Error Estimates of Finite Element Methods for the Nonlinear Backward Stochastic Stokes Equations

This paper is concerned with the numerical analyses of finite element methods for the nonlinear backward stochastic Stokes equations (BSSEs) where the forcing term is coupled with $z.$ Under several developed analysis techniques, the error estimates of the proposed semi-discrete and fully discrete schemes, as well as their boundedness, are rigorously presented and established. Optimal convergence rates of the fully discrete scheme are obtained not only for the velocity $u$ and auxiliary stochastic process $z$ but also for the pressure $p.$ For the efficiency of solving BSSEs, the proposed numerical scheme is parallelly designed in stochastic space. Numerical results are finally provided and tested in parallel to validate the theoretical results.

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Publication Details

Journal
CSIAM Transactions on Applied Mathematics
Published
2024-11-20
DOI
https://doi.org/10.4208/csiam-am.so-2024-0021
Citations
1
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
0.46
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article

Error Estimates of Finite Element Methods for the Nonlinear Backward Stochastic Stokes Equations

Yongwang Sun, Weidong Zhao and Wenju Zhao
1 citations
CSIAM Transactions on Applied Mathematics
Probabilistic and Robust Engineering Design
0.46
article

Error Estimates of Finite Element Methods for the Nonlinear Backward Stochastic Stokes Equations

Yongwang Sun, Weidong Zhao and Wenju Zhao
article en
1 citations

Abstract

This paper is concerned with the numerical analyses of finite element methods for the nonlinear backward stochastic Stokes equations (BSSEs) where the forcing term is coupled with $z.$ Under several developed analysis techniques, the error estimates of the proposed semi-discrete and fully discrete schemes, as well as their boundedness, are rigorously presented and established. Optimal convergence rates of the fully discrete scheme are obtained not only for the velocity $u$ and auxiliary stochastic process $z$ but also for the pressure $p.$ For the efficiency of solving BSSEs, the proposed numerical scheme is parallelly designed in stochastic space. Numerical results are finally provided and tested in parallel to validate the theoretical results.

CSIAM Transactions on Applied MathematicsVol. 6(1)
Shandong University (CN), University of Jinan (CN)
Openalex Percentile: Top 27%
Probabilistic and Robust Engineering Design
0.46
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