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Main Authors: Chen, Ping, Pan, Tianyi, Zhang, Tusheng
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.13468
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author Chen, Ping
Pan, Tianyi
Zhang, Tusheng
author_facet Chen, Ping
Pan, Tianyi
Zhang, Tusheng
contents In this paper, we establish the strong($H^1$) well-posedness of the two dimensional stochastic Navier-Stokes equation with multiplicative noise on moving domains. Due to the nonlocality effect, this equation exhibits a ``piecewise" variational setting. Namely the global well-posedness of this equation is decomposed into the well-posedness of a family of stochastic partial differential equations(SPDEs) in the variational setting on each small time-interval. We first examine the well-posedness on each time interval, which does not have (nonhomogeneous) coercivity. Subsequently, we give an estimate of lower bound of length of the time-interval, which enables us to achieve the global well-posedness.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13468
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Strong well-posedness of the two-dimensional stochastic Navier-Stokes equation on moving domains
Chen, Ping
Pan, Tianyi
Zhang, Tusheng
Probability
Analysis of PDEs
35R37, 60H15
In this paper, we establish the strong($H^1$) well-posedness of the two dimensional stochastic Navier-Stokes equation with multiplicative noise on moving domains. Due to the nonlocality effect, this equation exhibits a ``piecewise" variational setting. Namely the global well-posedness of this equation is decomposed into the well-posedness of a family of stochastic partial differential equations(SPDEs) in the variational setting on each small time-interval. We first examine the well-posedness on each time interval, which does not have (nonhomogeneous) coercivity. Subsequently, we give an estimate of lower bound of length of the time-interval, which enables us to achieve the global well-posedness.
title Strong well-posedness of the two-dimensional stochastic Navier-Stokes equation on moving domains
topic Probability
Analysis of PDEs
35R37, 60H15
url https://arxiv.org/abs/2504.13468