Uniform-in-time convergence of numerical methods for non-linear degenerate parabolic equations
Gradient schemes is a framework that enables the unified convergence analysis of many
numerical methods for elliptic and parabolic partial differential equations: conforming and
non-conforming finite element, mixed finite element and finite volume methods. We show
here that this framework can be applied to a family of degenerate non-linear parabolic
equations (which contain in particular the Richards', Stefan's and Leray–Lions' models), and
we prove a uniform-in-time strong-in-space convergence result for the gradient scheme …
numerical methods for elliptic and parabolic partial differential equations: conforming and
non-conforming finite element, mixed finite element and finite volume methods. We show
here that this framework can be applied to a family of degenerate non-linear parabolic
equations (which contain in particular the Richards', Stefan's and Leray–Lions' models), and
we prove a uniform-in-time strong-in-space convergence result for the gradient scheme …
Abstract
Gradient schemes is a framework that enables the unified convergence analysis of many numerical methods for elliptic and parabolic partial differential equations: conforming and non-conforming finite element, mixed finite element and finite volume methods. We show here that this framework can be applied to a family of degenerate non-linear parabolic equations (which contain in particular the Richards’, Stefan’s and Leray–Lions’ models), and we prove a uniform-in-time strong-in-space convergence result for the gradient scheme approximations of these equations. In order to establish this convergence, we develop several discrete compactness tools for numerical approximations of parabolic models, including a discontinuous Ascoli–Arzelà theorem and a uniform-in-time weak-in-space discrete Aubin–Simon theorem. The model’s degeneracies, which occur both in the time and space derivatives, also requires us to develop a discrete compensated compactness result.
Springer
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