Abstract

Sizing an air-cooled heat exchanger requires tedious, time-consuming calculations to balance air and liquid heat-transfer properties according to the temperature requirements. There are some constraints to make the design better. The airside pressure drop (ΔPa) and the number of heat transfer units (NTU) are two of them. The minimum ΔPa requires the minimum fan power. As a result of this the operational cost can be minimized. In some environmental conditions the noise can be minimized too. NTU includes the size of the heat exchanger and fluid heat transfer capacities. It is very important for producer to drop the cost of production and logistic. Imagining the transport of hundreds goods make us understand the importance of this parameter easily. There are a lot of work in literature to make the design of air-cooled heat exchanger easy. But most of them have irreversible calculations and all the calculations should be carried out many times till getting the acceptable results. These trial and error calculation require much time. To overcome such difficulties, today, in many engineering problems there is a mass application of heuristic algorithms. The most common of these is genetic algorithms. The design of an optimum heat exchanger is a formidable challenge for designers. First, such a design involves a large number of parameters to be optimized. It is almost impossible to find an optimum design by the traditional “trial and error” method. Second, design is usually a multi objective and multi-point problem that simultaneously has to content with a variety of design criteria. In this study, we obtained accurate and robust answers in a few minutes by developping a computer code using genetic algorithm. It is also possible to find the optimum size of any heat exchanger by making required changes in the code according to the type of heat exchangers.

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