This project focuses on applying bio-inspired principles to industrial resource networks and to creating relationships and metrics for design. This project is envisioned as a comprehensive, interdisciplinary approach to an investigation of biological network efficiencies and translation of the pertinent mechanisms into models for industrial resource networks. The research is focused on reducing the environmental burden and cost associated with human activities involving industrial networks. The intention is provide substantive quantifiable metrics for the design of networks within the industrial domain. The project goal, to achieve a fundamental understanding of why the application of ecological principles and patterns leads to environmentally superior industrial resource networks, is grounded in specific tasks that progressively build the foundation of knowledge, culminating in verification through robust industrial case studies. The impact of the reduction of environmental burden through bio-inspired design of industrial networks promises to be significant. The use of case studies will enhance outreach to industrial sectors with win-win examples of industrial ecology. The project is designed to systematically build on established relationships including industrial partnerships and educational programs that bring together biology students and engineers and others.
Bruce K. Hamilton 2/24/10
Human industrial manufacturing systems continue to be non-cyclic and open loop, despite efforts to create more sustainable and resilient systems (e.g. Industrial Ecology). A persistent problem is that ecology, which provides a potential model for cyclic systems, has not been used a source of deep principles. The goals of this project were to develop methods and approaches for identifying deep ecological principles that can be used to organize industrial activity around manufacturing, determine the current characteristics of industrial system organization to examine areas of potential improvement, and develop "design rules" that provide practical ways to reorganize collections of industries (often called eco-industrial parks or EIPs). These investigations were based on how ecologists analyze the structural properties of ecosystems (food webs), and determine their capacity to cycle energy and materials internally. These methods of analysis were applied to EIPs, and structural metrics and performance properties of EIPs were derived in the same way they would for ecosystems. Using a large data set of EIPs constructed during this process, the properties of EIPs were compared to that of natural ecologies to identify differences. The resulting analysis suggested that internal cycling of EIPs does not correspond to that of natural systems, and that this is due to differences in how food webs vs. industrial webs are constructed. That is, the values of metrics that measure system properties are different in ecological and industrial networks. Further analysis of an existing carpet manufacturing and recycling network determined the effect of different food web metrics individually, and in groups, in order to find key ecological properties and metrics most predictive of resultant network efficiency. This analysis showed that a specific subset of ecological metrics adequately predicts the capacity of the carpet network to minimize material waste and energy costs. In fact, optimizing the network using ecological rules showed a remarkable correlation with traditional industry optimization (i.e., with respect to financial cost and environmental burdens). Investigations further developed a flow (rather than structural-based) analysis using methods from Environmental Network Analysis (ENA). The application of ENA to the best combination of structural food web metrics found led to a two-step optimization. Flow-based food web metrics derived from ENA were applied to the carpet manufacturing and recycling model to relate the behavior of these new metrics and analysis technique to the thoroughly investigated structural analysis done earlier. This provides a standard methodology going forward that can be used to optimize flow based networks in order to improve cycling efficiency and resilience. This method can, and is, being applied to a variety of industrial settings (e.g., automotive and steel industries, trade networks, city water-energy-transport systems) to determine how best to reorganize these human activities to increase sustainability and resilience. Moreover, these investigations have resulted in ecologists and engineers learning from each other to create a new way to investigate a complex and critical problem facing human society. Finally, showing that ecological principles provides ways to examine human systems points out the deep connections of humans to other species, and encourages society to revalue nature as a teacher, and not simply a physical resource or abstract but beautiful object.
