Numerical analysis of shock wave and supersonic turbulent boundary interaction between adiabatic and cold walls

ABSTRACT

Direct numerical simulations of shock wave and supersonic turbulent boundary layer interaction in a 24° compression ramp with adiabatic and cold-wall temperatures are conducted. The wall temperature effects on turbulence structures and shock motions are investigated. The results are validated against previous experimental and numerical data. The effects of wall cooling on boundary layer characteristics are analysed. Statistical data show that wall cooling has a significant effect on the logarithmic region of mean velocity profile downstream the interaction region. Moreover, the influence of wall temperature on Reynolds stress anisotropy is mainly limited in the near-wall region and has little change on the outer layer. As the wall temperature decreases, the streamwise coherency of streaks increases. Based on the analysis of instantaneous Lamb vector divergence, the momentum transport between small-scale vortices on cold-wall condition is significantly enhanced. In addition, spectral analysis of wall pressure signals indicates that the location of peak of low-frequency energy shifts toward higher frequencies in cold case. Furthermore, the dynamic mode decomposition results reveal two characteristic modes, namely a low-frequency mode exhibiting the breathing motion of separation bubble and a high-frequency mode associated with the propagation of instability waves above separation bubble. The shape of dynamic modes is not sensitive to wall temperature.

KEYWORDS:

• Shock wave/turbulent boundary layer interaction
• wall temperature
• turbulence structure
• shock motion
• dynamic mode decomposition

Acknowledgments

Thanks to Profs. Dexun Fu and Yanwen Ma in the Institute of mechanics, CAS, for their suggestions. This work is based on the research sponsored by the National Key research and Development Program of China (2016YFA0401200), the National Natural Science Foundation of China (Grant Nos. 91441103, 11372330 and 11472278) and Science Challenge Project (JCKY2016212A501). The authors would like to thank the National Computer Center in Tianjin (NSCC-TJ) and National Computer Center in GuangZhou (NSCC-GZ) and for providing computer time.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

National Key Research and Development Program of China [grant number 2016YFA0401200]; National Natural Science Foundation of China [grant number 91441103], [grant number 11372330], [grant number 11472278]; Science Challenge Project [grant number JCKY2016212A501].