Development of Engineering Metal-Metal Composites for Controlled Shear Deformation under High-Strain Rate Compression.

We explore the dynamic deformation mechanisms in metal-metal composites subjected to high strain-rate compression utilizing Split Hopkinson Pressure Bar (SHPB) techniques. We emphasize the design and fabrication of mesoscale structures specifically engineered to induce controlled shear deformation, employing advanced computational design methods to optimize the composite's response. Our investigation combines numerical simulations with experimental validations, using the Johnson-Cook (JC) constitutive model to compare the predicted structural behavior with the actual responses observed in physical systems. Parameter fitting is conducted through monolithic experiments on individual composite constituents, sought to enhance our predictive capability. A novel print-cast fabrication method is introduced for manufacturing composite structures from 316 Stainless Steel and Aluminium 356. This technique facilitates manufacturing complex intrinsic structures, which in turn influence macroscopic deformation behavior. By utilizing computational design and numerical analysis of structures, we can streamline the production process and reduce the number of candidate structures. This method allows for precise manipulation of mechanical properties. Furthermore, the project outlines a small-lab FAIR data methodology designed to support finite element analysis (FEA) and machine learning (ML) applications, thereby promoting data-driven insights and enhancing the robustness of strength models. By integrating experimental, computational, and data-driven approaches, we propose a new systemic framework to gain insight into shear deformation mechanisms under conditions of high-strain loading.