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Research Article | Open Access

A fully discrete HDG ensemble Monte Carlo algorithm for a heat equation under uncertainty

JinJun Yong1,2Changlun Ye3Xianbing Luo1( )
School of Mathematics and Statistics, Guizhou University, Guiyang, 550025, China
School of Mathematics and Big Data, Guizhou Key Laboratory of Artificial Intelligence and Brain-inspired Computing, Guizhou Education University, Guiyang, 550018, China
School of Mathematical Sciences, Guizhou Normal University, Guiyang, 550001, China
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Abstract

This paper has introduced a novel fully discrete hybridizable discontinuous Galerkin (HDG) ensemble Monte Carlo method (FEMC-HDG) tailored for solving the heat equation with random diffusion and Robin coefficients. The FEMC-HDG method solves a single linear system with multiple right-hand side vectors per time step. We established stability analysis and error estimates that are optimal in the spatial and first-order accuracy in time for the L ( 0 , T , L 2 ( D ) )-norm error estimate. Numerical experiments were included to confirm the theoretical convergence and showcase the method's efficiency.

CLC number: 65C05, 65C20, 65M60

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Networks and Heterogeneous Media
Pages 65-88

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Cite this article:
Yong J, Ye C, Luo X. A fully discrete HDG ensemble Monte Carlo algorithm for a heat equation under uncertainty. Networks and Heterogeneous Media, 2025, 20(1): 65-88. https://doi.org/10.3934/nhm.2025005

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Received: 09 October 2024
Revised: 02 January 2025
Accepted: 13 January 2025
Published: 15 February 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)