Experimental study on the wall-pressure fluctuations of flow over an axisymmetric hull

Abstract

Wall pressure fluctuations beneath the turbulent boundary layer of high-speed underwater vehicles are crucial for hydro-acoustics and acoustic stealth. However, a comprehensive understanding remains limited due to a lack of high-quality experimental data, particularly under realistic operational conditions. To address this gap, this study establishes the first high-fidelity experimental database of wall-pressure fluctuations on an axisymmetric hull at high Reynolds numbers. The dataset's primary innovation is its systematic inclusion of complex maneuvering (yaw and pitch) conditions, providing a benchmark for validating flow noise prediction models. Analysis of this dataset yields key physical insights. The study quantifies systematic Reynolds number effects, including a spectral energy shift toward lower frequencies, and spectral scaling laws by revealing the critical influence of pressure-gradient effects. These findings provide fundamental insights into non-equilibrium 3D turbulent flows and establish an essential dataset to support the design of quieter and more effective underwater vehicles.

Figures (15)

• Figure 1: Schematic of the experimental setup: (a) installation of the axisymmetric hull in the high-speed test section of the Shanghai Jiao Tong University wind tunnel; (b) lateral view showing Section A-A and the location of the temperature and humidity (TH) sensor; (c) arrangement of measurement points along the hull's top meridian line. Square symbols denote wall-pressure fluctuation sensors; circles denote static pressure sensors.
• Figure 2: Photographs of the experimental setup: (a) the model installed in the wind tunnel, viewed from upstream looking downstream; (b) detailed view of the wall-pressure fluctuation sensor; (c) detailed view of the static pressure sensor.
• Figure 3: Photographs of (a) the CYG1506G-P4LS12C2 1/4 inch pressure-field microphone with pinhole, (b) the calibration process using the HBK 9721-A acoustic sensor calibration system, and (c) the measurement of facility noise.
• Figure 4: The calibrated frequency response of the pinhole resonator compared with the fitting model given by Eq. \ref{['eq:fitting model']}.
• Figure 5: (a) Step-by-step processing of the wall-pressure signal from the flat-plate TBL experiment at $U_\infty = 30$ m/s: $p_1$, original signal; $p_2$, after noise cancellation; $p_3$, after microphone calibration; $p_4$, averaged PSD. (b) Comparison of the averaged PSD ($p_4$) with data from Joseph2020JFMPlate.