier-Stokes Equations
Oseen-Stokes Equations
Helmholtz-Hodge-Leray Decomposition
Stochastic Partial Differential Equations
Conditional Feynman-Kac Formula
Weak Approximation of Stochastic Differential Equations and Layer Mathods
Milstein, G.N.
Tretyakov, M.V.
Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title_full Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title_fullStr Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title_full_unstemmed Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title_short Layer methods for stochastic Navier–Stokes equations using simplest characteristics
title_sort layer methods for stochastic navier–stokes equations using simplest characteristics
topic Navier-Stokes Equations
Oseen-Stokes Equations
Helmholtz-Hodge-Leray Decomposition
Stochastic Partial Differential Equations
Conditional Feynman-Kac Formula
Weak Approximation of Stochastic Differential Equations and Layer Mathods
url https://eprints.nottingham.ac.uk/32272/
https://eprints.nottingham.ac.uk/32272/
https://eprints.nottingham.ac.uk/32272/