Abstract
This study employed a genetic algorithm technique to examine and predict how shell-and-tube heat exchangers’ performance regarding heat recovery could be improved. In particular, a multi-objective energy-based optimization algorithm was employed. Two major parameters that were investigated in relation to their potential moderating effect included cost and energy efficiency. Regarding the cost, the study examined specific parameters such as operating cost (energy expenditure accruing from pumping) and equipment capital spending (the surface area of the heat exchanger). Regarding the design parameters, issues that were analyzed included baffle cut ratio, baffle spacing ratio, tube length, tube pitch ratio, tube diameters, and tube arrangement. To ensure that an optimal heat exchange was designed, aspects of the coefficient of heat transfer and pressure drop were estimated using Bell-Delaware procedure and the ε – NTU method. To ensure that minimum total cost, minimum energy destruction, and maximum energy efficiency were obtained, NSGA-II algorithm was applied. In turn, Pareto optimal solutions were reported in the results. From the findings, it was evident that two objective functions conflicted and that a change in geometrical properties would decrease the exergy destruction (or increase the exergy efficiency), leading to increased total cost. In exergy destruction, the heat exchanger optimization relative to exergy analysis indicated that irreversibility such as high temperature differences between the cold and hot steam and pressure drop affect the nature of exergy destruction. As such, it was concluded that when the heat exchanger’s component efficiency is increased, its cost increases.
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