Simulation models save costs through process control
Complex materials such as composite paint layers can be studied with the help of computer simulations. For example, drying processes take place on the quantum level, but also on larger spatial and temporal scales.
Multi-scale modelling is a mathematical method that combines these different simulation levels and thus helps to achieve an exact description and realistic predictions for materials and processes. The model in the research project captures the simultaneous heat and mass transfer in a liquid, drying paint layer. The focus was on optimising drying processes in the production of painted coils – primarily for the automotive industry. If these processes can be predicted precisely, this makes it possible to evaporate the maximum amount of solvent, and to do so in the shortest possible time with minimal energy consumption. At the same time, the quality of the surface should be maintained.
The developed multi-scale model is based on a micro/coating and a macro/oven scale, which are linked with the help of an iterative method. The processes were investigated in a convection oven and with IR radiators. In this way, the researchers were able to compare and optimise the parameters of drying time, energy consumption and efficiency, among others. When assessing the coating quality, the team paid particular attention to good adhesion to the metal substrate, high resistance to environmental influences and sufficient flexibility of the surface so that the sheet does not show any cracks when it has to be bent. The project was funded by the EU’s Horizon 2020 research and innovation funding programme, among others.