Materials Microstructure Design Integrated with Image-Based Simulation

Digital material design increasingly relies on statistical digital twins to accelerate material development and optimize performance. In this presentation, Nelly Nunheim-Pape demonstrates an image based workflow combining X ray computed tomography, AI driven microstructure analysis, and GeoDict simulations to create statistical digital twins of fiber reinforced polymer composites. By varying parameters such as fiber orientation, solid volume fraction, and porosity, the influence on mechanical properties can be predicted without extensive physical testing. This approach enables rapid virtual parameter studies that reduce development time and support data driven material optimization.