Heat Flux Identification of Aircraft Structure with Artificial Neural Network Compensation

Abstract

Aerodynamic heating measurement of reusable hypersonic vehicles has always been an important aspect of hypersonic vehicle design. In this paper, a mechanistic-model-based heat flux identification method with artificial neural network (ANN) compensation is established to determine the spatially distributed heat flux of the aircraft structure. A one-dimensional heat conduction model is used to estimate heat flux by a robust and efficient algorithm integrating Tikhonov regularization with Levenberg–Marquardt method. The one-dimensional estimated heat flux has large errors for not considering multidimensional heat conduction effects. The proposed mechanistic-model-based method is then utilized to compensate the multidimensional heat conduction by ANN. The performance of the proposed method will be assessed by the determination of the heat flux of a two-dimensional plate and aircraft structure. Results show that compared with the one-dimensional inversion results, ANN compensation method can significantly improve the accuracy of estimated heat flux and is also applicable for larger levels of heat flux. The proposed compensation method is an effective technique to identify the nonuniform surface heat flux of multidimensional structures.