Process to Planet Approach to Sustainable Process Design: Multiple Objectives and Byproducts

Полный текст

Открытый доступ Открытый доступ
Доступ закрыт Доступ предоставлен
Доступ закрыт Только для подписчиков

Аннотация

While standard life cycle assessment methods exclude fundamental process engineering models in its analysis, sustainable process design (SPD) is plagued by the dilemma of boundary selection that results in consideration of incomplete life cycles and shifting of emissions outside the system boundary. The Process to Planet (P2P) framework bridges this gap by combining sustainable process design with environmentally extended input output analysis. This framework extending across multiple scales provides the capability of working with process variables and designing processes at the equipment scale while considering the entire life cycle through the supply chain and economic scale models. This work expands the P2P framework to account for byproducts originating from any unit within the model. The framework is further modified to incorporate an economic objective function, henceforth developing a multiobjective (MO) optimization problem for optimal design of any generic industrial process. The modified P2P framework is demonstrated by application to a corn ethanol manufacturing process case study. The MO problem is solved using the epsilon constraint method to obtain Pareto optimal frontiers that reveal the trade-off between environmental and economic dimensions of the sustainable process design problem. Comparison between commonly practiced conventional SPD and P2P SPD Pareto curves exposes the chance of choosing non optimal solutions if the former method is employed.

Об авторах

Tapajyoti Ghosh

William G. Lowrie Department of Chemical and Biomolecular Engineering

Email: bakshi.2@osu.edu
США, Columbus, OH, 43210

Bhavik Bakshi

William G. Lowrie Department of Chemical and Biomolecular Engineering

Автор, ответственный за переписку.
Email: bakshi.2@osu.edu
США, Columbus, OH, 43210

Дополнительные файлы

Доп. файлы
Действие
1. JATS XML

© Pleiades Publishing, Ltd., 2017

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).