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A test campaign was conducted in the open-jet test section of the NASA Langley Research Center's 14- by 22-Foot Subsonic Tunnel on a 10%-scale semispan version of the High-Lift Common Research Model incorporating a leading-edge slat, a trailing-edge flap, and removable high-fidelity main landing gear. Computational simulations were used to support the model development, provide important information such as load distributions along the high-lift elements, and aid in the design of noise reduction devices. Aerodynamic and far-field acoustic measurements were obtained on baseline and acoustically treated model configurations using an ensemble of time-averaged and unsteady surface pressure sensors paired with a traversing 97-microphone phased array viewing the pressure side of the airframe. A deconvolution method incorporating corrections for shear layer acoustic wave decorrelation was employed to determine the locations and strengths of relevant noise sources along the span of the slat and in the vicinity of the flap edges and landing gear. The main goal of the test campaign was to use the surface pressure and array data to evaluate the effectiveness of various slat noise reduction concepts. It was found that slat-gap fillers produced significant broadband noise reduction with minimal aerodynamic performance penalties for all Mach numbers and airfoil angles of attack that were investigated. The test campaign clearly demonstrated the noise reduction benefits that can be obtained by applying appropriate treatments to leading-edge slats on commercial transport-class aircraft. [ABSTRACT FROM AUTHOR]

An extensive experimental study has been conducted to acquire detailed noise spectra and directivity data for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. The measurements were conducted in the NASA Langley Quiet Flow Facility using a 41-microphone directional array system positioned at a range of polar and azimuthal observer angles with respect to the model. DAMAS (Deconvolution Approach for the Mapping of Acoustic Sources) array processing as well as straightforward individual microphone processing were employed to compile unique flyover and sideline directivity databases for a range of freestream Mach numbers (0.11 - 0.17) covering typical approach conditions. Comprehensive corrections were applied to the test data to account for shear layer ray path and amplitude variations. This allowed proper beamforming at different measurement orientations, as well as directivity presentation in free-field emission coordinates. Four different configurations of the landing gear were tested: a baseline configuration with and without an attached side door, and a noise reduction concept "toboggan" truck fairing with and without side door. Spectral analyses demonstrated that individual microphones could establish model spectra. This finding permitted the determination of unique, spatially-detailed directivity contours of spectral band levels over a hemispherical surface. Spectral scaling for the baseline model confirmed that the acoustic intensity scaled with the expected sixth-power of the Mach number. A comparison of spectra and directivity between the baseline gear and the gear with an attached toboggan indicated that the toboggan fairing may be of some value in reducing gear noise over particular frequency ranges. Finally, spectrum results were scaled quantitatively to data obtained from flyover tests of a full-scale 777 aircraft. The comparison showed good agreement in frequency and level, suggesting the general applicability of the model-scale noise results. [ABSTRACT FROM AUTHOR]

The NASA Aircraft NOise Prediction Program (ANOPP) offers two empirically based methods to predict landing gear noise: the "Fink" method and the "Guo" method. The "Guo" method is the most recent and was developed almost exclusively using Boeing full-scale landing gear data. The "Fink" method was developed over 25 years ago, using both model and full-scale data. The details of the two methods are compared and contrasted. The Fink method is found to follow Strouhal scaling, and hence predictions are made with the scale model geometry as input. The Guo method was found not to scale for arbitrary sized landing gear and hence the method required full-scale geometry inputs and the resulting predictions required scaling in order to compare with the measured model results. Application of these methods to a model-scale landing gear is investigated by comparing predicted results from each method with measured acoustic data obtained for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. The measurements were obtained in the NASALangley Quiet Flow Facility for a range of Mach numbers at a large number of observer angles. Noise spectra and contours as a function of polar and azimuthal angle characterize the directivity of landing gear noise. The measured spectra and contours are compared to predictions made using the Fink method and to scaled predictions from the Guo method. This is the first time an extensive set of landing gear noise directivity data are available to compare and assess predictive capabilities. Both methods predict comparable amplitudes and trends for the flyover locations, but deviate at sideline locations. Neither method fully captures the measured noise directivity. [ABSTRACT FROM AUTHOR]

An aeroacoustic model test has been conducted to investigate the mechanisms of sound generation on high-lift wing configurations. This paper presents an analysis of flap side-edge noise, which is often the most dominant source. A model of a main element wing section with a half-span flap was tested at low speeds of up to a Mach number of 0.17, corresponding to a wing chord Reynolds number of approximately 1.7 million. Results are presented for flat (or blunt), flanged, and round flap-edge geometries, with and without boundary-layer tripping, deployed at both moderate and high flap angles. The acoustic database is obtained from a small aperture directional array (SADA) of microphones, which was constructed to electronically steer to different regions of the model and to obtain farfield noise spectra and directivity from these regions. The basic flap-edge aerodynamics is established by static surface pressure data, as well as by computational fluid dynamics (CFD) calculations and simplified edge flow analyses. Distributions of unsteady pressure sensors over the flap allow the noise source regions to be defined and quantified via cross-spectral diagnostics using the SADA output. It is found that shear layer instability and related pressure scatter is the primary noise mechanism. For the flat edge flap, two noise prediction methods based on unsteady-surface-pressure measurements are evaluated and compared to measured noise. One is a new causality spectral approach developed here. The other is a new application of an edge-noise scatter prediction method. The good comparisons for both approaches suggest that the prediction models capture much of the physics. Areas of disagreement appear to reveal when the assumed edge noise mechanism does not fully define the noise production. For the different edge conditions, extensive spectra and directivity are presented. The complexity of the directivity results demonstrate the strong role of edge source geometry and frequency in the noise radiation. Significantly, for each edge configuration, the spectra for different flow speeds, flap angles, and surface roughness were successfully scaled by utilizing aerodynamic performance and boundary-layer scaling methods developed herein. [Copyright &y& Elsevier]

Presents a comparative study of image compression techniques for use with digital particle image velocimetry. Theoretical background; Image sequences chosen for the study; Evaluation procedure adopted; Sample results and discussion.