Neural network model for fast prediction of infrared radiation of turbofan engine with axisymmetric exhaust system in preliminary design phase - Feng Wang; Honghu Ji; Haoying Chen; Xinlei Chen; Mingxin Wang; Xiaojuan Shi (Case Studies in Thermal Engineering, 2025)
It is widely agreed that the infrared stealth should be considered in the preliminary design phase of turbofan engine so as to decrease the infrared radiation of engine exhaust system. In the present study, a turbofan engine with afterburner at small bypass ratio (0.44, 0.5) in the flight envelope (altitude h < 12.8 km, Mach number M < 1.5) was studied, in which afterburner state was not taken into account. The design method of geometrical model of the exhaust system at the preliminary design phase was developed, and the Latin hypercube sampling method was used to design sample cases, which were numerically simulated to study the infrared radiation characteristics of the exhaust system at different inlet parameters of the exhaust system. A neural network model was developed to predict the infrared radiation of the exhaust system, in which the inlet parameters of the exhaust system in the flight envelope were applied as input parameters. Results show that the maximum error of the developed neural network model for predicting infrared radiation characteristics is less than 10 %, which can be used to evaluate the infrared radiation characteristics of the exhaust system at the preliminary design phase of turbofan engine.