Efficient stochastic simulation of thermal spray processes

Thermal spray processes allow the production of coatings with a wide variety of useful properties, and therefore are used in a lot of different industrial applications. However, in specific applications, it can be a challenging and time consuming task to tune the parameters of a thermal spraying system so that required surface properties, such as wear- , corrosion- or heat resistance, can be achieved. Computer-aided stochastic simulations of thermal spray processes try to overcome these problems by modelling the coating build-up on a per-droplet basis, and by deriving the properties of interest from the generated structure afterwards. Because of the large number of droplets that need to be treated during the simulation to generate a sufficiently large virtual coating, the use of efficient algorithms is essential. On the other hand more complex algorithms are needed to increase the accuracy of the simulation. s report we present novel extensions to a simulation model by Ghafouri et al. concerning plasma spraying. The extensions include a physically inspired splat spreading approach, a method to generate splat fingers, and a filtering technique that allows for the calculation of pores below overlapping splats. Furthermore, features characterizing coatings beyond the commonly used porosity or surface roughness are presented and analyzed with respect to their appropriateness. Features are considered appropriate if they are depending in a unique way on the parameters of the simulation model. This kind of features might be used in an automatic adaptation of the simulation model to real processes. Finally, several contributions are made in order to increasing the computational efficiency of the simulation. Most important, dexel models are introduced to represent the coating.