Abstract
Based on the thermohydraulic calculation model verified in this study and Non-dominated Sorted Genetic Algorithm-II (NSGA-II), a multi-objective configuration optimization method is proposed, and the performances of shell-and-tube heat exchanger with disc-and-doughnut baffles (STHX-DDB) and shell-and-tube heat exchanger with segmental baffles (STHX-SB) are compared after optimization. The results show that, except in the high range of heat transfer capacity of 16.5–17 kW, the thermohydraulic performance of STHX-DDB is better. Tube bundle diameter, inside tube bundle diameter, number of baffles of STHX-DDB and tube bundle diameter, baffle cut, number of baffles of STHX-SB are chosen as design parameters, and heat transfer capacity maximization and shell-side pressure drop minimization are considered as common optimization objectives. Three optimal configurations are obtained for STHX-DDB and another three are obtained for STHX-SB. The optimal results show that all the six selected optimal configurations are better than the original configurations. For STHX-DDB and STHX-SB, compared with the original configurations, the heat transfer capacity of optimal configurations increases by 6.26% on average and 5.16%, respectively, while the shell-side pressure drop decreases by 44.33% and 19.16% on average, respectively. It indicates that the optimization method is valid and feasible and can provide a significant reference for shell-and-tube heat exchanger design.
Highlights
Shell-and-tube heat exchanger (STHX) is one kind of mechanical device that can exchange heat through a tube wall between two fluids of different temperatures, which are widely used in oil cooling in aero-engines, heating, chemical and food industries, and so on [1]
In order to validate the accuracy of thermohydraulic calculation model, calculation results are
Based on the thermohydraulic calculation model verified in this paper, the effects of design parameters are analyzed
Summary
Shell-and-tube heat exchanger (STHX) is one kind of mechanical device that can exchange heat through a tube wall between two fluids of different temperatures, which are widely used in oil cooling in aero-engines, heating, chemical and food industries, and so on [1]. In the process of heat exchanger design, different configuration parameters can lead to different performances. In order to obtain the better performances, heat exchanger optimization is increasing significantly [2]. In the pursuit of optimized designs, configuration optimization as well as optimization methods application have been analyzed from different points of view. The genetic simulated annealing algorithm [3], biogeography-based algorithm [4], firefly algorithm [5], Jaya algorithm [6] and differential evolution algorithm [7] were used to minimize the cost of the heat exchanger. In the actual design process of the heat exchanger, total cost minimization is not the only objective. Many other objectives need to be considered, just like heat transfer capacity maximization, pressure drop
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