This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

A relatively recent report published by NASA (CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences, NASA/CR–2014-218178, 2014) identifies “Mesh generation and adaptivity” as one of the most significant deficiencies in the CFD workflow. In brief, the current link between simulation results and CAD models is rendered inadequate and poor mesh generation performance and robustness are highlighted as the main impediments causing CFD users to spend more time on mesh construction and maintenance, rather than focusing on the final solution. Moreover, increased human intervention required during the mesh generation phase is the main contributor towards increased cost of any CFD simulation that involves even lightly complex models. The report is dated six years ago and despite the advances in geometry clean-up, watertight-ing, common model build-up and meshing automation, the outcome is relatively similar due to the ever-increasing complexity in simulated models. Therefore, the challenges imposed on pre-processing software are significant, as it must deliver huge mesh sizes within the shortest time on a limited amount of hardware resources, while maintaining high-quality characteristics and promoting automation.

Over the years, CFD users did apply several workarounds to achieve reduction in preparation and meshing times of model variants; however, they result in limited model flexibility and rely heavily on the human factor. In this study, we investigate the impact of a new meshing technique that promises volume cavity replacement on external aerodynamics results of an open-wheel racing Champ Car, simulating different set-up variants. Seamless integration with data management systems, “intelligent” hybrid volume (re-)meshing (featuring prism layers and mixed Hex-Tet meshes) and automated domain splitting are some of the key features utilised to dramatically reduce preparation and meshing times of several aerodynamic package variants of the Champ Car. Investigations include method evaluation based on quantitative results on meshing times and impact of mesh quality and cavity interconnectivity on the calculated flow field variables.

Results presented in this study demonstrate an immense time reduction in preparation and meshing times of model variants, an unmatched mesh reproducibility and robustness between baseline and variant models, while maintaining high-quality mesh metrics according to solver requirements. In addition to method robustness, it was also concluded that the link between geometry and meshed model was improved due to direct association of original parts in the absence of dividing geometry boxes. The proposed volume cavity replacement method partially resolves known issues of CFD models of sizes from tens to hundreds million elements, while it also manages to minimise human interaction without compromising quality. Finally, such developments are potentially taking the CFD community closer to “results re-use” for minor local design changes.