Abstract
In this work, by adopting dynamic mesh technology along with the spring based smoothing method and the laying based zone moving method, we have numerically solved the axisymmetric N-S equations, analyzed the flow field mechanism and thermal shock characteristics, identified the thermal environment evaluating and influencing factors that are essential for dealing with problems in decision making of the new land-based concentric canister launcher (CCL) under the high-speed thermal shock load condition, and determined the evaluation index of the thermal environment. The mathematic model was established by optimal Latin hypercube design and radial basis function neural network (RBFNN), thus greatly facilitating the automatic modeling and compensating for the large amount of calculation for CFD. The intelligent decision research of the influencing factors for the missile thermal environment was performed using the RBFNN training method. The numerical results show that the thermal environment of the internal canister and the external cylinder are improved by the cryogenic gas coming from the cylinder port; the approximate model is accurate enough to meet the engineering standards required; the influencing factors for the missile thermal environment load are, according to their ranking from high to low, are the following: The diameter of the cylinder bottom baffle plate, the length of the cylinder bottom baffle plate, the height of the deflector. The research of the influencing factors will lay a solid foundation for the multidisciplinary optimization of the thermal environment.
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