X-FEM

Nicolas MOES's picture

Post-Doctoral position available on X-FEM for the simulation of fracture in composites

A one year (renewable) post-doc position is avalaible at the Ecole Centrale of Nantes, France.

The research deals with the simulation of complex cracking patterns in composites using

 the eXtended Finite Element method (X-FEM).

 

To apply : a CV + name of at least two references.

 

 


N. Sukumar's picture

Non-planar crack growth (X-FEM and fast marching)

In the attached manuscript, we have coupled the extended finite element
method (X-FEM) to the fast marching method (FMM) for non-planar crack
growth simuations. Unlike the level set method, the FMM is
ideally-suited to advance a monotonically growing front. The FMM is a
single-pass algorithm (no iterations) without any time-step
restrictions. The perturbation crack solutions due to Gao and Rice
(IJF, 1987) and Lai, Movchan and Rodin (IJF, 2002) are used for the
purpose of comparisons. A few of the pertinent cited references can be
found off my X-FEM web page. The final version of the manuscript is now attached.


Post-doctoral position in Computational Stochastic Mechanics, Nantes, France

Post-doctoral position - Stochastic computational techniques to deal with uncertainties on the geometry in structural analysis

The post-doctoral student will join the pole "Structures and Couplings" of the Research Institute en Civil Engineering and Mechanics (GeM), Nantes, France (Nantes University, Ecole Centrale Nantes, CNRS UMR 6183)

We have recently been awarded a Research Project by the French National Research Agency. This project addresses theorical and numerical developments in the field of stochastic computational mechanics. The main goal of this project is to develop a robust computational technique to deal with uncertainties on the geometry in structural analysis. The proposed methodology lies on the extension of the Extended Finite Element Method (X-FEM) into the stochastic framework and the development of efficient computational techniques for solving stochastic systems.


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