2007
DOI: 10.1002/nme.2036
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Numerical comparison of some Hessian recovery techniques

Abstract: SUMMARYDerivative recovery techniques are used in a posteriori error indicators to drive mesh adaptation. Their behaviour in the core of the computational domain and on boundaries constitutes an important efficiency factor for a subsequent mesh adaptation process. A methodology to compare recovery techniques for second-order derivatives from a piecewise linear approximation is presented in this paper. A systematic approach to measuring the performance of recovery techniques using analytical functions interpola… Show more

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Cited by 59 publications
(47 citation statements)
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References 23 publications
(46 reference statements)
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“…Thus, it is necessary to recover a discrete approximation to the true Hessian. Different recovery schemes such as quadratic fitting (Vallet et al 2007), superconvergent patch recovery (Zienkiewicz & Zhu 1992), integration by parts (Buscaglia & Dari 1997) and double Galerkin projection (Pain et al 2001) have been suggested. These schemes vary in cost, accuracy and robustness; a number of comparisons of Hessian recovery schemes have recently been published (e.g.…”
Section: (E) Hessian Recoverymentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, it is necessary to recover a discrete approximation to the true Hessian. Different recovery schemes such as quadratic fitting (Vallet et al 2007), superconvergent patch recovery (Zienkiewicz & Zhu 1992), integration by parts (Buscaglia & Dari 1997) and double Galerkin projection (Pain et al 2001) have been suggested. These schemes vary in cost, accuracy and robustness; a number of comparisons of Hessian recovery schemes have recently been published (e.g.…”
Section: (E) Hessian Recoverymentioning
confidence: 99%
“…These schemes vary in cost, accuracy and robustness; a number of comparisons of Hessian recovery schemes have recently been published (e.g. Lipnikov & Vassilevski 2006;Vallet et al 2007). Here, the double Galerkin projection approach described in Pain et al (2001) is used.…”
Section: (E) Hessian Recoverymentioning
confidence: 99%
“…Two different strategies can be devised to further enhance accuracy of the transverse normal stress and guarantee its convergence in any case (see the paper by Vallet et al (2007) for some details on Hessian recovery techniques). The first strategy is to apply a second superconvergent recovery procedure, inspired by the RCP procedure, to improve transverse shear stresses before reconstructing the transverse normal stress using threedimensional equilibrium.…”
Section: Reconstruction Of the Transverse Normal Stressmentioning
confidence: 99%
“…with h max and h min as the maximum and minimum allowed edge size in the mesh and the Hessian matrix is evaluated by a double projection scheme using a weak formulation [19].…”
Section: Metric Estimatesmentioning
confidence: 99%