An efficient method to predict thermal loads on hypersonic vehicles in rarefied flows is immediately needed, especially when designing the thermal protection system. To meet the demand, we combine artificial neural networks with the direct simulation Monte Carlo method and build the surrogate model for hypersonic rarefied flows with three inputs (Knudsen number, temperature ration, and Mach number). The heating coefficients at nine points along the surface of a two-dimensional cylinder are output from the model. The results at the stagnation point have errors within 3%, while the biggest error of nine points is 4.8%. The heating coefficients are also compared with the bridge function’s, whose errors reach 14% at the stagnation point and 20% along the surface. The reasons for the errors are discussed in detail. In addition, this framework of building the model with artificial neural networks can be extended to solve problems with more complex mechanisms or configurations.
This work investigates the variations of the stagnation point heat flux (SPHF) in hypersonic cylinder flows using the direct simulation Monte Carlo method, with the consideration of a constant freestream Knudsen number but different cylinder diameters. Four different freestream Mach numbers and the accompanying chemical reactions are considered. The result reveals a high-density effect in chemical reactions inside the thermal boundary layer, which induces an increasingly rising SPHF with a decreased cylinder diameter for all the cases. The cases at Ma∞ = 30 exhibit a characteristic of peculiarity that the value of SPHF increases the fastest, which is strongly correlated with the different high-density effects at different Ma∞. Further analysis demonstrates that the NO dissociation and recombination reactions always play a vitally important role in the high-density effect. A secondary NO dissociation reaction was observed inside the thermal boundary layer when Ma∞ > 30. This observation is the result of the shift of chemical equilibrium induced by violent recombination reaction and sufficiently high flow temperature. Subsequently, the newly emerging secondary dissociation reaction weakens the influence of recombination reaction; thus, the growth of SPHF at a high Mach number is not so strong as that with Ma∞ ≤ 30. Furthermore, in order to provide more reliable results, additional simulations are discussed by employing the widely accepted total collision energy and catalytic surface reaction models.
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