Integrated Computations Materials Engineering (ICME) Modeling Tool for Optimum Gas Flow in Metal Additive Manufacturing Processes

The objective of proposed research is to demonstrate and validate a prototype of an Integrated Computational Materials Engineering (ICME) predictive modeling tool to fine-tune Gas Flow (G) and associated parameters for Metal Fusion (M) to attain high-quality AM Process-Structure-Performance (PSP). Validate Additive Manufacturing (AM) part quality using Directed Energy Deposition (DED) to repair gas turbine component and utilizing Laser Power Bed Fusion (LPBF) to produce a representative Navy part. The research effort is to: (i) Enhance the precision to model the interaction between non-isothermal gas flow and metal fusion, e.g., for interface heat transfer, powder ricochet, local boiling, ejection, and spatter; (ii) Validate the models for gas flow interaction with metal fusion parameters in DED and LPBF using in-situ, layer-by-layer sensing data and materials characterization. For DED, collect data using a powder flow monitor, laser profilometer, and high-speed video. For LPBF, collect data using a laser profilometer, MWIR camera, and high-speed video. (iii) Optimize PSP for complex repair using DED and produce a representative Navy part using LPBF; (iv) Develop a predictive capability to select a nozzle design for part-specific DED repair; and (v) Train a technology transition partner to use the ICME models.