New BiSSL publication in the journal Integrative & Comparative Biology

June 20, 2025

A paper coauthored by Ph.D. student Hadear Hassan and Dr. Layton titled “Improving Cross-Disciplinary Knowledge Transfer for Bio-Inspired Engineering Design” has been published in the Integrative And Comparative Biology (ICB) journal. The work covers a 4 year study of the bio-inspired engineering design inspiration process, looking at how the technical level of biological information impacts the success of the resultant engineering designs. The work finds that a staggered approach may be the most beneficial, starting with basic references like those from National Geographic or zoos and following up the initial design generation round with highly technical and detailed journal articles to provide more functional details.

“Bio-inspired design has become a significant driver of innovation, enabling the development of effective solutions to some of the world’s toughest challenges. Bio-inspired design leverages evolutionary advancements to create products and processes that are often more efficient and sustainable. However, applying biological insights to engineering can be challenging due to the distinct ways the two disciplines define and interpret core concepts. This paper explores the cognitive and technical skills required to effectively translate biological inspiration into engineering solutions. Our hypothesis focuses on bridging the “language and representation gap” between biology and engineering. The goal of this paper is to identify key aspects of biological representation that enable its successful adaptation into engineering design, fostering the development of more impactful and efficient bio-inspired solutions. The analysis of student feedback and ideation outputs revealed that engineers preferred biology texts with a medium level of technical complexity, balancing ease of understanding with image quantity. Basic references were found to support diverse idea generation, while more technical texts proved useful and necessary for understanding in-depth biological insights and applying them to engineering problems. Future research could explore the impact of information presentation order, the role of biological experts in deepening insights, and the use of machine learning to refine how biological information is selected and categorized to enhance the bio-inspired design process.” – Hassan and Layton. (2025) “Improving Cross-Disciplinary Knowledge Transfer for Bio-Inspired Engineering Design.” Integrative & Comparative Biology. DOI: 10.1093/icb/icaf119

Normalized student usefulness ratings per reference, based on reading ease (FRE) across the 3 reference categories (technical-blue circles, general-orange triangles, and basic-green squares). The red horizontal and vertical shading bars highlight the most frequently selected range for FRE if technical references, which falls between 28 and 45, along with their corresponding normalized voting quantity ranging from 0.65 to 1.

Design Society Invited Talk on “Future of Sustainable Design”

March 20, 2025

Drs. Astrid Layton, Jessica Menold, Kosa Goucher-Lambert, Mohsen Moghaddam, and Zhenghui Sha were invited by Drs. Carolyn Seepersad and Julie Linsey at Georgia Tech for an insightful series of talks on The Future of Design for the annual “Rigi” meeting of the Design Society. The talks will be compiled in an editorial journal paper in the Journal of Mechanical Design later this year.

Drs. Carolyn Seepersad, Astrid Layton, Kosa Goucher-Lambert, Zhenghui Sha, and Mohsen Moghaddam at the annual Design Society “Rigi” meeting, held at Georgia Tech.

Journal Paper on Circular Economy in Manufacturing Published in JMSE

Two BiSSL students, Ph.D. student Hadear Hassan and MS alumna Amira Bushagour, have coauthored a paper in ASME’s Journal of Manufacturing Science and Engineering. The paper, originally presented at the 2024 MSEC conference, focuses on useful overlaps between reconfigurable manufacturing and circular economy efforts by assessing the adaptability and connection to circular economy principles in 44 different manufacturing system configurations.

