Modeling and Simulation of Additive Manufacturing

Representative publications:

Journal:

Qian Ye and Shikui Chen*, “Numerical Modeling of Metal-Based Additive Manufacturing Process Using Level Set Methods”, ASME Journal of Manufacturing Science and Engineering , 10.1115/1.4036226.

Conference:

Qian Ye and Shikui Chen*, “Numerical Modeling of Metal-Based Additive Manufacturing Process Using Level Set Methods”, Proceedings of the 2017 Manufacturing Science and Engineering Conference (MSEC2017), June 4 - 8, 2017, Los Angeles, California, USA.

Ye, Qian, Shikui Chen and Qing Chang , “Metal-based additive manufacturing: A literature review on modeling, simulation and energy consumption”, 2015 IEEE International Conference on Automation Science and Engineering (CASE). IEEE, 2015.

Recent years have witnessed the swift growth of metal-based additive manufacturing (AM) technologies from rapid prototype fabrication to direct digital manufacturing (DDM) of the end-use product, which provides a great opportunity to establish AM as a mainstream manufacturing process. While the future is bright, two technical hurdles remain. One is how to thoroughly understand the AM process, the other is how to efficiently optimize the AM design.  Modern computation technology enables people to study AM technologies at high fidelity, which has proven to be an effective way to analyze, predict, and design the AM processes. General methods for AM process simulation include the Finite Element Methods (FEM), Lattice Boltzmann Method (LBM) and Molecular Dynamics (MD). The three methods simulate the underlying physics at different scales and have their strength and limitations. In our work, a new method is proposed to simulate the melting process of Titanium alloy powder based AM. The physics are modeled by conservation equations of heat transfer and Laminar Flow. The free surface between liquid and solid phases (L/G) is tracked by the level set method.