NSF Award
2301627
This Engineering Research Initiation (ERI) project aims to supplement essential missing knowledge for representing and managing engineering design problems at large and extreme scales. Inspired by the striking similarities between complex physical systems and complex engineering systems, we will consider primitive technologies as fundamental building blocks that form components, subsystems, systems, and eventually, systems of systems, which is analogous to the hierarchical physical world, where particles form atoms, which in turn form molecules, cells, organisms, planets, and galaxies. This research will establish a rigorous mathematical foundation that enables: (a) systematic investigation of the statistical pattern of technology emergence in the time dimension during and after a given technical project; and (b) dynamic system representation and re-evaluation to interpret potential system behaviors with the existing technology pool. This research establishes a new understanding of the fundamental dynamics of system evolution during the design process and provides a bottom-up perspective to handle unreliable system model representations and unexpected design outcomes for complex engineering systems. We will test the framework using the Apollo and Artemis programs as two applications at extreme scales to investigate technology evolution and the spillover effect during and after each project. This research will generate new knowledge that can enhance our understanding of the underlying causes of cost and schedule overruns at both the technology and system levels. Such insights can inform decision-making processes for future space missions and complex engineering programs in various industries. This project will also strive to engage broader interest in engineering design and space exploration among K-12 students and the public through outreach and diversity initiatives.<br/><br/>The overarching goal of this project is to create a novel system representation framework by connecting complex engineering systems with recent breakthroughs in understanding complex physical systems. We will model the engineering design process as the Renormalization Group (RG) transformation, a ubiquitous technique in modern statistic physics that models the behaviors of a system depending on the scale of which it is observed. The research approach is to (R1) understand the technology recursion process in the time dimension; and (R2) create a renormalization scheme in the hierarchy dimension to support dynamic system representation based on the macroscopic design features we are interested in. This research will lead to a new bottom-up approach to resolve epistemic uncertainties during complex engineering system design driven by the lack of knowledge of the correct way to model the system, future design decisions, and technology development outcomes. The research will have broad societal impact by incorporating the rigorous mathematical structure of technology recursion and system dynamics into complex system design to benefit a wide range of industries suffering from high development costs and project schedule overruns (e.g., public infrastructure, healthcare, defense, and aerospace). The integrated education plan involves engineering-focused outreach initiatives, such as pre-college workshops for K-12 students and under-represented minorities to develop broader interest in engineering design and space exploration.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
