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Numerical Methods for Approximating Stochastic Semilinear Time-Fractional Rayleigh-Stokes Equations

Numerical Methods for Approximating Stochastic Semilinear Time-Fractional Rayleigh-Stokes Equations

Year:    2025

Author:    Mariam Al-Maskari

Journal of Computational Mathematics, Vol. 43 (2025), Iss. 3 : pp. 569–587

Abstract

This paper investigates a semilinear stochastic fractional Rayleigh-Stokes equation featuring a Riemann-Liouville fractional derivative of order $α ∈ (0, 1)$ in time and a fractional time-integral noise. The study begins with an examination of the solution’s existence, uniqueness, and regularity. The spatial discretization is then carried out using a finite element method, and the error estimate is analyzed. A convolution quadrature method generated by the backward Euler method is employed for the time discretization resulting in a fully discrete scheme. The error estimate for the fully discrete solution is considered based on the regularity of the solution, and a strong convergence rate is established. The paper concludes with numerical tests to validate the theoretical findings.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.2311-m2023-0047

Journal of Computational Mathematics, Vol. 43 (2025), Iss. 3 : pp. 569–587

Published online:    2025-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    19

Keywords:    Riemann-Liouville fractional derivative Stochastic Rayleigh-Stokes equation Finite element method Convolution quadrature Error estimates.

Author Details

Mariam Al-Maskari