Colloquia

Summary

Constitutive micromechanical models based on Crystal Plasticity methods have become increasingly used to predict material performance under complex loading conditions and manufacturing processes. It is a functional tool for product optimization, performance, and failure prediction that could eventually reduce the need for strenuous experimental measurements, with benefits from the point of view of time and costs. With advances in computational efficiency, such models also aid in gaining a more fundamental understanding of the effects microstructural parameters have on the overall macroscopic behavior, allowing for possible developments of new and improved products that account for material-induced limitations.

Moreover, modeling such a response is important for the entire lifetime of the material. With new regulations on CO2 emissions, there is an increased demand to make the steel industry sustainable. There is a focused effort to increase the content of recycled/scrap metal and DRI (direct reduced iron) used in the raw material. Crystal plasticity models could become an essential link in understanding and predicting the effects these changes have on the microstructure and mechanical properties.

Limiting the scope to metals and alloys, microscopic inhomogeneities of polycrystalline materials, such as grain orientation and size distribution, affect macroscopic plastic behavior. The goal of this thesis is to validate and test the capabilities of the current Crystal Plasticity and Gradient Enhanced Crystal Plasticity frameworks developed within the Nonlinear Solid Mechanics chair. The evolution of plastic deformation of heterogeneous crystallographic structures is investigated for a periodic 3D Representative Volume Element (RVE).  The influence of grain size and grain shape on the performance of the RVE is tested by varying grain size distribution and grain aspect ratio. The response of both models is compared, focusing on the effect strain gradient computation has on the behavior.