Reconfigurability in manufacturing signifies a system’s capacity to promptly adapt to evolving needs. This adaptability is critical for markets to maintain operations during unexpected disruptions, including weather anomalies, cyber-attacks, and physical obstructions. Concurrently, the concept of a circular economy is gaining popularity in manufacturing to mitigate waste and optimize resource utilization. Circular economy principles aim to reduce environmental impacts while maximizing economic benefits by emphasizing the reuse of goods and resource byproducts. The nexus between reconfigurability and the circular economy stems from their shared pursuit of sustainability and resilience. Interestingly, biological ecosystems also exhibit these traits, showcasing exceptional adaptability to disturbances alongside the ability to effectively utilize available resources during normal operations. This study explores various manufacturing system configurations to assess both their adaptability and connection to circular economy principles. 44 configurations are categorized based on layout (e.g., job shop, flow line, cellular) and analyzed using convertibility, cyclicity, and Degree of System Order metrics. A significant positive correlation (R2 = 0.655) is found between high convertibility and ecologically similar levels of structural cycling, suggesting that effective resource utilization supports adaptability in manufacturing systems. Furthermore, this paper proposes the existence of a possible “window of vitality” for cyclicity, as it demonstrates a significant correlation (R2 = 0.855) between the Degree of System Order and cyclicity. Identifying systems that strike a balance between redundancy, efficiency, convertibility, and cyclicity can aid manufacturing system designers and decision-makers in making choices that address increasing requirements for both sustainability and resilience.

Hassan, H., A. Bushagour, and A. Layton. (2024) “Resilient Circularity in Manufacturing: Synergies between Circular Economy and Reconfigurable Manufacturing.” ASME Journal of Manufacturing Science and Engineering. 146(11): 110902. DOI: 10.1115/1.4065744

2 New Cyber-Physical Power Systems Papers Published

Two new papers have been recently published from the BiSSL group first-authored and co-authored by its students resulting from a collaborative grant with Sandia National Lab and Dr. Kate Davis’ group in Electrical Engineering.

Highlights include:

1. A graph-embedding technique, Node2Vec, to capture neighborhood relationships with second-order biased random walks for risk assessment in cyber-physical power grids.
2. Highly realistic and synthetic cyber network topologies for power grids to perform our case studies.
3. Visualization of the risk assessment with various methods for a more comprehensive situational awareness for grid operators.

Modern power grids and other complex systems are a fusion of physical and cyber components, giving rise to intricate interdependencies. These interdependencies, however, also expose vulnerabilities that can be exploited by adversaries. This paper delves into the critical examination of these interconnections, inspired by Ecological Network Analysis (ENA) techniques. By drawing from ecological modeling, we aim to understand the role of cyber-physical interdependencies in the resilience of complex systems. We introduce various modeling methods, including bipartite and tripartite networks, to analyze and map these interdependencies in the context of the IEEE WSCC 9-bus and the ACTIV 200-bus case study. The paper explores how these models can identify key actors and assess network resilience. Through a detailed methodology, we apply ecological metrics and community identification techniques to comprehensively evaluate the system’s interactions. The findings offer insights into the interplay of cyber and physical elements in power grids and other complex systems. These analysis methods show that tripartite networks produce more information on indirect interactions within a complex network. Additionally, they provide detailed information on how disturbances could propagate in a cyber-physical power system. Denial of service scenarios for the WSCC 9-bus and the ACTIV 200-bus case studies are employed to support this conclusion.

Payne, E., S. Hossain-McKenzie, N. Jacobs, K. Davis, A. Layton. (2024) “Analyzing Cyber-Physical Modularity and Interdependence Using Bio-Inspired Graph Modeling.” IEEE Access. DOI: 10.1109/ACCESS.2024.3450368
This article explores vulnerabilities in modern power systems due to interdependencies between physical, cyber-physical, and cyber devices. Ecological Network Analysis (ENA) assists in constructing bipartite and tripartite networks for the WSCC 9-bus and ACTIV 200-bus systems. The findings reveal that tripartite networks offer deeper insights into indirect interactions, enhancing our understanding of systemic resilience under denial-of-service scenarios.

