Combining dimensional analysis with model based systems engineering

The model based systems engineering (MBSE) approach describes a system using consistent views to provide a holistic model as complete as possible. MBSE methodologies end with the physical architecture of the system, but a physical model is clearly incomplete without the study of its associated physical laws and phenomena related to the whole system or its parts. However, the computational demands could be excessive even for modest projects. Dimensional analysis (DA) is common in fluid dynamics and chemical engineering, but its application to systems engineering is still limited. We describe an engineering methodological process, which incorporates DA as a powerful tool to understand the physical constraints of the system without the burden of complex analytical or numerical calculations. A detailed example describing a microantenna is presented showing the benefits of this approach. The selected example describes a problem rarely covered in modern expositions of DA in order to show the wide benefit of these techniques. The information provided by this analysis is very useful to select the best physically realizable architectures, testing design, and conduct trade-off studies. The complexity of modern systems and systems of systems demands new testing procedures in order to comply with increasingly demanding requirements and regulations. This can be accomplished through research in new DA methods. Finally, this article serves as a fairly comprehensive guide to the use of DA in the context of MBSE, detailing its strengths, limitations, and controversial issues.

Automated summary

The model based systems engineering (MBSE) approach uses consistent views to create a comprehensive model of a system. However, a physical model of the system is incomplete without understanding the physical laws and phenomena associated with it. This article describes a methodological process that incorporates dimensional analysis (DA) as a tool to understand physical constraints without complex calculations. A detailed example of a microantenna is presented to demonstrate the benefits of this approach. The article also discusses the importance of research in new DA methods to meet the increasing demands of complex systems and regulations. Overall, this article serves as a comprehensive guide to using DA in the context of MBSE, detailing its strengths, limitations, and controversial issues.