Turbulent-nonturbulent interfaces in spatially developing compressible turbulent boundary layers

Area of Science:

• Fluid Dynamics
• Turbulence Research
• Computational Fluid Dynamics

Background:

• The turbulent-nonturbulent interface (TNTI) is a critical region in turbulent flows, influencing mixing and drag.
• Understanding the TNTI's structure and dynamics is essential for accurate modeling of spatially developing turbulent boundary layers.
• Previous research has provided insights, but detailed analysis of compressible boundary layers remains an active area.

Purpose of the Study:

• To investigate the characteristics of the turbulent-nonturbulent interface (TNTI) in spatially developing compressible turbulent boundary layers.
• To quantify the mean thicknesses of the TNTI layer and its components (viscous superlayer and turbulent sublayer).
• To analyze the interscale energy transfer mechanisms across the TNTI in different directions.

Main Methods:

• Direct numerical simulation (DNS) was employed to capture the fine-scale structures of the turbulent flow.
• Analysis focused on the mean thicknesses of the TNTI, viscous superlayer (δ_{VSL}), and turbulent sublayer (δ_{TSL}).
• Multiscale analysis was used to examine interscale energy transfer (T_{r_{1}} and T_{r_{2}}) normal and tangential to the interface.

Main Results:

• The mean TNTI layer thickness (δ_{TNTI}) was found to be approximately 13η_{ref}, with δ_{VSL} ≈ 3.6η_{ref} and δ_{TSL} ≈ 9.4η_{ref}.
• Interscale energy transfer normal to the TNTI (T_{r_{1}}) occurred from large to small scales.
• Energy transfer normal to the interface (T_{r_{2}}) showed an opposite trend, from small to large scales, with distinct behaviors in tangential directions.

Conclusions:

• The study provides detailed quantitative data on the structure and energy transfer dynamics of the TNTI in compressible turbulent boundary layers.
• The findings offer valuable insights into the multiscale nature of energy transfer at the turbulent-nonturbulent interface.
• These results are expected to aid in the development of more accurate models for predicting spatially developing turbulent flows.