Carsten Spehr

Two-Dimensional Evaluation of Turbulent Boundary Layer Pressure Fluctuations at Cruise Flight Conditions

A distributed microphone array was installed on an Airbus model A320 airplane and measurements were performed under various cruise ight conditions. Turbulent boundary layer pressure fluctuations were recorded at several ight altitudes and velocities. The array was installed directly in front of the wing root by replacing three pax windows with aluminum dummy windows equipped with Kulite pressure sensors. Combining the signals via a frequency-domain array processing technique provided information about local flow phenomena. Narrow-band convectional direction was extracted from the measurement data and decay of coherence was determined for the predominant flow direction. Two dimensional coherence of turbulent structures was compared with the empirical models of Corcos and Efimtsov.

Spectral broadening by shear layers of open jet wind tunnels

The presence of shear layers in open jet wind tunnels complicates aeroacoustic measurements. Tones from wind tunnel models are subject to spectral broadening (or ‘haystacking’) when propagating through the turbulent shear layer flow. For example, in measurements on contra-rotating propellers this obscures the identification and quantification of rotor tones. This paper describes a theoretical and experimental study into spectral broadening by the shear layers of open jet wind tunnels. A simple physical model is derived which predicts the amount of broadening as a function of a single parameter, which is proportional to wind speed, source frequency and shear layer thickness. The theory is compared against experimental data from five different wind tunnels. Especially for the smaller wind tunnels the agreement between theory and experiment is generally good, which makes it possible to retrieve the original level of a tone from a broadened spectrum.

In-flight Sound Measurements: A First Overview

A series of flight tests were carried out in June 2011 with more than 250 sensors in a cabin cross section upstream of the wings. The main purpose of the flight test was to qualify and quantify the main sources of cabin noise as well as the transfer paths to the passenger under real flight condition. The sensor set consists of pressure transducers installed in three dummy windows, accelerometers on the fuselage and the cabin and microphones inside the cabin. While varying the flight conditions by changing flight altitude, thrust and speed the main noise sources were distinguished and qualified.

Contributions of Different Aeroacoustic Sources to Aircraft Cabin Noise

The turbulent boundary layer (TBL) on the fuselage, jet noise and the air conditioning system (ACS) are considered as three important aeroacoustic sources of aircraft cabin noise. To improve current cabin noise prediction approaches as well as to investigate the different noise sources and their respective noise transfer paths, flight tests with DLR’s A320-232 research aircraft ’D-ATRA’ were carried out within the German national (LuFo IV) project SIMKAB. Extensive measurement data were collected using microphones inside the cabin, unsteady surface-pressure sensors for the characterization of the external TBL- and jet noise induced fuselage excitation, and accelerometers mounted at the frame structure, fuselage skin fields and cabin panels. Flight speed and -level as well as engine and air conditioning system operating conditions were varied to separately evaluate their parametric effects on cabin noise. The analysis of this extensive data base is still ongoing; in the current paper the focus is set on the results from microphone measurements at various longitudinal positions inside the cabin. Both TBL- and jet noise induced contributions increase towards the rear, reflecting the natural growth of the TBL thickness and typical jet noise radiation characteristics. Contrary to that the air conditioning system noise is of minor importance.

Examination of the Influence of Flight Altitude and Speed on the Efimtsov Model Parameters

A flight test was conducted and the data was evaluated in order to investigate the influence of flight altitude and flight speed on the coherence length model by Efimtsov. An underestimation of the measured values by the model was found below a frequency of 1 kHz. Above this frequency, the predicted values matched the measured values very well. The Efimtsov ansatz was found to be suitable for the description of coherence length, when the parameters are adapted. Three further analyses were performed: the flight speed was varied with constant altitude, the altitude was varied with constant flight speed, and both speed & altitude were varied together. No considerable variation was measured when the flight speed was varied separately. A small variation was determined at low frequency when the flight altitude was altered separately. When varying the parameters together, a distinct variation was found for the cases of highest speed and altitude. The applicability of the exponential coherence decay was analyzed. The absolute deviation was found to increase with lower frequency. The characteristic of the deviation was found to collapse in different regions with different scaling of the strouhal number.

Experimental Investigation of Flow-Induced Panel Vibrations at Cruise Mach Number

