Natural ecosystems are an untapped source of quantitative design inspiration for improving the sustainability of human networks. Nature’s achievement of sustainable operations within its ecosystems are the result of millions of years of design iterations. These complex systems are made up of interacting species that effectively use all available resources to support species’ needs while maintaining system-level functions.
Dr. Astrid Layton at Texas A&M University presented this E4C Research Seminar discussing insights into design for sustainability that engineers can glean from the natural world. Ecological food web characteristics offer novel routes to achieving traditionally ‘at odds’ engineering goals like sustainability and profit. Those characteristics include high levels of materials and energy cycling, and a unique balance between redundant and efficient pathways. Through such examples, natural ecosystems hint at solutions to fully achieve the circularity principle of ‘waste equals food.’
Here we are pleased to present highlights from Dr. Layton’s presentation.
In this clip, Dr. Layton characterizes sustainability as a systems-level problem with systems-level solutions.
Next, in takeaways from her presentation, Dr. Layton describes the benefits of bio-inspired systems. These are industrial or other human-made systems modeled after systems found in the natural world.
In this final clip, Dr. Astrid Layton describes the ‘window of vitality,’ a metric for systems analysis that measures efficiency and redundancy. She uses the metric to show the effects of modeling a water distribution network after a natural ecological system.
E4C’s Seminar Series features academic laboratories researching solutions to meet the United Nation’s Sustainable Development Goals. The world’s cutting edge research deserves a platform with a global audience. Join us for presentations of new findings from investigative teams around the globe. And researchers, we welcome your applications to take part in the series. Please send an email to editor@engineeringforchange.org.
Presenter
Dr. Astrid Layton is an assistant professor and Donna Walker Faculty Fellow at Texas A&M University in the Mechanical Engineering department. She received her Ph.D. in Mechanical Engineering from the Georgia Institute of Technology. Her research uses interdisciplinary collaborations to solve large-scale system problems, developing knowledge that supports designers and decision-makers. Dr. Layton is an expert on bio-inspired systems design, with a focus on the use of biological ecosystems as quantitative inspiration for achieving sustainability and resilience in the design of complex human networks/systems/systems of systems. She is the recipient of several teaching and research awards including a 2024 US National Science Foundation CAREER Award. She served as member and chair of ASME’s Design Theory and Methodology’s (DTM) technical committee, has been a guest editor for journal special issues covering resilient systems, networks & graphs, and sustainable design, and is currently an associate editor for ASME’s Journal of Mechanical Design.
Moderator
Dr. Jesse Austin-Breneman is an Associate Professor of Mechanical Engineering at Olin College of Engineering. He earned his Ph.D. in Mechanical Engineering in 2014 from MIT. He also holds a S.M. in Mechanical Engineering from MIT and a B.S. in Ocean Engineering also from MIT. Previous to his academic career, he worked as a development engineer in Peru, working with rural communities on alternative business opportunities and with local doctors’ groups on medical device development. He also spent two years as a high school mathematics teacher in Boston, MA. He currently is the director of the Global Design Laboratory. The group focuses on developing design processes and support tools to help multi-disciplinary design teams think at a systems-level when performing complex system design tasks. This includes investigating the best way to incorporate system-level interactions between stakeholders in emerging markets into the design decision-making process.
