导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA

    Next Articles

Rapid Predicting of Global Hypersonic Vehicle Aerothermodynamics Based on Adaptive Sampling

Guo-Tao YANG1,Zhen-Jiang YUELi LIU   

  • Received:2022-05-09 Revised:2022-09-27 Online:2022-09-30 Published:2022-09-30
  • Contact: Zhen-Jiang YUE

Abstract: High-fidelity aerothermodynamics analysis models in the thermal protection system of the hypersonic vehicles sig-nificantly increase the computational budget of engineering design, thus rapid predicting methods based on data-driven have been widely concerned recently. In this paper, a batch adaptive sampling method based on fuzzy clus-tering is proposed, aiming at improving the global prediction accuracy with the limited computational budget of high fidelity models. The sampling influence domain is constructed by clustering and hypersphere segmentation under the distribution characteristics of the predicting error, which takes into account the key sampling domain with larger error and exploration. The sampling refused domain is constructed by local error scoring coefficient weighted to reduce the redundancy of newly adding samples. The method adds new samples in the comprehensively deter-mined key sampling space to improve the sampling quality based on maxmin criterion, thereby the global accuracy of the predicting models have been improved rapidly. The comparison results show that the proposed method out-performs One-Shot, APSFC and CV–Voronoi in terms of reducing the sampling scale required and speeding up to improve predicting accuracy. The rapid predicting results of HTV-2 typed vehicle aerothermodynamics demon-strates the practicality and effectiveness of the proposed method in engineering practices.

Key words: adaptive sampling, fuzzy clustering, rapid predicting, hypersonic, aerothermodynamics

CLC Number: