
Month: February 2024
Dr. Astrid Layton selected for an NSF CAREER Award
The 5-year long award is for the grant titled “CAREER: Resilient Engineering Systems Design Via Early-Stage Bio-Inspiration.” NSF CAREER Awards, part of the NSF Faculty Early Career Development Program, are the most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Read more here.
Resilience is critical for engineering systems, but comprehensive methods and widely accepted guidelines tailored specifically for incorporating resilience in the early stages of system design are lacking. This Faculty Early Career Development Program (CAREER) award supports research which aims to address these gaps by working at the intersection of bio-inspired design, systems engineering, and engineering design to establish quantitative tools for addressing system resilience when minimal information is available. Biological ecosystem characteristics will be investigated for their ability to guide system designers in the early design stages towards better response and recovery, including situations involving targeted and/or random disturbances. Ultimately, the project will develop knowledge and methods to ensure that human systems can withstand disturbances – especially important for the critical infrastructure systems that supply our water, power, or medicines – by safeguarding against potential failures and costly downtime. Collaborative feedback from ecologists, industry, and academic experts will ensure that the interdisciplinary work maintains each domain’s critical features. Additional deliverables from this project include a “Walk Like an Engineer” program, which engages participants of all ages and abilities in engineering inspiration scavenger hunts through local parks, led by both a bio-inspired engineering design expert and a Nature Center host. The themed nature walks, which will focus on topics such as “Nature’s Systems” and “Nature’s Resilience”, will encourage participants to see themselves as design engineers learning from nature. The program will advance the United States future workforce by nurturing interdisciplinary communication skills and early interest and excitement in STEM-based design, while also teaching the public about nature and engineering in a connected manner.
More information can be found here: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2340170&HistoricalAwards=false
This project supports the long-term goal of enhancing the early integration of resilience into the system design process, allowing designers to make proactive choices to create more sustainable and resilient systems that can withstand disruptions and recover effectively. The research objectives of this project are to provide quantitative tools for assessment of biological inspiration in engineering system design, extend the use of effective bio-inspiration into system recovery, and formulate practical design tools for achieving system resilience from biological ecosystem principles found to be effective. Ecological Network Analysis will provide a quantitative method for extracting desirable traits from resilient biological ecosystems (e.g., food webs) and applying them to human engineered systems. Of interest is how these traits can improve a system’s robustness and recovery, which will be tested using a variety of case study types and criticality levels, including supply chains, water distribution networks, power grids, and industrial resource networks. The most beneficial biological systems traits will be further investigated to generate fundamental engineering principles, such as the impact of topology versus weights on nature’s systems characteristics. A study of targeted versus random disturbances will provide additional insight into where these biological systems characteristics have the most value for engineering designers seeking system-level resilience. The project’s research objectives are integrated and enhanced by the project’s educational objectives: to create and foster engineering excitement before students typically self-exclude from STEM; teach the public about how nature and engineering can be connected; and create STEM access for and inclusion of students with intellectual and developmental disabilities. Evaluation of the educational outreach activities will also provide important documentation for the use of nature to increase interest in engineering at all ages, as well as in underrepresented and underserved groups.
Two New BiSSL Papers Published
Two journal papers related to the use of bio-inspired system design approaches for cyber-physical systems from the BiSSL group have recently been accepted for publication! The 1st stems directly from a current ongoing grant with Sandia National Labs with BiSSL Ph.D. student Emily Payne as co-author and the 2nd is a culmination of multiple collaborations across mechanical and electrical engineering at Texas A&M and is led by former BiSSL Ph.D. student Abheek Chatterjee, now a post-doc at NIST.
Abstract: Cyber-physical systems have behavior that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber-physical systems requires improved understanding of the combined cyber-physical system behavior and methods for holistic analysis. Therefore, we propose leveraging clustering techniques on cyber-physical data from smart grid systems to analyze differences and similarities in behavior during cyber-, physical-, and cyberphysical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber-physical systems. Through this analysis, deeper insights can be shared with decision-makers on what cyber and physical components are strongly or weakly linked, what cyber-physical pathways are most traversed, and the criticality of certain cyber-physical nodes or edges. This paper presents several types of clustering methods for cyber-physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber-physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber-physical graph interdependency analysis.
Jacobs, N., S. Hossain-McKenzie, S. Sun, E. Payne, A. Summers, L. Al Homoud, A. Layton, K. Davis, and C. Goes. (2024) “Leveraging Clustering Techniques for Cyber-Physical System Analysis to Enhance Disturbance Characterization.” The Institution of Engineering and Technology (IET) Cyber-Physical Systems: Theory & Applications.
Abstract: The design of resilient infrastructure is a critical engineering challenge for the smooth functioning of society. These networks are best described as Cyber-Physical Systems of Systems (CPSoS): integration of independent constituent systems, connected by physical and cyber interactions, to achieve novel capabilities. Bio-inspired design, using a framework called the Ecological Network Analysis (ENA), has been shown to be a promising solution for improving the resilience of engineering networks. However, the existing ENA framework can only account for one type of flow in a network. Thus, it is not yet applicable for the evaluation of CPSoS. The present work addresses this limitation by proposing a novel multigraph model of CPSoS, along with guidelines and modified metrics that enable ENA evaluation of the overall (cyber and physical) network organization of the CPSoS. The application of the extended framework is demonstrated using an energy infrastructure case study. This research lays the critical groundwork for investigating the design of resilient CPSoS using biological ecosystems inspiration.
Chatterjee, A., H. Huang, R. Malak, K. Davis, and A. Layton. (2024) “Extending Ecological Network Analysis to Design Resilient Cyber-Physical System of Systems.” IEEE Open Journal of Systems Engineering.