Surface structures exposed to a fluctuating pressure field are excited best, if the pressure field contains characteristics that match the eigenmodes and wave speeds of the structural vibration. A pressure field can be caused either by acoustical sources, or a turbulent boundary layer, or both. The aim of this paper is the experimental determination of the excitation characteristic of the boundary layer and the corresponding vibration response of an underlying structure under like conditions. The motivation behind this is to obtain experimentally a joint model for the excitation and the related response of the vibration. Individual measurements of the vibration response of a generic aircraft panel exposed to the pressure field of a turbulent boundary layer have been conducted in the past. Individual characterization of a field of fluctuating pressure on a surface has been investigated as well. However, measurements of the excitation characteristics of the turbulent boundary layer of a generic aircraft panel at the same test setup are scarce. The excitation characteristics of the turbulent boundary layer have been measured individually in several speed ranges. A wavenumber decomposition is oftentimes used to display the features of the surface pressure. In the low-speed range, Arguillat^1 detected the convective propagation on a at plate in the wavenumber domain. Smith^2 used a generic setup of a at plate and a generic car side mirror in order to find turbulenceinduced acoustic waves propagating over the surface. These acoustic waves were believed to be responsible for a part of the excitation of the surface structure. In the high speed measurements by Ehrenfried & Koop^3 in the wind tunnel and Haxter & Spehr^4 in a flight test, the convective velocity of the turbulent structures in the boundary layer were considered to be the main cause for excitation of the surface structure. At high speeds, the modes of the structure match the convective speed of the turbulent vortices in the boundary layer, which is called aerodynamic coincidence. The vibration of airplane fuselage subject to excitation by a turbulent boundary layer has been measured by Wilby and Gloyna.^5 In their measurement, accelerometers were placed in lengthwise and streamwise direction on panels, stringers, and frames of a Boeing model 737 aircraft. The distribution was carried out with large distances in between the sensors in order to find correlations in between adjacent panels and structure.

Determining Flow Propagation Direction from In-Flight Array Surface Pressure Fluctuation Data

b wavenumber dirty map e steering vector f frequency H hermitian i imaginary unit kc convective wavenumber kx, ky wavenumber L window size lx, ly coherence lengths M number of signal averages N number of transducers R cross-spectral matrix s, ŝ inclination factors uφ phase velocity x, y transducer position α tilt angle of the coherence pattern α̂ tilt angle of the convective ridge β angle to the center of the convective ridge γ coherence φ spectrum ξ, η transducer separation ξ̂, η̂ rotated transducer separation ξ,′ η′ rotated transducer separation

A Comparison of Microphone Phased Array MethodsApplied to the Study of Airframe Noise in WindTunnel Testing

In this werk, various microphone phased array data processing techniques are applied to two existing datasets from aeroacoustic wind tunnel tests. The first of these is from a !arge closed-wall facility, DLRs Kryo-Kanal Koln (DNW·KKK), and is a measurement cf the high-lift noise cf a semispan model. The second is from a small-scale open-jet facility, the NASA Langley Quiet Flow Facility (QFF), and is a measurement cf a clean airfoil selfnoise. The data had been made publicly available in 2015, and were analyzed by several research groups using multiple analysis techniques. This procedure allows the assessment of the variability of individual methods across various organizational implementations, as weil as the variability cf results produced by different array analysis methods. This paper summarizes the results presented at panel sessions held at AIAA conferences in 2015 and 2016. Results show that with appropriate handling of background noise, all advanced methods can identify dominant acoustic sources for a broad range cf frequencies. Lowerlevel sources may be masked er underpredicted. lntegrated levels are more robust and in closer agreement between methods than narrowband maps for individual frequencies. Overall there is no obvious best method, though multiple methods may be used to bound expected behavior.

Up in the Air: In-Flight Wavenumber Characterization of Surface Pressure Fluctuations at Transonic Conditions

One way of representing surface pressure fluctuations is to display them in frequency-dependent wavenumber spectra. They can be used to feed structural vibration predictions model. However, mostly models and experimental data from wind tunnel and water tunnel experiments have been employed. Apart from possible scaling effects, only hydrodynamic pressure fluctuations are incorporated in these models. Some data from flight tests exists, but again this data is limited to sections of the aircraft where the hydrodynamic pressure fluctuations are dominant. In order to consider both, acoustic and hydrodynamic surface pressure fluctuations in flight a beamforming approach is used in the following to determine wavenumber spectra of pressure fluctuations in cruise flight. This allows for the simultaneous characterization of both, hydrodynamic and acoustic pressure fluctuations and for the discrimination between the two. The wavenumber spectra can be used directly as input for the prediction of structural vibration.

A Tomographic Directivity Approach to Frequency Domain Beamforming

Aeroacoustic measurements in wind tunnels are a common tool in the determination of sound sources on scaled models. Most of the algorithms used are based on the assumption that the unknown aeroacoustic sources radiate sound waves omnidirectionally, thus monopole sources are utilized. For the prediction of the noise footprint of aircrafts however, it is essential to have information on the directivity of the airframe sources. An approach to estimating this directivity is to use different array positions for measurement relative to the model which leads to different observation angles. The evaluation of measurements at several observation angles holds several issues, for example the difficult source localization due to the three-dimensionality of the point spread function and partial shadowing of sources at large observation angles. This paper therefore presents an approach to estimate the source positions taking into account information from all four observation angles at once. The positions estimated in this fashion are subsequently used for an improved prediction of source power and eventually lead to an estimation of directivity of the observed aeroacoustic sources.