activity
20162022
most citedContainers for portable, productive and performant scientific computing

46 citations · 58 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MS2022★ 2 cited

SOniCS: Develop intuition on biomechanical systems through interactive error controlled simulations

Arnaud Mazier, Sidaty El Hadramy, Jean-Nicolas Brunet +3

This new approach allows the user to experiment with model choices easily and quickly without requiring in-depth expertise, as constitutive models can be modified by one line of co…

math.NA2022★ 4 cited

An a posteriori error estimator for the spectral fractional power of the Laplacian

Raphaël Bulle, Olga Barrera, Stéphane P. A. Bordas +2

We develop a novel a posteriori error estimator for the error committed by the finite element discretization of the solution of the fractional Laplacian. Our a posteriori err…

cs.CE2021★ 3 cited

Inverse deformation analysis: an experimental and numerical assessment using the FEniCS Project

Arnaud Mazier, Alexandre Bilger, Antonio E. Forte +25

In this paper, we develop a framework for solving inverse deformation problems using the FEniCS Project finite element software. We validate our approach with experimental imaging…

math.NA2021

Hierarchical a posteriori error estimation of Bank-Weiser type in the FEniCS Project

Raphaël Bulle, Jack S. Hale, Alexei Lozinski +2

In the seminal paper of Bank and Weiser [Math. Comp., 44 (1985), pp.283-301] a new a posteriori estimator was introduced. This estimator requires the solution of a local Neumann pr…

cs.DC2016★ 46 cited

Containers for portable, productive and performant scientific computing

Jack S. Hale, Lizao Li, Chris N. Richardson +1

Containers are an emerging technology that hold promise for improving productivity and code portability in scientific computing. We examine Linux container technology for the distr…

cs.CE2016★ 3 cited

Bayesian inference for the stochastic identification of elastoplastic material parameters: Introduction, misconceptions and insights

Hussein Rappel, Lars A. A. Beex, Jack S. Hale +1

We discuss Bayesian inference (BI) for the probabilistic identification of material parameters. This contribution aims to shed light on the use of BI for the identification of elas…