Abstract: Power systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large-scale power infrastructures as cyber-physical systems is still in its early stages. Drawing inspiration from machine-learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large-scale cyber-physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high-dimensional structures in low-dimensional spaces, facilitating advanced machine-learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding-based approach, the authors present a structured and methodical framework for risk assessment in cyber-physical systems. The proposed graph embedding-based risk analysis framework aims to provide a more insightful perspective on cyber-physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber-physical power system models: the Western System Coordinating Council (WSCC) 9-Bus System and the Illinois 200-Bus System, thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Sun, S., H. Huang, E. Payne, S. Hossain-McKenzie, N. Jacobs, H. Vincent Poor, A. Layton, and K. Davis. (2024) “A Graph Embedding-Based Approach for Automatic Cyber-Physical Power System Risk Assessment to Prevent and Mitigate Threats at Scale.” The Institution of Engineering and Technology (IET) Cyber-Physical Systems: Theory & Applications. DOI: 10.1049/cps2.12097

Successful ASME 2024 MSEC Manufacturing Science & Engineering Conference

BiSSL Ph.D. student Hadear Hassan presented work at the annual ASME 2024 MSEC Manufacturing Science & Engineering Conference in Knoxville, TN. She presented two papers, both co-authored with BiSSL alum Amira Bushagour (who is now a Ph.D. student at Aarhus University in Denmark). One of the papers has already been selected for publication in the special issue of ASME’s Journal of Manufacturing Science and Engineering (JMSE).

Abstract: The circular economy (CE) is a resource system in which byproducts and traditional end-of-life resource flows are fed back into the system to reduce virgin resource use and waste production. Emerging technologies offer an exciting opportunity to support circular economy efforts, especially in the early design phase when opportunities for incorporating these technologies are relatively easy. Traditionally, however, the early design phase has access to very little data about resource flows which makes the introduction of new technologies difficult to do, especially with respect to market-related design decisions. In the later design stages, this data is easier to obtain but is met with increased inflexibility and costs that make these types of changes less common. This paper proposes the use of cyclicity, also known as spectral radius, and NS* minimal-data input metrics that can direct designers to options with the greatest theoretical impact on routing commonly wasted resources back into value circulation. Cyclicity is a metric commonly used in ecology to assess the existence and complexity of cycles, or material/energy pathways that can start and end at the same node, occurring in a system. The metric uses a topological adjacency matrix of resource flows between potential circular economy actors, modeled as a directional graph, and is calculated as the largest absolute eigenvalue of an adjacency matrix and can be a value of zero (no cycles), one (basic cycles), and any value larger than one (increasing presence and complexity of cycles). This study also evaluates actors making up the network as to whether they are part of a strong cycle, a weak component of a cycle, or are disconnected from a cycle, quantified with NS. In a strong cycle, all actors feed into the cycle and the cycle feeds back into the actors. Actors that are weakly connected to a cycle do not contribute to a cyclic pathway. Disconnected actors are not connected to any actor participating in cycling. This paper conducts two case studies on these design tools. The first, a survey of 51 eco-industrial parks (EIPs) and 38 ecological food webs to compare the presence and complexity of cycles in industrial resource systems to ecological resource systems. The latter, food webs, are very effective at retaining value inside the system boundaries. The former, EIPs, were built in support of circular economy principles to use waste streams from one industry as resource streams for others. The analysis shows that 46 out of 51 EIPs had cyclicity values of one or greater and an average of 54% of actors in an EIP are strong. The food webs all have a cyclicity greater than one and an average of 79% of actors in a food web are strong. These results can help decision makers consider CE-supporting pathways earlier in the design process, increasing the likelihood that emerging technologies are incorporated to maximize their CE impact. The second case study explores an emerging technology, Brine Miners, and how cyclicity and NS can be used to guide design decisions to impact the ability of this technology to aid in the creation of a circular economy. The exploration found that focusing on the creation of energy has the potential to add new actors to resource cycling and that diversifying the uses of byproducts creates more complex cycling within a hypothetical economy.

