A cryogenic-helium pipe flow facility with unique double-line molecular tagging velocimetry capability.

Cryogenic helium-4 has extremely small kinetic viscosity, which makes it a promising material for high Reynolds (Re) number turbulence research in compact laboratory apparatus. In its superfluid phase (He II), helium has an extraordinary heat transfer capability and has been utilized in various scientific and engineering applications. In order to unlock the full potential of helium in turbulence research and to improve our understanding of the heat transfer mechanism in He II, a flow facility that allows quantitative study of helium heat-and-mass transfer processes is needed. Here, we report our work in assembling and testing a unique helium pipe-flow facility that incorporates a novel double-line molecular tagging velocimetry (DL-MTV) system. This flow facility allows us to generate turbulent pipe flows with Re above 107, and it can also be adapted to produce heat-induced counterflow in He II. The DL-MTV system, which is based on the generation and tracking of two parallel thin He2 * molecular tracer lines with an adjustable separation distance, allows us to measure not only the velocity profile but also both the transverse and longitudinal spatial velocity structure functions. We have also installed a differential pressure sensor on the flow pipe for pressure drop measurements. The testing results of the flow facility and the measuring instruments are presented. We discuss how this facility will allow us to solve some outstanding problems in the helium heat-and-mass transfer topic area.

Limits of coherence-based aeroacoustic analysis in the presence of distributed sources.

Coherence-based analysis techniques utilizing a small number of microphones are often applied in aeroacoustic measurements. These techniques can remove statistically incoherent noise, electronic or hydrodynamic, from acoustic signals measured by microphones, at significantly lower cost than array methods. However, the assumptions involved in the usage of the ordinary coherence function technically limit analysis to a single-source field. In the presence of multiple sources the coherence function breaks down and ordinary analysis techniques under-predict true acoustic levels. This phenomenon is demonstrated mathematically and illustrated using experimental trailing edge noise data.

A covariance fitting approach for correlated acoustic source mapping.

Microphone arrays are commonly used for noise source localization and power estimation in aeroacoustic measurements. The delay-and-sum (DAS) beamformer, which is the most widely used beamforming algorithm in practice, suffers from low resolution and high sidelobe level problems. Therefore, deconvolution approaches, such as the deconvolution approach for the mapping of acoustic sources (DAMAS), are often used for extracting the actual source powers from the contaminated DAS results. However, most deconvolution approaches assume that the sources are uncorrelated. Although deconvolution algorithms that can deal with correlated sources, such as DAMAS for correlated sources, do exist, these algorithms are computationally impractical even for small scanning grid sizes. This paper presents a covariance fitting approach for the mapping of acoustic correlated sources (MACS), which can work with uncorrelated, partially correlated or even coherent sources with a reasonably low computational complexity. MACS minimizes a quadratic cost function in a cyclic manner by making use of convex optimization and sparsity, and is guaranteed to converge at least locally. Simulations and experimental data acquired at the University of Florida Aeroacoustic Flow Facility with a 63-element logarithmic spiral microphone array in the absence of flow are used to demonstrate the performance of MACS.

Covariance-based approaches to aeroacoustic noise source analysis.

In this paper, several covariance-based approaches are proposed for aeroacoustic noise source analysis under the assumptions of a single dominant source and all observers contaminated solely by uncorrelated noise. The Cramér-Rao Bounds (CRB) of the unbiased source power estimates are also derived. The proposed methods are evaluated using both simulated data as well as data acquired from an airfoil trailing edge noise experiment in an open-jet aeroacoustic facility. The numerical examples show that the covariance-based algorithms significantly outperform an existing least-squares approach and provide accurate power estimates even under low signal-to-noise ratio (SNR) conditions. Furthermore, the mean-squared-errors (MSEs) of the so-obtained estimates are close to the corresponding CRB especially for a large number of data samples. The experimental results show that the power estimates of the proposed approaches are consistent with one another as long as the core analysis assumptions are obeyed.

Sparsity constrained deconvolution approaches for acoustic source mapping.

Using microphone arrays for estimating source locations and strengths has become common practice in aeroacoustic applications. The classical delay-and-sum approach suffers from low resolution and high sidelobes and the resulting beamforming maps are difficult to interpret. The deconvolution approach for the mapping of acoustic sources (DAMAS) deconvolution algorithm recovers the actual source levels from the contaminated delay-and-sum results by defining an inverse problem that can be represented as a linear system of equations. In this paper, the deconvolution problem is carried onto the sparse signal representation area and a sparsity constrained deconvolution approach (SC-DAMAS) is presented for solving the DAMAS inverse problem. A sparsity preserving covariance matrix fitting approach (CMF) is also presented to overcome the drawbacks of the DAMAS inverse problem. The proposed algorithms are convex optimization problems. Our simulations show that CMF and SC-DAMAS outperform DAMAS and as the noise in the measurements increases, CMF works better than both DAMAS and SC-DAMAS. It is observed that the proposed algorithms converge faster than DAMAS. A modification to SC-DAMAS is also provided which makes it significantly faster than DAMAS and CMF. For the correlated source case, the CMF-C algorithm is proposed and compared with DAMAS-C. Improvements in performance are obtained similar to the uncorrelated case.

