Sensitivity Analysis of the Thickness Mapping and Local Stiffness for Bumper Grille Structural Simulations

In recent decades, thermoplastics have become fundamental materials for the automotive industry, due to characteristics such as low density and increased possibility of manufacturing parts into complex geometries. Correlate the mechanical behavior of parts made with these materials, between virtual and physical testing, still poses a challenge that can be explained by the inherent nature of polymeric compounds, which generally exhibit a complex microstructural composition. This study uses a Bumper Grille made of Acrylonitrile Styrene Acrylate (ASA) as case study. This part is a fundamental external vehicle component, not only for safety criteria, but also for consumer satisfaction. To analyze the structural behavior of a vehicle components such as a Grille, Computer Aided Engineering (CAE) tools with the Finite Element Method (FEM) are commonly applied, in which a good understanding of the analysis setup and physical properties used to define the model are essential. For models built with shell elements the thickness representation is a fundamental parameter that can be determined through automated techniques that define node element values or values ranges to be used. Furthermore, understanding the influence of geometric patterns on FEM results is crucial for accurate and reliable component validation. This work uses different thickness representation in FEM models to analyze the sensitivity of this parameter in static and modal analyses, and subsequently it was described the local stiffness pattern around each actuator position, aiming to subjectively justify the results. The results include natural frequencies for modal analysis and displacements in different regions for static analysis. This study aims to understand the impact that the usage of different thickness mapping variation on the results of structural simulations as well as how the local geometry pattern of each simulation affects the results, and improve the processes of the thickness parameter definition, allowing better data-driven decisions in the future.