AM-CFD: a well-validated thermal-fluid simulator for additive manufacturing part qualification

Z. Gan, K.K. Jones, Y. Lu, X. Xie, S. Saha, S. Mojumder, W.K. Liu
Northwestern University,
United States

Keywords: multiphysics, lack of fusion, thermal-fluid dynamics, materials design


Critical additively manufactured parts for defense, aerospace, and medical applications must be formally qualified prior to use. Currently, extensive empirical testing for part qualification consists of thousands of individual tests, costs millions of dollars and necessitates several years to complete. Furthermore, complex surface topographies, internal defects, and anisotropic properties challenge current state of the art measurement and testing techniques. These challenges hinder the manufacturers’ and users’ ability to benefit from the key advantages of additive manufacturing (AM). To address this need, we have developed an in-house software, called AM-CFD, for AM process simulation and rapid part qualification. Differing from the most commercial software that simulates part scale AM process, AM-CFD focuses on the smaller melt pool scale and thus can accurately capture melt pool geometries and thermal-fluid dynamics, which are critical features for predicting internal defects (e.g., lack-of-fusion porosity), microstructure, and resulting mechanical properties. The AM-CFD can simulate numerous cases in parallel and search for the optimal process condition enabling defect-free additively manufactured parts with fine-grained microstructures and favorable mechanical properties. It also has been extent to multitrack and multilayer AM simulations. To validate the AM-CFD, blind benchmark tests have been independently conducted by National Institute of Standards and Technology (NIST) and Air Force Research Laboratory (AFRL). Our AM-CFD won three 1st place prizes in the NIST AM-Bench (2018) and identified as Top Performer in AFRL AM Modeling Challenge Series (2020). The AM-CFD is very flexible and can be linked with other optimizers for materials design and engineering optimization.