Flow maldistribution in the inlet of the plate-fin heat exchanger along the longitudinal direction affects heat transfer among different layers. Nowadays experimental methods are used to determine the parameters of the leading flow structure

however

optimization of these parameters has not been reported yet. A new multi-objective optimizing method was proposed based on traditional leading flow structure. Considering the factors influencing fluid distribution in the inlet of the plate-fin heat exchanger

including diameter

space and number of hole on the leading flow structure

fluid velocity

location of the leading flow structure in the inlet of the exchanger and inlet diameter of the exchanger

the multi-objective optimizing models of pressure drop and heat transfer per unit time were established. Orthogonal experiment was conducted to create the simulation model and deduce non-linear mapping equations of the leading flow structure. The leading flow structure was optimized using back propagation network (BP) combined with genetic algorithm and the final parameters of the structur were determined. Fluid flow and distribution in the inlet of the plate-fin heat exchanger before and after optimization were simulated using the commercial software

Fluent

and were compared with those without the leading flow structure. The leading flow structure after optimization could improve fluid distribution along the longitudinal direction obviously

and meanwhile

improve heat transfer and enhance performance of the exchanger.