Background noise cancellation of manatee vocalizations using an adaptive line enhancer.

The West Indian manatee (Trichechus manatus latirostris) has become an endangered species partly because of an increase in the number of collisions with boats. A device to alert boaters of the presence of manatees is desired. Previous research has shown that background noise limits the manatee vocalization detection range (which is critical for practical implementation). By improving the signal-to-noise ratio of the measured manatee vocalization signal, it is possible to extend the detection range. The finite impulse response (FIR) structure of the adaptive line enhancer (ALE) can detect and track narrow-band signals buried in broadband noise. In this paper, a constrained infinite impulse response (IIR) ALE, called a feedback ALE (FALE), is implemented to reduce the background noise. In addition, a bandpass filter is used as a baseline for comparison. A library consisting of 100 manatee calls spanning ten different signal categories is used to evaluate the performance of the bandpass filter, FIR-ALE, and FALE. The results show that the FALE is capable of reducing background noise by about 6.0 and 21.4 dB better than that of the FIR-ALE and bandpass filter, respectively, when the signal-to-noise ratio (SNR) of the original manatee call is -5 dB.

Modal decomposition method for acoustic impedance testing in square ducts.

Accurate duct acoustic propagation models are required to predict and reduce aircraft engine noise. These models ultimately rely on measurements of the acoustic impedance to characterize candidate engine nacelle liners. This research effort increases the frequency range of normal-incidence acoustic impedance testing in square ducts by extending the standard two-microphone method (TMM), which is limited to plane wave propagation, to include higher-order modes. The modal decomposition method (MDM) presented includes four normal modes in the model of the sound field, thus increasing the bandwidth from 6.7 to 13.5 kHz for a 25.4 mm square waveguide. The MDM characterizes the test specimen for normal- and oblique-incident acoustic impedance and mode scattering coefficients. The MDM is first formulated and then applied to the measurement of the reflection coefficient matrix for a ceramic tubular specimen. The experimental results are consistent with results from the TMM for the same specimen to within the 95% confidence intervals for the TMM. The MDM results show a series of resonances for the ceramic tubular material exhibiting a monotonic decrease in the resonant peaks of the acoustic resistance with increasing frequency, resembling a rigidly-terminated viscous tube, and also evidence of mode scattering is visible at the higher frequencies.

An acoustic proximity ranging system for monitoring the cavity thickness.

To control high speed underwater vehicles, a proximity ranging system is needed to monitor the cavity thickness. In this paper, we study a time-of-flight (TOF) principle based acoustic proximity ranging system. By taking into account the acoustically hard boundary at the air-water interface, we first present a two-stage computationally efficient time delay estimation algorithm, referred to as the PEARS (Parameter Estimation for Acoustic Ranging Systems) algorithm, which is applicable to arbitrary transmitted waveforms. Numerical results based on a simulated waveform demonstrate that the PEARS estimates can approach the Cramér-Rao bound as the signal-to-noise ratio increases. We then present experiments performed by using commercially available acoustic transducers to further verify our method. To update TOF estimates quickly, a specially designed continuous wave (CW) is applied to the transducer. Experimental results show that PEARS can achieve high measurement accuracy for ranging distances less than 100 mm with an achievable parameter update rate of approximately 1.5 kHz.

A directional acoustic array using silicon micromachined piezoresistive microphones.

The need for noise source localization and characterization has driven the development of advanced sound field measurement techniques using microphone arrays. Unfortunately, the cost and complexity of these systems currently limit their widespread use. Directional acoustic arrays are commonly used in wind tunnel studies of aeroacoustic sources and may consist of hundreds of condenser microphones. A microelectromechanical system (MEMS)-based directional acoustic array system is presented to demonstrate key technologies to reduce the cost, increase the mobility, and improve the data processing efficiency versus conventional systems. The system uses 16 hybrid-packaged MEMS silicon piezoresistive microphones that are mounted to a printed circuit board. In addition, a high-speed signal processing system was employed to generate the array response in near real time. Dynamic calibrations of the microphone sensor modules indicate an average sensitivity of 831 microV/Pa with matched magnitude (+/-0.6 dB) and phase (+/-1 degree) responses between devices. The array system was characterized in an anechoic chamber using a monopole source as a function of frequency, sound pressure level, and source location. The performance of the MEMS-based array is comparable to conventional array systems and also benefits from significant cost savings.