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Grégoire Allaire

Researcher at École Polytechnique

Publications -  216
Citations -  14746

Grégoire Allaire is an academic researcher from École Polytechnique. The author has contributed to research in topics: Homogenization (chemistry) & Topology optimization. The author has an hindex of 46, co-authored 204 publications receiving 12849 citations. Previous affiliations of Grégoire Allaire include Chicago Metropolitan Agency for Planning & Pierre-and-Marie-Curie University.

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Homogenization and two-scale convergence

TL;DR: In this article, the authors define a notion of "two-scale" convergence, which is aimed at a better description of sequences of oscillating functions, and prove that bounded sequences in $L^2 (Omega )$ are relatively compact with respect to this new type of convergence.
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Structural optimization using sensitivity analysis and a level-set method

TL;DR: A new numerical method based on a combination of the classical shape derivative and of the level-set method for front propagation, which can easily handle topology changes and is strongly dependent on the initial guess.
Book

Shape optimization by the homogenization method

TL;DR: In this article, a relaxed formulation for shape optimization in the context of shape optimization is presented, where the authors seek minimizers of the sum of the elastic compliance and of the weight of a solid structure under specified loading.
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A level-set method for shape optimization

TL;DR: Although this method is not specifically designed for topology optimization, it can easily handle topology changes for a very large class of objective functions and its cost is moderate since the shape is captured on a fixed Eulerian mesh.
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A five-equation model for the simulation of interfaces between compressible fluids

TL;DR: In this article, a diffuse-interface method is proposed for the simulation of interfaces between compressible fluids with general equations of state, including tabulated laws, and the interface is allowed to diffuse on a small number of computational cells.