Design and optimization of a gas turbine regenerator with fixed pressure drop using GA and firefly algorithms
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Department of Mechanical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
Department of Mechanical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
Department of Biosystems Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
Ashkan Ghafouri   

Department of Mechanical Engineering, Ahvaz Branch, Islamic Azad University, Iran
Submission date: 2019-12-09
Final revision date: 2020-03-04
Acceptance date: 2020-03-10
Online publication date: 2020-10-15
Publication date: 2020-10-15
Journal of Theoretical and Applied Mechanics 2020;58(4):943–952
The present study investigates eight design parameters such as seal coverage, core porosity, core volume ratio, core thickness, dimensionless core rotation rate, inner diameter of the core, air mass flow rate and exhaust mass flow rate to design and optimize a regenerator of a 20-MW power generation gas turbine with fixed pressure drop. The application of GA and Firefly algorithms to optimize the effectiveness of the regenerator is presented to demonstrate the efficiency and accuracy of the proposed algorithms. The effect of change in the seal coverage, core porosity, core volume ratio and dimensionless core rotation rate are evaluated as important design parameters having influence on the size and mass of the core of the regenerator. This could be done through fixing each of these parameters, while the other seven design parameters are selected as variables to optimize the effectiveness. The results show that the selection of all eight-design parameters proposed as operating variables is necessary to optimize the parameters to achieve the proper design of this regenerator.
Akbari A., Kouravand S., Chegini G., 2018, Experimental analysis of a rotary heat exchanger for waste heat recovery from the exhaust gas of dryer, Applied Thermal Engineering, 138, 668-674.
Alhusseny A., Turan A., 2016, An effective engineering computational procedure to analyse and design rotary regenerators using a porous media approach, International Journal of Heat and Mass Transfer, 95, 593-605.
Beck D.S., 1995, A Compact Lightweight Gas-Turbine Regenerator, ASME.
Beck D.S., Wilson D.G., 1996, Gas-Turbine Regenerators, Springer, Boston, MA.
Chung H.J., Lee J.S., Baek C., Kang H., Kim Y., 2016, Numerical analysis of the performance characteristics and optimal design of a plastic rotary regenerator considering leakage and adsorption, Applied Thermal Engineering, 109, 227-237.
Holland J.H., 1975, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, Michigan; re-issued by MIT Press (1992).
Mioralli P.C., Ganzarolli M.M., 2013, Thermal analysis of a rotary regenerator with fixed pressure drop or fixed pumping power, Applied Thermal Engineering, 52, 187-197.
Mohanty D. K., 2016, Application of firefly algorithm for design optimization of a shell and tube heat exchanger from economic point of view, International Journal of Thermal Sciences, 102, 228-238.
Özdemir K., Serincan M.F., 2018, A computational fluid dynamics model of a rotary regenerative heat exchanger in a flue gas desulfurization system, Applied Thermal Engineering, 143, 988-1002.
Raja B.D., Jhala R.L., Patel V., 2016, Multi-objective optimization of a rotary regenerator using tutorial training and self-learning inspired teaching-learning based optimization algorithm (TS-TLBO), Applied Thermal Engineering, 93, 456-467.
Raja B.D., Jhala R.L., Patel V., 2018, Thermal-hydraulic optimization of plate heat exchanger: A multi-objective approach, International Journal of Thermal Sciences, 124, 522-535.
Raja B.D., Patel V., Jhala R.L., 2017, Thermal design and optimization of fin-and-tube heat exchanger using heat transfer search algorithm, Thermal Science and Engineering Progress, 4, 45-57.
Rao R.V., Patel V.K., 2010, Thermodynamic optimization of cross flow plate-fin heat exchanger using a particle swarm optimization algorithm, International Journal of Thermal Sciences, 49, 1712-1721.
Rao R.V., Patel V.K., 2013, Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm, Applied Mathematical Modeling, 37, 1147-1162.
Sanaye S., Jafari S., Ghaebi H., 2008, Optimum operational conditions of a rotary regenerator using genetic algorithm, Energy and Buildings, 40, 1637-1642.
Shah R.K., Sekulic D.P., 2003, Fundamentals of Heat Exchanger Design, John Wiley & Sons, Inc.
Wang L., Bu Y., Li D., Tang C., Che D.F., 2019, Single and multi-objective optimizations of rotary regenerative air preheater for coal-fired power plant considering the ammonium bisulfate deposition, International Journal of Thermal Sciences, 136, 52-59.
Wang S., Jian G., Xiao J., Wen J., Zhang Z., Tu J., 2018, Fluid-thermal-structural analysis and structural optimization of spiral-wound heat exchanger, International Communications in Heat and Mass Transfer, 95, 42-52.
Wen J., Gu X.,Wang M.,Wang S., Tu J., 2017, Numerical investigation on the multi-objective optimization of a shell-and-tube heat exchanger with helical baffles, International Communications in Heat and Mass Transfer, 89, 91-97.
Wu J., Liu S., Wang M., 2018, Process calculation method and optimization of the spiral-wound heat exchanger with bilateral phase change, Applied Thermal Engineering, 134, 360-368.
Yang X.S., 2008, Nature-Inspired Metaheuristic Algorithms, Luniver Press.