Procedure for Experimental Data Assessment for Numerical Solver Validation in the Context of Model based Prediction of Powder Coating Patterns

Abstract

In the scope of this study an experimental powder coating setup is designed and the method to extract statistically significant trends from the data generated is developed. The ultimate goals are to i) validate a previously developed 3D Euler-LaGrangian numerical solver [1] and to ii) characterize the essential parameters for industrial powder coating processes in subsequent phases. The experiments involved coating a flat plate substrate with a corona spraying pistol. The resulting coating thickness has been quantified through the state of the art Coatmaster technology [2,3]. The raw data generated from the Coatmaster has been filtered and rigorously analyzed to identify statistically significant trends. Furthermore, characteristic variables have been constructed for subsequent comparison to the numerical solver. This study reveals the challenges involved in assessing experimental data to extract meaningful comparisons for numerical solver validation.