(Paper Number: MSEC2024-125107) “Cyclicity as an Early Circular Economy Design Tool for Emerging Technologies” by Amira Bushagour, Hadear Hassan, and Astrid Layton

Abstract: Reconfigurability in manufacturing signifies a system’s capacity to promptly adapt to evolving needs. This adaptability is critical for markets to maintain operations during unexpected disruptions, including weather anomalies, cyber-attacks, and physical obstructions. Concurrently, the concept of a circular economy is gaining popularity in manufacturing to mitigate waste and optimize resource utilization. Circular economy principles aim to reduce environmental impacts while maximizing economic benefits by emphasizing the reuse of goods and resource byproducts. The nexus between reconfigurability and the circular economy stems from their shared pursuit of sustainability and resilience. Interestingly, biological ecosystems also exhibit these traits, showcasing exceptional adaptability to disturbances alongside the ability to effectively utilize available resources during normal operations. This study explores various manufacturing system configurations to assess both their adaptability and connection to circular economy principles. 44 configurations are categorized based on layout (e.g., job shop, flow line, cellular) and analyzed using convertibility, cyclicity, and Degree of System Order metrics. A significant positive correlation (R2 =0.655) is found between high convertibility and ecologically similar levels of structural cycling, suggesting that effective resource utilization supports adaptability in manufacturing systems. Furthermore, this paper proposes the existence of a possible ” window of vitality” for cyclicity, as it demonstrates a significant correlation (R2 =0.855) between the Degree of System Order and cyclicity. Identifying systems that strike a balance between redundancy, efficiency, convertibility, and cyclicity can aid manufacturing system designers and decision-makers in making choices that address increasing requirements for both sustainability and resilience.

(DOI: 10.1115/1.4065744) “Resilient Circularity in Manufacturing: Synergies between Circular Economy and Reconfigurable Manufacturing” by Hadear Hassan, Amira Bushagour, and Astrid Layton, Journal of Manufacturing Science and Engineering

New Journal Paper in Proceedings of the IEEE

A new paper in the Proceedings of the IEEE led by collaborator Hao Huang (postdoc at Princeton) has been published. In this paper, we present a systematic review of power system resilience enhancement techniques that aim to harden the infrastructure and proactively defend against threats. Furthermore, this article broadens the perspective on modern power systems, considering their interconnected cross-domain multi-layered architecture, for enhancing their resilience. We believe that it is significant to incorporate heterogeneous networks and data across physical, cyber, weather, and human domains to develop holistic criteria and approaches, and it is necessary to emphasize the value of heterogeneity in physical, cyber, and social networks along with granular modeling to derive new standards and requirements for designing and operating modern power systems. Additionally, we propose two new research directions: higher-order subgraph analyses and scientific machine learning, to understand the interdependence and interactions across different networks and data, facilitating trustworthy decision-making processes to enhance the inherent resilience of modern power systems.

Abstract: Modern power systems are the backbone of our society, supplying electric energy for daily activities. With the integration of communication networks and high penetration of renewable energy sources (RESs), modern power systems have evolved into a cross-domain multilayer complex system of systems with improved efficiency, controllability, and sustainability. However, increasing numbers of unexpected events, including natural disasters, extreme weather, and cyberattacks, are compromising the functionality of modern power systems and causing tremendous societal and economic losses. Resilience, a desirable property, is needed in modern power systems to ensure their capability to withstand all kinds of hazards while maintaining their functions. This article presents a systematic review of recent power system resilience enhancement techniques and proposes new directions for enhancing modern power systems’ resilience considering their cross-domain multi-layer features. We first answer the question, “What is power system resilience?” from the perspectives of its definition, constituents, and categorization. It is important to recognize that power system resilience depends on two interdependent factors: network design and system operation. Following that, we present a review of articles published since 2016 that have developed innovative methodologies to improve power system resilience and categorize them into infrastructural resilience enhancement and operational resilience enhancement. We discuss their problem formulations and proposed quantifiable resilience measures, as well as point out their merits and limitations. Finally, we argue that it is paramount to leverage higher-order subgraph studies and scientific machine learning (SciML) for modern power systems to capture the interdependence and interactions across heterogeneous networks and data for holistically enhancing their infrastructural and operational resilience.

