A conceptual framework will facilitate research across the four main areas of complexity highlighted by the figure below. Multi-scale boundaries range from nanometers in materials science and engineering (e.g., ECC design and testing) to kilometers in the geological and environmental sciences (e.g., life cycle modeling and evaluation). Multi-disciplinary expertise reflects the need for contributions from diverse academic disciplines, and collaboration with industry and government experts. Multi-criteria sustainability indicators encompass performance and evaluative criteria for judging design decisions (e.g., material durability, structural integrity, life cycle emissions and energy consumption, land use, human health impacts, and social and agency costs). Multi-project infrastructure applications including bridge decks, roadways and pipes pose unique challenges for sustainable design.
Integrated Materials Design Framework for Sustainable Infrastructure
The above figure demonstrates the challenge of sustainable design within these dimensions of complexity. Traditionally, process loops “A” and “B” have existed separately. Materials scientists and engineers have focused on a limited set of performance criteria in design activities within loop “A”, while industrial ecologists, economists and geologists have maintained a macro-level perspective for analyzing the life cycle of infrastructure systems within loop “B”. Prior to this work, no meaningful link has existed between these two loops. The proposed framework will ensure regular flows of information between these two loops, shown as “Material Design Integration” in the figure. ECC formulations developed in loop “A” are translated into material and energy inputs for life cycle analysis in loop “B”. The environmental, social and economic performance indicators developed throughout this process can be used to guide changes in material design in order to optimize system performance. This iterative design, evaluation, and re-design sequence fully addresses the four complexity dimensions, and it can be repeated until satisfactory solutions are reached.
University of Michigan
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October 16, 2006
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