473748 Process to Planet Framework for Sustainable Design: Systematic Approach for Developing a Multiscale Model and for Multiobjective Optimization
This presentation proposes extensions and modifications that address some of the inadequacies that are inherent in the original P2P framework. While strictly applied to P2P, these extensions can be extrapolated to answer challenges that exist in broad areas of literature, like HLCA. The selection of significant processes that are modeled at the process based life cycle scale and the insignificant processes that are studied at the economy scale is arbitrary. In other words, delineation of the boundary between the different scales of the P2P framework was a subjective task. Previously, this was done based on data availability, accuracy and detail requirements and the complexity of the overall problem which is proportional to the solving time [5,6]. The problem was first mentioned and some methods were proposed for addressing it in a paper by Suh . Lenzen proposed Structural Path Analysis (SPA) involving the decomposition of the Leontief Inverse for addressing this problem . Treloar also used this method to study energy use of individual residential buildings in Australia [9,10]. Lave et al.  and Lenzen  used SPA to quantify the truncation errors in process-based LCA. A path exchange method using SPA was also developed as an alternative to the method of combining process LCA and IO LCA within integrated hybrid LCA as proposed by Suh. We intend to address this knowledge gap by proposing a path analysis algorithm where the P2P framework superstructure model generation is guided by a hierarchical structural path decomposition method which determines the coverage of the different scales. It is one of the first applications of SPA for solving the boundary selection problem involving the distribution of different upstream processes between multiple scales.
A large number of studies have dealt with multi objective optimization in process design and energy systems involving environmental and economic impacts. A comprehensive list of such literature can be found in Diwekar et al. Reviewing these articles, it becomes apparent that it is necessary to simultaneously work towards both economic profitability and environmental sustainability of the system. Previously, the P2P framework focused only on the environmental dimension of process design. In this work, we propose a multi objective optimization problem, involving the trade-off between an economic objective and an environmental objective function. The novelty in this addendum is that it makes the P2P framework more fruitful for designing any generic process while exercising control over both the economic and environmental scope.
Preliminary results have provided insightful views on the application of SPA algorithm for model generation as well as exposed existing deficiencies to work on. While SPA is successful in mapping the upstream networks of the process to be designed and calculate their contributions to the entire life cycle, the quantification of the quality of the generated model still needs to be addressed. For example, considering two scenarios where an upstream sector is modeled at the IO model scale and process LCA scale respectively, we need to develop parameters that can quantitatively compare between the two cases and rank them objectively. As of now, subjective decisions are being used to build the model, but we intend to develop an algorithm based on error analysis or uncertainty information to determine the model quality. Multiobjective optimization solutions demonstrated that, highly erroneous optimal solutions and counter intuitive results are obtained from practicing conventional SPD approach rather than P2P. In addition to this, it was observed that there is a 59% chance of choosing an inferior solution over the optimal solution when solving the design problem using conventional SPD.
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