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Pierre Kerfriden
Researcher at Cardiff University
Publications - 17
Citations - 1722
Pierre Kerfriden is an academic researcher from Cardiff University. The author has contributed to research in topics: Domain decomposition methods & Model order reduction. The author has an hindex of 14, co-authored 17 publications receiving 1378 citations. Previous affiliations of Pierre Kerfriden include UniverSud Paris.
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A computational library for multiscale modeling of material failure
TL;DR: PerMIX is an object oriented open-source effort written primarily in Fortran 2003 standard with Fortran/C++ interfaces to a number of other libraries such as LAMMPS, ABAQUS, LS-DYNA and GMSH for multiscale modeling and simulation of fracture in solids.
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Extended finite element method with edge-based strain smoothing (ESm-XFEM) for linear elastic crack growth
TL;DR: In this article, a strain smoothing procedure for the extended finite element method (XFEM) is presented, which is tailored to linear elastic fracture mechanics and, in this context, to outperform the standard XFEM.
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Nitsche's method for two and three dimensional NURBS patch coupling
TL;DR: In this paper, a Nitche's method is used to couple non-conforming two and three-dimensional non-uniform rational b-splines (NURBS) patches in the context of isogeometric analysis.
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Real-time simulation of contact and cutting of heterogeneous soft-tissues
Hadrien Courtecuisse,Hadrien Courtecuisse,Hadrien Courtecuisse,Jérémie Allard,Pierre Kerfriden,Stéphane Bordas,Stéphane Cotin,Christian Duriez +7 more
TL;DR: A numerical method for interactive (real-time) simulations, which considerably improves the accuracy of the response of heterogeneous soft-tissue models undergoing contact, cutting and other topological changes is presented.
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Bridging proper orthogonal decomposition methods and augmented Newton–Krylov algorithms: An adaptive model order reduction for highly nonlinear mechanical problems
TL;DR: A bridge between POD-based model order reduction techniques and the classical Newton/Krylov solvers is described, used to derive an efficient algorithm to correct, "on-the-fly", the reduced order modelling of highly nonlinear problems undergoing strong topological changes.