Multivariate Optimization of a Jacketed Heating System: A Genetic Algorithm Approach
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International Journal of Recent Engineering Science (IJRES) |  |
| © 2021 by IJRES Journal | ||
| Volume-8 Issue-2 |
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| Year of Publication : 2021 | ||
| Authors : Mahlon Marvin Kida, Zakiyyu Muhamad Sarkinbaka |
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| DOI : 10.14445/23497157/IJRES-V8I2P104 |
How to Cite?
Mahlon Marvin Kida, Zakiyyu Muhamad Sarkinbaka, "Multivariate Optimization of a Jacketed Heating System: A Genetic Algorithm Approach," International Journal of Recent Engineering Science, vol. 8, no. 1, pp. 20-25, 2023. Crossref, https://doi.org/10.14445/23497157/IJRES-V8I2P104
Abstract
Many industrial processes involve the heating or cooling of fluids, and as such, it is important to figure out ways and synopsis that could effectively determine operating conditions for a desired optimum process output. In this paper, a fluid heating jacketed system was studied. The model of the jacketed heater was derived in its steady-state form for the purpose of sensitivity study in Fortran. The sensitivity study was carried out on the heater's fluid density, heat capacity, cross-sectional area, volume, and jacket output temperature. An optimization was employed using a Genetic algorithm to determine the optimum parameters of the heating system.
The sensitivity investigation verified that the variation of density, area, and heat capacity was more effective in the performance of the jacketed heating system. An increase or decrease of these process parameters will increase or decrease the heating system's temperature, respectively. The variation in the volume was insignificant in terms of temperature.
The optimization results verified the optimum values of the parameters, as shown in Table 1. The density and heat capacity of the fluid(water) in the jacket produced an optimum temperature of 500K, while that of the fluid in the tank produced an optimum temperature of 349.99K.
Keywords
Jacketed Heating System, Genetic Algorithm, Sensitivity study, MATLAB, Fortran Language.
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