Abstract

The digitalization of development processes in high-tech industries has taken up pace, fueled for years by rising High Performance Computing (HPC) capacity and accelerated by the recent pandemic, that drove companies to enable their engineers to work remote with simulations instead of performing physical experiments on site. To compete at the forefront of innovation, these companies are forced to make the most efficient use of their computational power and provide their developers with the tools to exploit the vast amount of data generated in simulation processes. In this contribution, we demonstrate three aspects of a data-driven digitalization strategy on the example of an automotive vehicle design process: We present a tool for interactive design space exploration, quantify the benefits of using adaptive sampling strategy over one-shot DoE approaches and speak on the analysis of parameter importance based on sampled data. Interactive design space exploration exploits Reduced Order Models (ROM), such as Proper Orthogonal Decomposition (POD) and Isomap, as well as surrogate modelling for the real time prediction of CFD solutions, that would otherwise require of the order of days to compute. Together with an intuitive graphical user interface, this enables engineers to quickly define, visualize and evaluate promising design solutions from an infinite number of variants in the parameter space. The use of adaptive sampling (AS) in the data generation process allows to improve model quality within a given computational budget or to reduce the number of required high fidelity simulations without deteriorating model quality. Different adaptive sampling strategies will be presented and evaluated based on ROM and surrogate model error. Finally, we will illustrate how algorithmic determination of the importance of parameters with respect to performance values, such as the drag coefficient, enables developers to make informed choices on where to best invest further effort and how different parameters are coupled.