Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II
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College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
2
Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3
School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(10), 1065; https://doi.org/10.3390/e22101065
Received: 24 July 2020
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Revised: 19 September 2020
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Accepted: 19 September 2020
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Published: 23 September 2020
(This article belongs to the Special Issue Finite-Time Thermodynamics)
Based on the theory of finite-time thermodynamics (FTT), the effects of three design parameters, that is, inlet temperature, inlet pressure, and inlet total mole flow rate, of a tubular plug-flow sulfuric acid decomposition reactor on the total entropy generation rate (EGR) and SO2 yield are analyzed firstly. One can find that when the three design parameters are taken as optimization variables, the minimum total EGR and the maximum SO2 yield of the reference reactor restrict each other, i.e., the two different performance objectives cannot achieve the corresponding extremum values at the same time. Then, the second-generation non-dominated solution sequencing genetic algorithm (NSGA-II) is further used to pursue the minimum total EGR and the maximum SO2 yield of the reference reactor by taking the three parameters as optimization design variables. After the multi-objective optimization, the reference reactor can be Pareto improved, and the total EGR can be reduced by 9% and the SO2 yield can be increased by 14% compared to those of the reference reactor. The obtained results could provide certain theoretical guidance for the optimal design of actual sulfuric acid decomposition reactors.
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Keywords:
finite-time thermodynamics; sulfuric acid decomposition; tubular plug-flow reactor; entropy generation rate; SO2 yield; multi-objective optimization
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MDPI and ACS Style
Sun, M.; Xia, S.; Chen, L.; Wang, C.; Tang, C. Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II. Entropy 2020, 22, 1065. https://doi.org/10.3390/e22101065
AMA Style
Sun M, Xia S, Chen L, Wang C, Tang C. Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II. Entropy. 2020; 22(10):1065. https://doi.org/10.3390/e22101065
Chicago/Turabian StyleSun, Ming, Shaojun Xia, Lingen Chen, Chao Wang, and Chenqi Tang. 2020. "Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II" Entropy 22, no. 10: 1065. https://doi.org/10.3390/e22101065
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