Development of advanced material modelling for metal additive manufacturing

Abstract

Additive manufacturing (AM) is becoming an increasingly popular manufacturing process due to its design freedoms and material efficiency. However, the use of AM in industry is limited by the reliability of the deposited parts. Process-microstructure-property relationships are of paramount importance to increasing understanding and consistency within additive processes. Within this work, thermal and microstructure modelling methods are investigated to develop an efficient approach to the simulation of solidification microstructure. Finite element thermal models are considered as well as the implementation of analytical solutions. Cellular automata methods are used to simulate grain growth, 2D models are implemented for computational efficiency. The established approach is applied to three case studies within this work. The first is the application to laser scans on a bare nickel superalloy substrate, followed by the application to direct energy deposition techniques. Within the second study the capability of the modelling approach to capture changes in microstructure as a result of a change in process parameters is investigated. Finally, the modelling approach is applied to functionally graded materials through in situ changes in process parameters.