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Numerical Analysis of Stochastic Elliptic Variational Inequalities of the First Kind
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Numerical Analysis of Stochastic Elliptic Variational Inequalities of the First Kind

Chenhui Zhu, Fei Wang and Weimin Han
ArXiv.org
Cornell University
04/28/2026
DOI: 10.48550/arxiv.2604.25111
url
https://doi.org/10.48550/arxiv.2604.25111View
Preprint (Author's original) This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

This paper presents a numerical approach to the stochastic obstacle problem using the stochastic Galerkin (SG) method. Due to the low regularity of the solution, linear finite elements are employed in both the physical and random variable spaces. Properties of random fields and variational inequalities of the first kind are employed to establish the well-posedness of the problem. Finite element spaces are introduced to construct suitable approximation subspaces, and a comprehensive SG formulation is proposed to solve the stochastic obstacle problem. Well-posedness of the discrete formulation is shown and an optimal error estimate for the numerical solution in theH¹ -norm is derived. Numerical experiments validate the effectiveness of the SG method, showing that both the expectation error and second moment error converge at a rate ofO(h)in theH¹ -norm, consistent with theoretical predictions.
Computer Science - Numerical Analysis Mathematics - Numerical Analysis

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