Congratulations to BiSSL graduate students Varuneswara Panyam and Abheek Chatterjee for each of their first-authored papers being accepted to the 2019 ASME International Design Engineering Technical Conferences: 31st International Conference on Design Theory and Methodology (DTM) in the Biologically Inspired Design session. They will be presenting their papers in Anaheim, California August 18-21, 2019.

Varuneswara Panyam and Astrid Layton, “Bio-inspired modeling approaches for human networks with link dissipation”

Structural similarities between human networks and biological ecosystems have inspired biomimetic design of human networks. The approach requires the networks to be represented as graphs, where the actors are nodes and the connections between actors are links. A major oversight in the application of ecosystem-based modeling to human networks thus far has been in the selection of actors and links. Transfers between species in a biological ecosystem are direct, happening when the species are co-located. Human networks often require a physical aid to complete the transaction, such as power transmission lines, pipelines, or vehicles. These exchange methods experience dissipation, which is not captured in current applications of ecosystem-based human network modeling. Human networks modeled as ecosystems thus far simply categorize exchanges as links in the graph, effectively forcing dissipation during material/energy transport to be neglected. This dissipation can sometimes be high relative to the total energy/material exchanged and thus is a potentially large oversight. Three hypothetical power grids and three Italian urban water distribution networks are used to quantify the impact of modeling interaction aids — power lines and water pipelines — as actors (and thus including any dissipation) in an ecosystem model. Ecological structural and flow metrics previously applied to human networks are evaluated between the two modeling methods. The comparison shows that the impact of this overlooked aspect is potentially significant and warrants consideration.

Abheek Chatterjee and Astrid Layton, “Bio-Inspired Human Network Design: Multi-Currency Robustness Metric Formulation Inspired By Ecological Network Analysis”

The Ecological Network Analysis (ENA) metric ecological robustness quantifies the unique balance that biological food webs have between their pathway efficiency and redundancy, enabling them to maximize their robustness to system disturbances. This robustness is a potentially desirable quality for human systems to mimic. Modeling the interactions between actors in human networks as predator-prey type exchanges (of a medium or currency rather than caloric exchanges) enables an ENA analysis. ENA has been shown to be a useful tool in improving the design of human networks because it allows the characteristics of biological networks to be mimicked. The application of these metrics is, however, limited to networks with only one flow type. Human networks are composed of many different types of flow interactions and thus a biologically-inspired indicator of total system robustness must take into account all of these interactions. This work further develops the traditional ENA ecological robustness metric to accommodate various flows between actors in multi-currency human networks. Two novel methods for quantifying multi-currency flow network robustness are introduced. The mathematical derivation for these new metrics is presented. The water network for the Kalundborg Eco-Industrial Park (EIP) is used as a case study to determine benefits of the proposed robustness metrics. The results obtained using the single-currency robustness and the two multi-currency robustness metrics are compared using the case study. Based on the analysis of the results obtained at the system level, as well as at the sub-levels, both multi-currency metrics showed the ability to predict systems characteristics for the multi-currency Kalundborg EIP. While both of these are promising, more research regarding these metrics is needed in order to develop an elegant and comprehensive total system robustness metric.