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Model-Based Systems Engineering (MBSE), is the model on which the relation between which the system components are specified and integrated. MBSE has become essential in various scientific applications as it helps and ensures systems work well across different areas, by improving team collaboration in work and by making the design process more efficient. However, the main role of MBSE lies in its use in astrophysical and overall physical and engineering missions. Traditional methods of modeling often struggle to give a completely diverse view of complex systems due to their limited scope. MBSE with Systems Modeling Language (SysML), on the other hand, offers significant advantages in these domains in lieu of the onion model of its systems, where the model is developed and completed in layers. This study explores in depth how MBSE and SysML can improve astrophysical and physical missions by a thorough examination of their biases and their use in previous missions, as well as discussing their potential challenges and plausible solutions. This study identifies and reviews the critical metrics for measuring success in astrophysical missions, and suggests the factors that should be considered while reviewing the scientific data for the same. Furthermore, by examining case studies from previous missions by NASA, ESA, etc., this study aims to show the clear advantages of using MBSE for designing, testing, and validating complex astrophysical systems for their broader applications in the field and beyond.
Moulic et al. (Tue,) studied this question.