Suwelack, StefanStefanSuwelackStoll, MarkusMarkusStollMeyer, AnnikaAnnikaMeyerSlavetinsky, SteffenSteffenSlavetinskySerf, ManuelManuelSerfBursac, NikolaNikolaBursacAlbers, AlbertAlbertAlbersBendl, RolfRolfBendlDillmann, RüdigerRüdigerDillmannSpeidel, StefanieStefanieSpeidel2023-09-262023-09-262016International Association for the Engineering Modeling, Analysis and Simulation Community (NAFEMS 2016)https://hdl.handle.net/11420/43505Computer Aided Engineering (CAE) methods such as finite element based simulation and optimization techniques have become invaluable for product development in the automotive industry. Due to the continuously growing computational power and the introduction of cloud infrastructures, CAE tools are becoming more powerful, faster and cheaper to deploy. However, they still require a lot of expert knowledge in order to be used correctly and effectively. This is why larger corporations usually employ specially trained simulation engineers who help design engineers to set-up, run and post-process simulation scenarios. In order to make simulation technology ubiquitous even in small and medium sized enterprises, it is necessary to develop CAE tools that are equipped with intuitive interfaces and that can be used by non-experts (CAE democratization).Recent advances in artificial intelligence have sparked the development of novel computer-based assistance systems in many domains such as autonomous vehicles, robotics and medicine. These systems demonstrate how knowledge-based approaches can either augment the capabilities of human experts or even replace them. Currently, these methods have seen very limited use within the CAE community.Conference PaperConference Paper