Regina Ammer

Universität Erlangen-Nürnberg, Department of Computer Science, Germany



Electron beam melting (EBM) is an additive manufacturing method used to produce complex metallic structures layer by layer from metal powder. EBM opens many new opportunities in many industries, ranging from aircraft manufacturers to producers of medical implants.

However, until now the parts cannot be manufactured at sufficient speed to make them economically viable for any but specific very high value applications. In order to accelerate the building process and improve the accuracy a better understanding of the beam-powder interaction is necessary. This can be gained by three-dimensional (3D) simulations of the process.

It has already been shown that a 2D thermal free surface lattice Boltzmann (LB) model can be used for the numerical discretization of EBM simulations. Because of stability reasons a multi-distribution LB approach is used instead of a multi-speed approach for simulating hydrodynamic effects, like melt flow, capillarity and wetting, as well as thermal effects, like beam absorption, melting and solidification.

We have extended this successful method to a thermal 3D free surface LB implementation. A careful parallelization and optimization is necessary because of the high computational costs of 3D simulations.

Our validation experiments deal first with fundamental examples like the melting of a single spot where we validate the numerical results against real experimental data.

In this and more complex example scenarios we validate characteristic features such as the size, temperature, and surface structure of the melt pool, including its dynamical behavior, and the values of the heat-affected zone.

Experimental and numerical results are in good agreement such that we can proceed to model, simulate and validate even more complex structures (e.g. the melting of a hatch). These simulations require the use of advanced supercomputing resources.

These numerical results demonstrate the good potential of the LB approach to understand and  predict  complex processes like the EBM depending on thermodynamic as well as on  fluid dynamic phenomena.