Duration: 4 hours – Date and time: Oct 1, 2023 – Location: TBD
One defining characteristic of twenty-first century engineering challenges is the breadth of their scope. Each is so large and complex in its own right that each might seem entirely intractable. Furthermore, each goal might appear so different from the next that one might naturally conclude that the skills needed to solve one challenge are entirely distinct from those of another. Consequently, our engineering education system would have to turn “on a dime”, orient itself towards each of these 14 challenges, and ask our engineering students to commit themselves to one of these challenges; never to change direction again. And in the event that we are successful on such a course, the engineering education system would have to pivot again years later to address the newly cropped-up grand challenges. Quite fortunately, the developing consensus across a number of STEM fields is that each of these goals is characterized by an “engineering system” that is analyzed and re-synthesized using a meta-problem-solving skill set. In essence, our formidable challenge is one of convergence towards abstract and consistent methodological foundations for engineering systems, in general. Two fields in particular have attempted to traverse this convergence challenge: model-based systems engineering (MBSE) and network science. MBSE has developed as a practical and interdisciplinary engineering discipline that enables the successful realization of complex systems from concept, through design, to full implementation. Despite its many accomplishments, MBSE’s reliance on graphical modeling language ultimately requires additional mathematical tools to gain quantitative insight. In contrast, the network science community (NSC) has developed to quantitatively analyze networks that appear in a wide variety of engineering systems. And yet, despite its methodological developments in multi-layer networks, the NSC has often been unable to address the explicit heterogeneity often encountered in engineering systems. This tutorial serves to introduce the audience to hetero-functional graph theory drawing on several recent publications and a new consolidating textbook entitled: Hetero-functional Graph Theory for Interdependent Smart City Infrastructures by W.C. Schoonenberg, I.S. Khayal, and A.M. Farid. It demonstrates that HFGT can be applied extensibly to an arbitrary number of arbitrarily connected topologies of “convergent” engineering systems. To the MBSE community, we hope that HFGT will be accepted as a quantification of many of the structural concepts found in MBSE languages like SysML. To the NSC, we hope to present a new view as to how to construct graphs with fundamentally different meaning and insight. Finally, it is our hope that HFGT serves to overcome many of the theoretical and modeling limitations that have hindered our ability to systematically synthesize, analyze, and re-synthesize the structure and function of convergent engineering systems.