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A reduced-order model for fast predicting ionized flows of hypersonic vehicles along flight trajectory

Chinese Journal of Aeronautics 2024年第1期37卷 89-105页

作者： Jingchao ZHANG Chunsheng NIE Jinsheng CAI Shucheng PAN School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Space Physics Laboratory China Academy of Launch Vehicle TechnologyBeijing 100076China Institute of Extreme Mechanics Northwestern Polytechnical UniversityXi’an 710072China

An improved Reduced-Order Model(ROM)is proposed based on a flow-solution preprocessing operation and a fast sampling strategy to efficiently and accurately predict ionized hypersonic *** ROM is generated in low-dimensional space by performing the Proper Orthogonal Decomposition(POD)on snapshots and is coupled with the Radial Basis Function(RBF)to achieve fast prediction ***,due to the disparate scales in the ionized flow field,the conventional ROM usually generates spurious negative ***,this issue is addressed by performing flow-solution preprocessing in logarithmic space to improve the conventional ***,extra orthogonal polynomials are introduced in the RBF interpolation to achieve additional improvement of the prediction *** addition,to construct high-efficiency snapshots,a trajectory-constrained adaptive sampling strategy based on convex hull optimization is *** evaluate the performance of the proposed fast prediction method,two hypersonic vehicles with classic configurations,i.e.a wave-rider and a reentry capsule,are used to validate the proposed *** two cases show that the proposed fast prediction method has high accuracy near the vehicle surface and the free-stream region where the flow field is *** with the conventional ROM prediction,the prediction results are significantly improved by the proposed method around the discontinuities,*** shock wave and the ionized *** a result,the proposed fast prediction method reduces the error of the conventional ROM by at least 45%,with a speedup of approximately 2.0×105compared to the Computational Fluid Dynamic(CFD)*** test cases demonstrate that the method developed here is efficient and accurate for predicting ionized hypersonic flows.

关键词： Reduced-order model Radial basis function Constrained sampling Transfer function Fast flow prediction ionized hypersonic flows

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