Numerical algorithms in material science

  • Sylvie Aubry | Stanford University

The talk will consist of two parts. In the first part, I will present prior work aimed at developing new algorithms for materials science applications. I developed a novel numerical method to optimize the shape of mechanical parts and maximize their strength. This optimization problem was extremely challenging as it involved changing the topology and therefore classical optimization methods do not apply. A similar idea can be applied to model shape memory alloys and plasticity in metals. In this project, the optimization led to the construction of a tree of laminated microstructures. Constraints from mechanical equilibrium were used to construct an adaptive tree and to determine the optimal number of levels.

The second part involves more recent work. I will present the implementation of a new heat flux algorithm to understand failures in micro-devices in LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator); LAMMPS is a high performance code which was benchmarked on Blue Gene L with 90% parallel efficiency. Also I am currently extending the capabilities of ParaDiS (Parallel Dislocation Simulator), another high performance code which has run on 135k processors of Blue Gene L.

Speaker Details

Sylvie Aubry got her PhD in applied mathematics at University Pierre and Marie Curie in France in 1999. She did a two years post-doctoral fellowship at Caltech, Pasadena, CA. In 2001, Sylvie became a staff member at Sandia National Laboratories, in Livermore, CA. Since September 2007, She is a research associate at Stanford University. While doing her PhD, she won the Seymour Cray prize in numerical simulation. Dr. Aubry’s interests are in dislocations mechanisms in metals, parallel computing and optimization techniques.

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