Hybrid intelligent modeling approach for online predicting and simulating surface temperature of HVs

Abstract

Online prediction as well as online simulation of surface temperature will play a significant role in flight safety of future near space hypersonic vehicles (HVs). But it still remains a classical scientific problem both in thermodynamics and aerospace science. In view of the complex HV structure and complex heat conduction procedure, three-dimensional numerical simulation is too inefficient for online prediction, while current rapid computation methods cannot meet the requirement of accuracy. Therefore, a hybrid intelligent dynamic modeling approach is proposed to estimate the surface temperature of HV with the combination of mechanism equations, test data and intelligent modeling technology. A simplified model based on a mechanism equation and experimental formulas is presented for predicting or simulating transient heat conduction procedure efficiently, while a case-based reasoning (CBR) algorithm is developed to estimate two uncertain coefficients in the simplified model. Furthermore, a support vector regression (SVR)-based model is developed to compensate the modeling error. With the data both from high-precision finite element computation and from real-world HV thermal protection experiments, a number of comparative simulations demonstrate the effectiveness of the proposed hybrid intelligent modeling approach.