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Acta Aeronautica et Astronautica Sinica ›› 2023, Vol. 44 ›› Issue (S2): 729429-729429.doi: 10.7527/S1000-6893.2023.29429

• Near Space Technology • Previous Articles     Next Articles

Uncertainty quantification of parameters in SST turbulence model for inlet simulation

Kailing ZHANG1(), Siyi LI1, Yi DUAN1, Chao YAN2   

  1. 1.Science and Technology on Space Physics Laboratory,China Academy of Launch Vehicle Technology,Beijing  100076,China
    2.School of Aeronautic Science and Engineering,Beijing University,Beijing  100083,China
  • Received:2023-08-10 Revised:2023-08-14 Accepted:2023-09-06 Online:2023-09-25 Published:2023-09-21
  • Contact: Kailing ZHANG E-mail:zhangkailingtt@163.com

Abstract:

The inlet, as one of the key components of the air-breathing high Mach number vehicle, is significant to the performance of the whole propulsion system. In the numerically simulated inlet flow for engineering applications, RANS (Reynolds Averaged Navier-Stokes) still plays an irreplaceable role. However, the turbulence model frequently used in RANS would affect the reliability of the numerical results due to its parameter uncertainty. The purpose of this paper is to carry out quantitative analysis on parameter uncertainty in the SST (Shear Stress Transport) turbulence model, and evaluate the influence on the inlet flow. The hysteresis loop of the inlet start performance was firstly predicted by the SST turbulence model, the uncertainty of QoIs (Quantity of Interests) caused by the parameter uncertainty was then quantified by Non-Intrusive Polynomial Chaos (NIPC) method, and the key parameters were identified by the sensitivity analysis for both the start and unstart states of the inlet. The results show that the uncertainty of model parameters leads to a large uncertainty in the prediction results of the shock wave structure for the inlet start state and the separation flow for the inlet unstart state, further resulting in a 10% non-negligible uncertainty of the inlet performance parameters. According to the parameter sensitivity analysis, σω1 and a1 are the key model parameters contributing most to the QoIs uncertainty.

Key words: turbulence model, inlet, hysteresis loop, uncertainty quantification, sensitivity analysis

CLC Number: