A posteriori error estimates for variable time-step discretizations of nonlinear evolution equations †
By Ricardo H. Nochetto, Giuseppe Savar'e, C. Verdi. 2000
188 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computational Theory and Mathematics, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/515cf02fa4839671318bf4db4d0e7248b786bd44
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
In Computational Theory and Mathematics
- Alexander Mielke
- Giuseppe Savar'e
- Riccarda Rossi
- Ulisse Stefanelli
- Luigi Ambrosio
- Xicheng Zhang
- Nicola Gigli
- Gianluca Crippa
In Control and Systems Engineering
- Alexander Mielke
- Riccarda Rossi
- Giuseppe Savar'e
- Ulisse Stefanelli
- Luigi Ambrosio
- Xicheng Zhang
- Gianluca Crippa
- Pierre-Emmanuel Jabin
Citations in the corpus
- Gradient flows and Evolution Variational Inequalities in metric spaces. I: Structural properties (2018, unknown): “In this framework, the link between the limit contraction semigroup (obtained by the convergence of the variational scheme) with the EVIλ-formulation has been clarified by [5], with two further important developments: the optimal error estimate of order 1 (as in Hilbert spaces, [14, 71])”
- WEIGHTED ENERGY-DISSIPATION FUNCTIONALS FOR GRADIENT FLOWS (2011, background): “Let us however mention that, even restricting to the present quite classical setting [Bre73b], relation (1.1) stems in a variety of different applications such as heat conduction, the Stefan problem, the Hele-Shaw cell, porous media, parabolic variational inequalities, some classes of ODEs with obst”
- Gradient flows of non convex functionals in Hilbert spaces and applications (2006, background): “In our case, assuming for simplicity φ ≥ 0, it is possible to prove the uniform Cauchy estimates (see [34])”
- Nonsmooth analysis of doubly nonlinear evolution equations (2011, background): “, [17, 12, 6, 1, 47, 48, 41, 2, 44]), and in general doubly nonlinear equations [16, 15, 52, 51, 36], we approximate (2.”
- Chapter 1 – Gradient Flows of Probability Measures (2007, result): “It extends to the Wasserstein framework previous results: the celebrated Crandall-Liggett [32] generation theorem for nonlinear contraction semigroups in Banach spaces, the optimal error estimates of [14, 82, 69] for gradient flows in Hilbert spaces, the convergence results of [65] in non positively”