Zhang Z-Q, Guo J, Msolli S, et al (2019) Virtual Platform for Cold Spray Additive Manufacturing Process with an Integrated Multiphysics Multiscale Computational Model. In: Processing and Fabrication of Advanced Materials ( (PFAM-XXVII))
Abstract:
A virtual platform for metal Cold Spray (CS) Additive Manufacturing process has been developed to predict with high fidelity the optimal process parameters and the coating properties under different process parameters. The validated and integrated multiphysics, multiscale computational model forms the core of the present virtual platform and consists of: (1) a multiphase CFD model for supersonic gas flow characterising the trajectory of the powder particles in the Cold Spray system; (2) a mesoscale FEM model to simulate bonding for single particle impact (3) and a continuum scale FEM model for coating build-up by considering multi particle-substrate impact events and computing the effective stress, strain, and temperature evolution during the build. The model has been validated with experimental data for different material systems, and successfully employed to guide the manufacturing process by providing guidelines for optimal process parameters including gas pressure, gas pre-heat temperature, and the powder mass flow rate. Besides validating the prediction of the virtual platform, the experimental data serve as key inputs to the machine learning toolbox.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Machining Learning Assisted Control of Metal Cold Spray and Shot Peening Processes
Grant Reference no. : A1894a0032