Open PhD position: “Efficient computational platform on grain structure induced anisotropic behaviour in selective laser melting (SLM)”

In the team of Metallurgy, Mechanics, Structures & Solidification (2MS) at CEMEF, SLM simulation models at particle, meso and macro scales have been developed. These models have been extended for direct energy deposition and wire arc additive manufacturing process for academic and industrial projects. Recently, with the possibility to print single crystal, it shows the necessity to control the desired grain orientation and the induced anisotropic mechanical response by the numerical model at part scale.

The goal of this project ECOGRAM is to develop an efficient numerical platform for optimizing the selective laser melting (SLM) process by coupling the grain growth and its anisotropic mechanical behaviour at part scale. The macro-scale numerical model considering the non-exposed powder has been originally developed within the framework of finite element (FE) method and level-set formulation [1]: see figure hereunder for thermomechanical analysis. To generate the grain structure during the construction process, the Cellular Automaton – Finite Element (CAFE) method [2] will be adopted in this project.

The main research works focus on:
– Coupling the SLM macro-scale model with CAFE approach to predict the grain structure growth.
– Applying the anisotropic elasto-visco-plastic laws for different grain structures in case of mechanical analysis.
– Validating the generated grain structure and mechanical response by measured microstructure, distortion and residual stresses.
– Adapting the inherent strain method and reduced order model to the mechanical analysis.
– Optimizing the desired grain structure to build a close loop from process parameters to anisotropic mechanical responses.
All the numerical simulation will be performed within the C++ library CimLib® developed in the laboratory. The PhD student needs to adapt and extend the existed numerical developments in this library and specifically its application to additive manufacturing simulation.