| Citation: | TAO Kaihang, ZHU Jianqin, CHENG Zeyuan. Calculation of thermophysical properties of supercritical RP-3 based on artificial neural network model[J]. Journal of Aerospace Power, 2023, 38（4）：806-815 doi: 10.13224/j.cnki.jasp.20220836
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In order to accurately obtain the thermophysical properties of RP-3 under supercritical pressure, the calculation models of density, viscosity, specific heat capacity at constant pressure and thermal conductivity of supercritical RP-3 were established based on artificial neural network （ANN） method. The RP-3 thermophysical properties obtained by the extended corresponding state were used to train the neural network, and the modified ANN model was obtained by coupling the experimental error model. The calculated temperature range was 300−800 K, and the pressure range was 3−6 MPa. The results showed that the ANN model can accurately predict the thermophysical properties of supercritical RP-3, and the calculation accuracy was 16.3% higher than that of the extended corresponding state. At the pressure of 5 MPa, the regression coefficients of density, viscosity, specific heat capacity at constant pressure and thermal conductivity predicted by the ANN model were all greater than 0.99. The mean relative errors with the experimental results were 1.5%, 4.1%, 0.9% and 0.7%, respectively.
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