Improving Acoustic Measurements with Cavities in Closed Test Section Wind Tunnels

Colin VanDercreek

Research output: ThesisDissertation (TU Delft)

115 Downloads (Pure)

Abstract


Aerodynamic noise produced by aircraft, wind turbines, and other objects subjected to airflow contribute to environmental noise pollution, which adversely affects human and animal health. Consequently, governments impose restrictions on aircraft and wind turbine noise levels. These restrictions can have an economic impact by limiting aircraft traffic and reducing wind turbine energy production. Accordingly, improving the design of aerodynamic surfaces to reduce their noise levels benefits health while enabling improved operational efficiency. Therefore, aeroacoustic research focuses on identifying and understanding the physical mechanisms behind aerodynamic noise to improve noise mitigation technologies. This research relies on acoustic wind tunnel measurements to validate simulations, theories, and design improvements.

Closed test section wind tunnels are widely used for aerodynamic testing but are less suitable for acoustic measurements because microphones must be installed in the wall. This location subjects the microphones to pressure fluctuations from the turbulent boundary layer (TBL), which contaminates acoustic measurements and reduces the signal-to-noise ratio (SNR). The impact of the TBL can be mitigated by recessing microphones within cavities and covering them with an acoustically transparent material. Modifying existing wind tunnel walls by installing cavity--mounted microphones is a straightforward and cost-effective improvement that enables combined aerodynamic and acoustic measurement campaigns.

The cavity geometry, i.e., depth, aperture size, wall angle, and presence of a covering determines the amount of TBL attenuation and consequently the improvement to SNR. While several studies have shown empirically that these parameters have an effect, few studies focus on identifying the physical mechanisms that explain the relationship between geometry and the reduction in TBL pressure fluctuations at the microphone. Thus, this thesis aims to identify these physical mechanisms through experiments and different modeling approaches to better explain the relationship between cavity geometry, the amount of TBL attenuation, and the subsequent impact on the measured acoustic signal.

Experimental data were collected to develop an empirical model to quantify how varying cavity geometry affects the measured pressure spectra. Moreover, experiments were also performed to validate simulation results and to quantify the SNR improvement when applying a beamforming algorithm to microphone array data. The modeling and simulation efforts focus on explaining the trends and phenomena identified in the experimental data. Initially, a physical model was developed that assumed acoustic propagation into an axisymmetric cavity with a constant cross-section. This model decomposes a pressure field, resulting from a TBL, into circular duct modes and was used to evaluate the relationship between cavity geometry and the propagation of these acoustic modes into the cavity. This model was followed up with a finite element method (FEM) simulation to study the influence of different cavity geometric parameters and wall materials on the acoustic response of the cavity when subjected to an acoustic wave.

The FEM simulation showed that the cavity's acoustic response is determined by the presence of standing waves in the form of acoustic depth modes. This simulation showed that cavities with angled walls have depth modes with lower amplitude waves and thus distort the acoustic signal less. Furthermore, it is shown that the acoustic responses of cavities formed out of sound-absorbing foam are driven by the shape of the foam holder and not the cavity shapes within the foam. Thus, the holder can be optimized to minimize the acoustic response, while the cavity itself can be optimized to reduce the influence of the TBL. Building upon these simulations, a Lattice Boltzmann based computational fluid dynamics (CFD) method was used to simulate the pressure and flow fields within three uncovered cavities and covered cavities resulting from the presence of a turbulent boundary layer.

The CFD simulations confirmed a significant finding of the physical model, that the amount of TBL attenuation increases as the cavity aperture size increases relative to the TBL streamwise coherence length. This is due to the resulting modal decomposition of the pressure field above larger cavities having more energy distributed across higher-order modes than for smaller cavities. These higher-order modes decay exponentially into the cavity, resulting in increased attenuation of the TBL. Smaller cavities have most of their energy in their first mode, which does not decay with increasing cavity depth. Furthermore, these simulations showed that the pressure field within covered cavities is primarily acoustic and can be decomposed into acoustic circular duct modes. Since the propagation of TBL pressure fluctuations into covered cavities is primarily acoustic, the shape of future cavities can be efficiently optimized using FEM simulations.

Finally, beamforming used with cavities improved the acoustic measurement SNR. Analysis shows that the improvements due to beamforming are independent of those attributed to the cavity geometry. Thus, combining the two approaches improves the SNR of acoustic measurements in closed test section wind tunnels.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Snellen, M., Supervisor
  • Ragni, D., Supervisor
  • Avallone, F., Advisor
Thesis sponsors
Award date26 Sept 2022
Print ISBNs978-94-6421-857-2
Electronic ISBNs978-94-6421-857-2
DOIs
Publication statusPublished - 2022

Keywords

  • Acoustics
  • CFD
  • Cavity
  • Beamforming
  • Aeroacoustics
  • Wind Tunnel
  • FEM

Fingerprint

Dive into the research topics of 'Improving Acoustic Measurements with Cavities in Closed Test Section Wind Tunnels'. Together they form a unique fingerprint.

Cite this