Stochastic and analytical methods from image processing for the characterization of local mechanical properties of multiphase metallic materials
The main aim of the project is to develop stochastic and analytical methods to characterize the local mechanical properties of multiphase metallic materials by digital image processing. The test material is an aluminum matrix composite with SiC particle reinforcement and the digital image correlation is based on modern mathematical methods of image processing. In addition to the experimental characterization of local mechanical properties, we will also be quantifying anisotropic deformation behavior using digital image correlation. In the current research phase, the focus is on analysing the influence of the grain structure of the metallic matrix on the local damage behavior of the investigated composite materials.
The project is being carried out in cooperation with the Department of Mathematics (Professor Gabriele Steidl and Professor Claudia Redenbach) Technical University Kaiserslautern. We are grateful for the support of the German Research Foundation (DFG), provided as part of the Research Training Group 1932 (subproject 3).