GOALI: Novel Surface Engineering Methodology to Anneal the Surface Defects Generated During Grinding Operation for Silicon Nitride Ceramic Components for Heavy Duty Equipment

点击翻译按钮获取中文摘要

This Grant Opportunities for Academic Liaison with Industry (GOALI) award provides funding for the development of a numerical tool for determining optimal process parameters in bulk forming processes, such as rolling, extrusion, and forging. The developed numerical tool will determine the optimal process geometry, temperature and speed that satisfy specified design criteria for a given two- dimensional forming process. An optimization algorithm based on an adaptive arbitrary Lagrangian-Eulerian finite element formulation for modeling large deformation thermo-elasto-viscoplastic contact problems used. The algorithm will be implemented in the context of an existing advanced computational framework that has tools for mesh generation, adaptivity, and parallel computing. Experiments involving the extrusion process will also be performed to validate the algorithms developed. Experimental dies will be manufactured according to the optimal die shapes predicted in this work and tested at the predicted optimal die speeds. A model press, which can extrude plasticine material marked with grid, will be used in these experiments to observe the material flow behavior.If successful, the results of this research will lead to improvements in the design of bulk forming processes and new developments in optimization methods for handling complex nonlinear problems. The primary goal of this work is to determine optimal process geometry, thermal conditions, and process speed in bulk forming processes that will satisfy typically prescribed design criteria. These design criteria may include generating a uniform flow of the material, generating a specified material property distribution in the formatted product, minimizing the production time, or minimizing the energy required for the process. Determining the process parameters to achieve these objectives will help to reduce the cost and improve the quality of the final product in processes such as extrusion and forging. The proposed work will also contribute to the computational tools and methodologies available for nonlinearoptimization problems.