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Process to planet: A multiscale modeling framework toward sustainable engineering

doi: 10.1002/aic.14919
To prevent the chance of unintended environmental harm, engineering decisions need to consider an expanded boundary that captures all relevant connected systems. Comprehensive models for sustainable engineering may be developed by combining models at multiple scales. Models at the finest “equipment” scale are engineering models based on fundamental knowledge. At the intermediate “value chain” scale, empirical models represent average production technologies, and at the coarsest “economy” scale, models represent monetary and environmental exchanges for industrial sectors in a national or global economy. However, existing methods for sustainable engineering design ignore the economy scale, while existing methods for life cycle assessment do not consider the equipment scale. This work proposes an integrated, multiscale modeling framework for connecting models from process to planet and using them for sustainable engineering applications. The proposed framework is demonstrated with a toy problem, and potential applications of the framework including current and future work are discussed. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3332–3352, 2015
- University System of Ohio United States
- The Ohio State University at Marion United States
- The Ohio State University United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).40 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
