Date of Graduation
Statler College of Engineering and Mineral Resources
Chemical and Biomedical Engineering
Fernando V. Lima
David S. Mebane
Stephen E. Zitney
Gerardo J. Ruiz-Mercado
Industry, government, and society have begun to shift from economic stand-alone focus to the inclusion of sustainability in the decision-making process. This shift can be attributed to the growing environmental and social awareness that makes consumers and stakeholders not only care about product quality and cost, but also products and processes that minimize the environmental impact and conserve natural resources. As a result, some progress has been made in recognizing and understanding the challenges of sustainable development, which helps evaluating the sustainability performance of a specific process/product. In particular, sustainability assessment tools and methodologies have been developed to help the future engineer and scientist with designing and optimizing the chemical processes in terms of sustainability. However, an efficient framework for the integration of advanced process control with sustainability assessment technologies is still missing.
In this dissertation, a novel process systems framework for integrating sustainability assessment, optimization, and advanced control is developed to simultaneously optimize and control chemical process systems at the optimal operating points considering efficiency, environmental, economic and energy aspects. This proposed framework bridges gaps in the literature by addressing the following challenges: 1) assessment of sustainability performance at steady-state and dynamic operations; 2) integration of sustainability indicators into a process control framework. Specifically, the proposed framework contains three main components: an integrated sustainability assessment tool, a multi-objective optimization formulation, and an advanced control strategy. The integrated sustainability assessment tool is developed using a user-friendly automation interface that enables the communication between process simulation, pollution control units (PCUs), life cycle inventory (LCI) generation, and the U.S. EPA’s GREENSCOPE (Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a Multi-Objective Process Evaluator) tool. With the sustainability indicators for chemical processes, a multi-objective optimization problem is formulated to identify the Pareto set of most sustainable operating conditions using a genetic algorithm for the decision-making step. To better balance the trade-off between economic and environmental aspects, a sustainable control strategy is implemented to drive the process to the chosen Pareto optimal solution while meeting pre-defined sustainability constraints. For the control implementation, a novel visualization method is developed to visualize the dynamic multidimensional sustainability indicators during transient.
To illustrate the effectiveness of the developed framework, two chemical processes are addressed: i) a continuous fermentation process for bio-ethanol production, for which the implemented sustainable process control scheme can improve the performance in terms of sustainability by 9.65% ~ 16.86% for different operating conditions; and ii) a biomass/coal co-gasification process for syngas production with the end goal of methanol manufacturing, for which the optimal sustainable operating condition is identified using a multi-objective optimization and then control is implemented to drive the system to the chosen setpoint, while maintaining the process within sustainable zones during transient. The performed case studies indicate that the proposed framework can be a powerful tool for assessing and controlling chemical processes for sustainability.
Li, Shuyun, "Development of a Sustainability Evaluation and Control Framework for Chemical Processes" (2019). Graduate Theses, Dissertations, and Problem Reports. 7382.