High Performance Computing in Global DIC for the analysis of large datasets

International audienceThe computational burden associated to finite element based digital image correlation methods is mostly due to the inversion of finite element systems and to image interpolations. A variable separation technique was recently proposed that alleviate mesh constraints. However, in digital volume correlation, the question of the interpolation of the images remains important. For that, a non-overlapping dual domain decomposition method is proposed to rationalize the computational cost of high resolution finite element digital image correlation measurements when dealing with large datasets. It consists in splitting the global mesh into submeshes and the reference and deformed states images into subset images. It will be shown to combine the metrological performances of finite element based digital image correlation and the parallelisation ability of subset based methods