Projects per year
Abstract
The article discusses the gradient discretisation method (GDM) for distributed optimal control problems governed by diffusion equation with pure Neumann boundary condition. Using the GDM framework enables to develop an analysis that directly applies to a wide range of numerical schemes, from conforming and non-conforming finite elements, to mixed finite elements, to finite volumes and mimetic finite differences methods. Optimal order error estimates for state, adjoint and control variables for low-order schemes are derived under standard regularity assumptions. A novel projection relation between the optimal control and the adjoint variable allows the proof of a super-convergence result for post-processed control. Numerical experiments performed using a modified active set strategy algorithm for conforming, non-conforming and mimetic finite difference methods confirm the theoretical rates of convergence.
Original language | English |
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Pages (from-to) | 609-637 |
Number of pages | 29 |
Journal | Computational Methods in Applied Mathematics |
Volume | 18 |
Issue number | 4 |
DOIs | |
Publication status | Published - Oct 2018 |
Keywords
- Elliptic Equations
- Error Estimates
- Finite Elements
- GDM
- Mimetic Finite Differences
- Neumann Boundary Conditions
- Optimal Control
- Super-Convergence
Projects
- 1 Finished
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Discrete functional analysis: bridging pure and numerical mathematics
Droniou, J., Eymard, R. & Manzini, G.
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