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Description
(Text)
Atmospheric plasma spraying is a versatile technology that can produce coatings with a wide range of characteristics. Adapting the coating characteristics to the increasing demands of modern industrial applications is an ongoing research topic. Modelling and simulation increase the understanding of the process dynamics and have the potential to predict the coating properties. Correlating the coating properties with the process parameters is an essential step for a modelling approach to fulfil this potential. Due to its complexity, it is practically impossible to describe the whole process in a single model. However, based on the nature and the scale of the governing physical phenomena, the plasma spraying process can be divided into constituting sub-processes, which can then be described by separate models. Available models of isolated sub-processes in the literature are not able to derive the coating properties from the process parameters. This thesis is therefore devoted to creating a predictive simulation chain by combining the models of atmospheric plasma spraying sub-processes with each other and thus connecting the coating properties with the process parameters.The simulation chain includes the established models of the sub-processes, models developed in this work to describe previously neglected phenomena and the coupling strategies designed to link separate models together. The existing validated model of the plasma generator was utilized, while the discrete particle jet model was developed further to include the temperature gradients within individual particles. This model assumes perfectly homogenous and spherical particles. To account for realistic particle morphologies, a separate model that can resolve particles with complex shape was developed. By incorporating this model into the gradient particle jet model, the multiscale particle jet model were developed. Since the temperature gradients within the particles cannot be captured experimentally, the model was validated indirectly by correlating particle temperatures with experimentally obtained coating thickness distributions. A particle impact model was generated to simulate the coating formation by multiple particle impacts. This model can track the cooling rates of the individual particles as well. A multi-scale coupling strategy enabled linking the multiscale particle jet with the coating formation model. Finally, a model for the determination of the effective thermal conductivity of the simulated coatings was implemented as the final link in the simulation chain. In addition to increasing the understanding of distinct aspects of the process, the simulation chain has laid the foundation of a predictive tool that can be deployed for designing new coating systems.
