Additive Manufacturing Simulator (AMS)

Metal additive manufacturing (AM) processes are in general very complex, because of the large energy input of the heat source and the complete melting of particles, problems like balling, residual stress and deformation occur. These process parameters not only vary from material to material, but may vary locally within a single part to attain the desired part shape. Physics-based modeling tool will be a very useful tool for assessing the impact of process parameters and predicting optimized conditions in the deposition process. However, the physics based AM models generally require a lot of computational power since they generally involve multi-physics such as heat transfer, fluid dynamics, and solid mechanics, etc. This proposed SBIR project will leverage the funded project experiences from the Air Force, NASA, NSF, and many manufacturing companies to provide a scalable and predictive modeling tool. During modelling, the most time consuming task is to compute the physics regarding solid-fluid transformation in the melt pool. The proposed method works by dividing the fluid into a set of discrete elements, referred to as particles. Since this approach will be based on particles, it can use algorithms which are highly adaptable to parallel computing and hence can achieve real time simulations in less computation time. The proposed HPC (High Performance Computing) simulation modeling systems framework will target high performance parallel simulation. It will be based on a three-tier client server architecture, client, management, and server, coupled with service oriented architecture’s subscription and publication model. In Phase I, Product Innovation and Engineering will demonstrate the feasibility of developing high performance AMS. The objectives are to implement AMS in a client-manager-server architecture for HPC, and to validate the efficiency and effectiveness of the HPC-based AMS prototype. A full scale HPC based AMS for AM processes, will be implemented in Phase II. The project will develop a powerful additive manufacturing process modeling tool to transform US additive manufacturing industry, thus will place US AM industry in the world leading position. Commercial Applications and Other Benefits: The success of this project will provide a powerful predictive modeling tool for AM processes. It will enable process parameter optimization, advanced materials fabrication, and AM process qualification. It will directly impact many industries, such as gas turbine manufacturers, automotive, aerospace, heavy machine manufacturers.