Projects per year
Abstract
The gradient discretization method (GDM) is a generic framework for designing and analyzing numerical schemes for diffusion models. In this paper, we study the GDM for the porous medium equation, including fast diffusion and slow diffusion models, and a concentration dependent diffusion tensor. Using discrete functional analysis techniques, we establish a strong L2-convergence of the approximate gradients and a uniform-in-time convergence for the approximate solution, without assuming nonphysical regularity assumptions on the data or continuous solution. Being established in the generic GDM framework, these results apply to a variety of numerical methods, such as finite volume, (mass-lumped) finite elements, etc. The theoretical results are illustrated, in both fast and slow diffusion regimes, by numerical tests based on two methods that fit the GDM framework: mass-lumped conforming finite elements and the hybrid mimetic mixed method.
Original language | English |
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Pages (from-to) | 1965-1992 |
Number of pages | 28 |
Journal | SIAM Journal on Numerical Analysis |
Volume | 58 |
Issue number | 3 |
DOIs | |
Publication status | Published - 25 Jun 2020 |
Keywords
- Convergence analysis
- Fast-slow diffusion models
- Gradient discretization method
- Numerical methods
- Porous media equations
Projects
- 1 Finished
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Discrete functional analysis: bridging pure and numerical mathematics
Droniou, J. (Primary Chief Investigator (PCI)), Eymard, R. (Partner Investigator (PI)) & Manzini, G. (Partner Investigator (PI))
Australian Research Council (ARC), Monash University, Université Paris-Est Créteil Val de Marne (Paris-East Créteil University Val de Marne), University of California System
1/01/17 → 31/12/20
Project: Research