Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
SIAM Review
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
The Definitive Guide to ImageMagick (Definitive Guide)
The Definitive Guide to ImageMagick (Definitive Guide)
Mesh Generation: Application to Finite Elements
Mesh Generation: Application to Finite Elements
On Smoothing Surfaces in Voxel Based Finite Element Analysis of Trabecular Bone
Large-Scale Scientific Computing
Computer Methods and Programs in Biomedicine
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In material science, images are increasingly used as input data for computational models. In most of the published papers, voxel-based finite element models are employed using a mesh that is automatically built by converting each voxel into a finite element. We have recently proposed (Legrain et al., Int J Numer Methods Eng 86(7): 915---934, 2011) another computational approach for incorporating images in models, based on the extended finite element method (X-FEM) and levelsets. Its main advantages are that the mesh does not need to conform to the geometry and that a smooth representation of physical surfaces is obtained. The aim of this paper is to compare the two approaches in the framework of computational homogenization in elasticity, starting from material microstructural images. Attention will be paid to geometrical approximations, macroscopic properties and local quantities (e.g. stress oscillations, local error etc.). It is shown that the X-FEM/levelset approach is more efficient than voxel-based FEM.