Willem Rutten

PhD Candidate in the Nuclear Fusion group within the Applied Physics and Science Education Department at TU/e

Integrating MBSE and multidisciplinary analysis & optimization in deep tech system design:
the case of nuclear fusion

Bio.
Willem Rutten is a PhD Candidate in the Nuclear Fusion group within the Applied Physics and Science Education Department at TU/e, focusing on applications of model-based system engineering and design optimization in nuclear fusion. Willem received his BSc in Applied Physics and a double MSc degree in Mechanical Engineering and Science & Technology of Nuclear Fusion from Eindhoven University of Technology.

Abstract.
As a deep tech endeavour, the design of a first-of-a-kind nuclear fusion reactor involves extensive research projects to predict system behaviour. Currently, digital design approaches are being pursued to manage complexity, explore design concepts and inform decision-making. Such approaches will need to integrate model-based systems engineering (MBSE) approaches with multidisciplinary design analysis and optimisation (MDAO) to simulate and optimise system performance. However, state-of-the-art integrated MBSE-MDAO approaches do not explicitly focus on supporting collaboration in research-oriented design processes.
This work reframes MBSE and MDAO in an integrated design process, and develops a method designed to facilitate communication between the process actors: architects, engineers and physicists. To that end, we introduce causal physical effects into the MBSE graph to intuitively represent current understanding of system behaviour as developed by physicists. Furthermore, the MBSE graph is visualised using design structure matrices (DSMs), providing stakeholder-specific overviews of the system and the simulation and optimisation workflows to be executed. With an illustrative example it is demonstrated how this approach can enable systematic identification of integration issues in the system design and its analysis workflow. As such, the presented work provides an approach to streamline the integration of MBSE and MDAO in the design process and shows potential to improve collaborative decision-making in the design of first-of-a-kind complex systems.