Developing autonomous functions for complex systems leads to high demands on the consideration of dependencies to external actors in the usage phase. In Model-Based Systems Engineering (MBSE), this can be achieved by modelling operational aspects. Operational aspects are model elements and their relationships to each other. In this contribution, modelling of operational aspects with a MBSE-approach will be demonstrated exemplary on a case study related to the development of a yacht with an autonomous docking assistant. Currently modelling operational aspects is not common in the civil sector.

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Design of software in the automotive domain often involves simulation to allow early software parametrization. Modeling complex systems or components impacted by the software in an analytical way can be time-consuming, require domain knowledge and executing the analytical models can result in high computational effort. In specific applications, these challenges can be overcome by applying machine learning based simulation. This contribution presents results of a case study in which powertrain components are modeled data-driven with artificial neural networks to support design space exploration