Geneitc algorithm based design and optimization of an outer-fins and inner-fins tube heat exchanger

One of passive enhancement techniques, Extended Surfaces, are commonly employed in many heat exchangers to enlarge the heat transfer area on gases side because of the low heat transfer coefficients, which may be 10 to 100 times smaller than those of liquids side. The use of extended surfaces (or referred to as finned surfaces) will reduce the thermal resistance of gases side. Enhanced heat transfer coefficient will be achieved by using the basic Surface geometries: plate-fin and tube-fin. With respect to the tube-fin type heat exchanger, fins may be employed outside tubes (herein called outer-fins) to enhance the heat transfer of shell-side, and alternatively fins may be also employed inside tubes (herein called inner-fins) to increase the intensity of heat transfer Of tube-side. The desire to accomplish the gas-to-gas heat exchange through the tubular heat exchangers will lead to develop heat transfer enhancement techniques for outside and inside tubes. Therefore based on integration with Such two mechanisms, namely, outer-fins and inner-fins of enhancement heat transfer techniques, a kind Of outer-fins and inner-fins tube heat exchanger has been preliminary proposed (ASME-IGTI, Paper No.2006-90260 [20]). Such heat exchanger is potentially used in gas-to-gas heat exchangers, especially used for high-pressure operating conditions, where the plate-Fin heat exchangers might not be applicable. In general, the design task is a complex trial-and-error process and there is always the possibility that the design results Such as geometrical parameters are not the optimum. Therefore, the motivation of this paper is to conduct Optimum designs Of Such heat exchanger (hereafter called Outer-Fins and Inner h-ins tube Heat Exchanger, OFIF HE). A computational intelligent technique, Genetic Algorithm (GA) is applied to search and optimize geometrical parameters of the OFIF HE. The minimum total Volume or minimum total annual cost of such OFIF HE is taken as an objective function in the GA respectively. The results show that the optimized OFIF HE provides lower total Volume or lower total annual cost than those presented in previous work. The method is universal and may be used for design and optimization of OFIF HEs under different specified duties and design objectives.