Huang, H., H. V. Poor, K. R. Davis, T. J. Overbye, A. Layton, A. Goulart, and S. Zonouz. (2024) “Toward Resilient Modern Power Systems: From Single Domain to Cross-Domain Resilience Enhancement.” Proceedings of the IEEE. 112(4): 365-398. DOI: 10.1109/JPROC.2024.3405709

New Systems Engineering Journal Publication

A new open access publication is out in the Wiley and INCOSE journal Systems Engineering from BiSSL in collaboration with Dr. Julie Linsey at Georgia Institute of Technology! The article, co-authored by Samuel Blair, Garrett Hairston, Claire Kaat, and Henry Banks and titled “Bio-inspired human network diagnostics: Ecological modularity and nestedness as quantitative indicators of human engineered network function,” investigates the use of modularity and nestedness, 2 analyses that are traditionally used in ecology to study interaction patterns in mutualistic networks (ex. plant-pollinator networks), for human-engineered interaction networks. The paper uses two university engineering makerspaces, modeled as student-tool interaction networks, as case studies to highlight the ability of the approaches to quantitatively monitor the interaction patterns over time and even capture network disturbances (in the case study COVID-19 occurred over the course of data collection).

Abstract:

Analyzing interactions between actors from a systems perspective yields valuable information about the overall system’s form and function. When this is coupled with ecological modeling and analysis techniques, biological inspiration can also be applied to these systems. The diagnostic value of three metrics frequently used to study mutualistic biological ecosystems (nestedness, modularity, and connectance) is shown here using academic engineering makerspaces. Engineering students get hands-on usage experience with tools for personal, class, and competition-based projects in these spaces. COVID-19 provides a unique study of university makerspaces, enabling the analysis of makerspace health through the known disturbance and resultant regulatory changes (implementation and return to normal operations). Nestedness, modularity, and connectance are shown to provide information on space functioning in a way that enables them to serve as heuristic diagnostics tools for system conditions. The makerspaces at two large R1 universities are analyzed across multiple semesters by modeling them as bipartite student-tool interaction networks. The results visualize the predictive ability of these metrics, finding that the makerspaces tended to be structurally nested in any one semester, however when compared to a “normal” semester the restrictions are reflected via a higher modularity. The makerspace network case studies provide insight into the use and value of quantitative ecosystem structure and function indicators for monitoring similar human-engineered interaction networks that are normally only tracked qualitatively.

Blair S, Hairston G, Banks H, Kaat C, Linsey J, Layton A. Bio-inspired human network diagnostics: Ecological modularity and nestedness as quantitative indicators of human engineered network function. Systems Engineering. 2024; 1-13. https://doi.org/10.1002/sys.21756

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.

Joint (JMD & JMSE) Special Issue On Advances In Design And Manufacturing For Sustainability

Dr. Layton is a guest editor for an upcoming special issue on sustainability in design and manufacturing being published jointly between ASME’s journals of Mechanical Design and Manufacturing Science and Engineering. Drafts are due July 31, 2023.

This special issue is a joint effort between the ASME Manufacturing Engineering Division (MED) and the Design Engineering Division (DED) as part of a collaboration to advance design and manufacturing research in sustainability. As the need grows for methodologies and tools capable of supporting sustainable systems, this collection welcomes new scientific approaches, data-driven techniques, informatics solutions, and case studies at the intersection of sustainability, design, and manufacturing. The call focuses on the main challenges the design and manufacturing communities face regarding sustainability and seeks to identify emerging research trends as well as current industry practices for integrating sustainability principles into the design and implementation of engineered systems and processes. Recent advances and future directions along the design-manufacturing continuum are welcome, including submissions on topics such as design decisions, manufacturing process development, manufacturing systems optimization, supply chain integration, sustainable energy systems, product user interaction, and product end-of-life analysis.

Topic Areas

  • Circular Economy and Industry 5.0
  • Artificial intelligence for sustainable design and manufacturing
  • Sustainability analytics
  • Sustainable additive manufacturing and additive remanufacturing
  • Design for recycling, remanufacturing, and reuse
  • CAD integration of sustainable design methods and techniques
  • Sustainable energy systems
  • Industrial ecology in design, manufacturing, and automation
  • Environmental justice in design and eco-design approaches
  • Human-centric design and manufacturing
  • Remanufacturing and advanced recycling processes for critical materials
  • System efficiency and Decarbonization