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Journal Articles Journal of Computational Physics Year : 2023

Well-Posedness and Variational Numerical Scheme for an Adaptive Model in Highly Heterogeneous Porous Media

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Abstract

Mathematical modeling of fluid flow in a porous medium is usually described by a continuity equation and a chosen constitutive law. The latter, depending on the problem at hand, may be a nonlinear relation between the fluid's pressure gradient and velocity. The actual shape of this relation is normally chosen at the outset of the problem, even though, in practice, the fluid may experience velocities outside of its range of applicability. We propose here an adaptive model, so that the most appropriate law is locally selected depending on the computed velocity. From the analytical point of view, we show well-posedness of the problem when the law is monotone in velocity and show existence in one space dimension otherwise. From the computational point of view, we present a new approach based on regularizing via mollification the underlying dissipation, i.e., the power lost by the fluid to the porous medium through drag. The resulting regularization is shown to converge to the original problem using Γ-convergence on the dissipation in the monotone case. This approach gives rise to a variational numerical scheme which applies to very general problems and which we validate on three test cases.
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hal-03945325 , version 1 (18-01-2023)

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Alessio Fumagalli, Francesco Saverio Patacchini. Well-Posedness and Variational Numerical Scheme for an Adaptive Model in Highly Heterogeneous Porous Media. Journal of Computational Physics, 2023, 475, pp.111844. ⟨10.1016/j.jcp.2022.111844⟩. ⟨hal-03945325⟩

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