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Preprints, Working Papers, ... Year : 2023

Robust augmented energy a posteriori estimates for Lipschitz and strongly monotone elliptic problems

Abstract

In this paper, we design a posteriori estimates for finite element approximations of nonlinear elliptic problems satisfying strong-monotonicity and Lipschitz-continuity properties. These estimates include, and build on, any iterative linearization method that satisfies a few clearly identified assumptions; this encompasses the Picard, Newton, and Zarantonello linearizations. The estimates give a guaranteed upper bound on an augmented energy difference (reliability with constant one), as well as a lower bound (efficiency up to a generic constant). We prove that for the Zarantonello linearization, this generic constant only depends on the space dimension, the mesh shape regularity, and possibly the approximation polynomial degree in four or more space dimensions, making the estimates robust with respect to the strength of the nonlinearity. For the other linearizations, there is only a computable dependence on the local variation of the linearization operators. We also derive similar estimates for the usual energy difference that depend locally on the nonlinearity and improve the established bound. Numerical experiments illustrate and validate the theoretical results, for both smooth and singular solutions.
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Dates and versions

hal-04033438 , version 1 (17-03-2023)
hal-04033438 , version 2 (26-05-2023)
hal-04033438 , version 3 (10-06-2024)

Identifiers

  • HAL Id : hal-04033438 , version 3

Cite

André Harnist, Koondanibha Mitra, Ari Rappaport, Martin Vohralík. Robust augmented energy a posteriori estimates for Lipschitz and strongly monotone elliptic problems. 2024. ⟨hal-04033438v3⟩
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