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This study explores application of a bees algorithm (BA) for economic optimal design of plate-fin heat exchangers. Therefore in this study, the optimization is targeting two single-objective functions separately. The first is the minimum heat transfer area which is mainly associated with the capital cost of the heat exchanger and the other is minimum total pressure drop that represents the operating cost for specific heat duty requirement under given space restrictions. Based on applications, heat exchanger length, fin frequency, numbers of fin layers, lance length of fin, fin height and fin thickness of the heat exchanger are considered for optimization. The constraints are handled by penalty function method. Also, the effectiveness and accuracy ofthe proposed algorithm is demonstrated through a case study. Comparing the results with the corresponding results using genetic algorithm (GA)and particle swarm optimization (PSO) algorithm reveals that the bees algorithm can converge to optimum solution with higher accuracy

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The purpose of this paper is to reach the maximum energy recovery or maximum cold stream outlet terminal temperature in a plate fin heat exchanger (PFHE) with constant volume and heat transfer area for a specified maximum pressure drop. This paper presents a methodology in surface selection and design of PFHE where full pressure drop utilization is taken as a design objective in constant heat exchanger volume and heat transfer area. Several kinds of PFHE with different fin type and geometries and different heat exchanger width, length and height could satisfy the constant volume and area condition. Setting maximum pressure drop could reduce these several heat exchangers. While the fin type and dimension of each heat exchanger is extracted due to constant volume-area and pressure drop conditions respectively, the terminal temperature of the heat exchanger would be calculated utilizing thermo-hydraulic modeling of the PFHE. A typical gas turbine regenerator is chosen as case study. The methodology is applied to this case study and results are shown. The surfaces which result maximum energy recovery are specified. In the cases that energy recovery of some surfaces would be approximately the same, other parameters such as frontal area and flow length will be considered