Optimization design with an advanced genetic algorithm for a compact air-air heat exchanger applied in aero engine

Abstract

This work presents an optimal design method for a compact air-air serpentine tube heat exchanger (STHE), which is applied as the core component of the bearing sealing cooling system in the aero engine. A new optimization tool, coupling with the Logarithmic Mean Temperature Difference (LMTD) method and an advanced genetic algorithm (AGA) using Gray code, is proposed to optimize the STHE with unknown outlet parameters under variable working conditions. Under the given performance and structural constraints, six optimization design variables, including tube outer diameter, the transverse tube pitch, the longitudinal tube pitch, the transverse tube rows, the height and the number of elbows, are selected to obtain the maximum heat transfer capability KA per total weight. The optimization results show that, by using AGA, the target parameter distribution is narrowed from 88.31~93.86 kW/(K•kg) to 91.90~93.92 kW/(K•kg), and the proportion of the optimal solutions higher than 93 kW/(K•kg) increases from 22.62% to 94.32%. The optimization also improves the heat transfer capability KA per total weight to 93.92 kW/(K•kg), comparing with the original value of 70.08 kW/(K•kg). As the key limiting factors, the hot side maximum outlet temperature and pressure drop in the optimized STHE do not appear at the same operation mode and both of them are quite close to the given limits. It well demonstrates the validity and applicability of the proposed optimization design method using under multiple restrictions and conditions.