Optimization of the aero-engine thermal management system with intermediate cycle based on heat current method

Reliability and efficiency of the aero-engine thermal management system (ATMS) is of great importance to ensure the required working condition. Conventional methods on modeling ATMS are complex and difficult to solve for optimizing the whole system under multiple conditions. This study combines the heat current method and artificial neural network (ANN) to develop the optimization models with the objectives of maximum heat transfer rate and minimum thermal conductivity respectively. The ATMS experimental platform with interme-diate cycle using water as the simulated medium is constructed to verify the optimization reliability. After optimization, the maximum heat transfer rate of ATMS is increased from 7740 W to 8402 W by 8.6%. The minimum thermal conductivity decreases from 1628 W/K to 1032 W/K by 36.6% comparing with the initial working condition. While considering the conditions of artificial control on the fuel oil side, the optimal thermal conductivity decreases from 1628 W/K to 1101 W/K by 32.3%. The optimal findings provide powerful guidance for improving the heat dissipation and reducing weight of the aircraft.