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Shock Trains Characteristic of Supersonic air Ejector

Weixiong Chen
State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China

Kangkang Xue
State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China

Yingchun Wang
State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China; Shanxi Institute of Energy, Taiyuan 030600, China

Gen Li
State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China

Daotong Chong
State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China

Junjie Yan
State Key Laboratory of Multiphase Flow in Power Engineering, School of Energy & Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, P. R. of China

DOI: 10.1615/TFEC2017.emi.017518
pages 1237-1244

要約

The supersonic ejectors involve complex phenomena, such as interaction between supersonic and subsonic flows, shock trains, instabilities and strong turbulence flow, which strongly influence the performance of supersonic ejector. Flow visualization techniques are essential to understand flow dynamics, and the Schlieren method has been applied to evaluate flow field in the present study, as well as CFD method. It finds that the Schlieren method could clearly represent the shock trains, including the first and second shock trains phenomena and the transformation process between the compression waves and expansion waves. As the primary pressure increases, the location of first shock train moves downstream. Meanwhile, as the back pressure rises, the location of first shock train moves upstream. Generally, it indicates that the ejector has a higher critical back pressure when the length of first shock trains increases. When there is no obvious demarcation line, the ejector is at sub-critical mode. Five different turbulence models are applied to simulate the internal flow filed. It could be concluded that RNG k-ε turbulence model has a good following features with the shock train characteristic, including the first shock train in the mixing tube and the second shock train in the diffuser. The result under RNG k-ε turbulence model could also well capture the shock position as primary pressure varies.

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