Performance optimization of a printed circuit heat exchanger for the recuperated gas turbine

To further improve the thermal efficiency of gas turbines, the recuperator needs to be employed and the printed circuit heat exchanger with airfoil fins meets the recuperator's requirements of high heat transfer capacity, low flow resistance, and high reliability. However, the effect of airfoil fin pitches is not clear and the structure optimization method should be developed. In this study, the heat transfer quantity and pressure drop per length of the flue gas in the airfoil channels are numerically investigated under different Reynolds numbers and airfoil fin pitches. The results show that the effect of the airfoil transverse pitch has a great effect on the performance of the flue gas and the heat transfer quantity is increased by 82.39 %–96.08 % when the transverse pitch is decreased from 6.0 mm to 1.2 mm. At the same time, the pressure drop per length is increased to 189.39–842.47 Pa/m. The heat transfer performance is varied not obviously when the airfoil longitudinal pitch is varied from 4 mm to 15 mm. Based on the numerical data, the multiple-objective genetic algorithm combined with the backpropagation neural network is proposed for the performance predictions and optimizations. The corresponding Pareto front is obtained and the technique for order preference by similarity to the ideal solution method is employed to obtain the optimal point. Under the current conditions, the heat transfer quantity of the optimal point is 521.25 kW/m 2 , which is decreased by 34.5 % compared to the highest value, and the pressure drop per length of the optimal point is 108.45 Pa/m, which is decreased by 85.2 % compared to the highest value.