Improved jet noise modeling using a new time-scale.

Area of Science:

• Fluid Dynamics
• Acoustics
• Computational Fluid Dynamics

Background:

• Calculating turbulent flow noise requires understanding unsteady flow characteristics, including correlation tensors and time-scales.
• Reynolds-Averaged Navier-Stokes (RANS) calculations provide steady-state flow data, necessitating modeling for unsteady behavior.
• Existing models focus on correlation tensor forms, often neglecting the physics governing time-scale selection.

Purpose of the Study:

• To propose a new method for obtaining the time-scale in turbulent flows.
• To investigate the underlying physics dictating the proper choice of time-scale.
• To improve the accuracy of noise prediction from turbulent flows.

Main Methods:

• Utilized isothermal single-stream flow jets at Mach numbers 0.75 and 0.90.
• Employed the Mani-Gliebe-Balsa-Khavaran method for noise prediction.
• Developed and applied a novel approach for determining the time-scale based on underlying physics.

Main Results:

• The proposed new time-scale method shows good agreement between predicted and observed noise levels.
• The new time-scale possesses inherent frequency dependency derived from physical principles.
• This natural frequency dependency eliminates the need for supplementary mathematical enhancements.

Conclusions:

• The novel time-scale determination method enhances the accuracy of acoustic analogy-based noise prediction.
• The physically derived, frequency-dependent time-scale offers a more robust approach to modeling unsteady turbulence.
• This research contributes to more accurate noise modeling in turbulent flows, particularly for jet acoustics.