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Optimizing safety-constrained solvent selection for process systems with economic uncertainties
Authors:Ali El-Halwagi  Vasiliki Kazantzi  Mahmoud El-Halwagi  Nikolas Kazantzis
Institution:1. Texas A&M University, Department of Chemical Engineering, College Station, TX 77843-3122, USA;2. Technological Educational Institute of Larissa, Department of Project Management, Larissa 41110, Greece;3. The Chemical and Materials Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia;4. Department of Chemical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
Abstract:Solvents are very commonly used in industrial facilities for a multitude of reasons. Traditionally, solvent selection has been based on minimizing the process operating cost while satisfying a set of operational requirements. Regrettably, safety considerations have typically been overlooked during the design phase. In this paper, a systematic approach is introduced to integrate safety issues into solvent selection and provides a computationally effective method for establishing tradeoffs between the economic and safety objectives. In order to quantify the risk associated with the solvent, we focus on the potential spillage of the solvent and introduce a risk index that is a function of the amount of solvent used and stored, as well as the Permissible Exposure Limit (PEL) dictated by regulatory directives. An optimization formulation is developed and the associated mathematical program solved to select optimal solvents and blends while incorporating economic, technical, and safety considerations. Tradeoff (Pareto) curves are developed to represent the multi-objective optimization results and tradeoffs. Furthermore, economic-data uncertainty and variability over expected ranges are included in the optimization formulation to conduct an insightful sensitivity analysis. Finally, an illustrative case study is considered via increasing levels of complexity in order to evaluate the proposed optimization method which considers both operating cost and safety risk implications in the presence of economic uncertainties.
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