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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Greenwood, Eric, II↗
NASA NTRSDate not supplied

Multiplanar Synthetic Arrays and Their Application to Full-Scale Landing Gear Noise Source Identification

Identification and quantification of noise sources generated by the landing gears of large civil transports are critical for the development of viable abatement technologies that can be applied locally to affect solely the source regions. Leveraging validated computational data sets obtained from airframe noise simulations of a full-scale B777-300ER aircraft, a frame-work based on multiplanar synthetic arrays was developed to examine landing gear sources. The position of the arrays relative to the aircraft nose or main landing gears, the number of microphones in each array, and their distribution pattern were judiciously selected to provide adequate spatial resolution of the sources in the primary flyover, sideline, and upstream directions while maintaining reasonable signal-to-noise ratio and beamwidth over a wide frequency range. Overall, seven synthetic arrays with 800 microphones each, for a total of 5,600 microphones, were used in the framework. Fully synchronous synthetic pressure records at each microphone location were obtained from the simulated data sets via a Ffowcs-Williams and Hawkings integral approach, with flow quantities on a permeable data surface enclosing the source regions used as input. Various applications of synthetic multiplanar arrays to acoustic data analysis are presented; the advantages of the framework in properly resolving and identifying the B777 landing gear sources is demonstrated by comparing three-dimensional source distribution maps with those obtained from a synthetic version of the ground-based microphone array used during flight tests of the same aircraft.

airframe noise↗
NASA NTRS2004

Further Progress in Noise Source Identification in High Speed Jets via Causality Principle

To locate noise sources in high-speed jets, the sound pressure fluctuations p/, measured at far field locations, were correlated with each of density p, axial velocity u, radial velocity v, puu and pvv fluctuations measured from various points in fully expanded, unheated plumes of Mach number 0.95, 1.4 and 1.8. The velocity and density fluctuations were measured simultaneously using a recently developed, non-intrusive, point measurement technique based on molecular Rayleigh scattering (Seasholtz, Panda, and Elam, AIAA Paper 2002-0827). The technique uses a continuous wave, narrow line-width laser, Fabry-Perot interferometer and photon counting electronics. The far field sound pressure fluctuations at 30 to the jet axis provided the highest correlation coefficients with all flow variables. The correlation coefficients decreased sharply with increased microphone polar angle, and beyond about 60 all correlation mostly fell below the experimental noise floor. Among all correlations < puu; p/> showed the highest values. Interestingly, , in all respects, were very similar to . The and correlations with 90deg microphone fell below the noise floor. By moving the laser probe at various locations in the jet it was found that the strongest noise source lies downstream of the end of the potential core and extends many diameters beyond. Correlation measurement from the lip shear layer showed a Mach number dependency. While significant correlations were measured in Mach 1.8 jet, values were mostly below the noise floor for subsonic Mach 0.95 jet. Various additional analyses showed that fluctuations from large organized structures mostly contributed to the measured correlation, while that from small scale structures fell below the noise floor.

Panda, J.↗
NASA NTRSDate not supplied

Physics Informed Broadband Noise Source Identification and Prediction of an Ideally Twisted Rotor

This work aims at a physics based approach for the prediction and isolation of broadband noise emanating from different regions of an ideally twisted rotor. A preliminary prediction was conducted using a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) implemented within the software suite, PowerFLOW. Regions of particular interest to broadband noise were investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor. These regions were then isolated and treated as individual Ffowcs Williams-Hawkings (FW-H) surfaces for three run conditions at a much finer spatial resolution to delineate the broadband noise from these separate regions from the total acoustic spectra. These predictions were then compared to experimentally acquired data as well as to semi-empirical prediction methods to highlight the acoustic contributions of various broadband noise generation mechanisms as well as to exemplify and explain shortcomings in the semi-empirical methodology.

Christopher S Thurman↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Transonic Truss-Braced Wing Aircraft: Part 2 – Acoustic Signature and Noise Source Identification

High-fidelity, time-dependent simulations of a Boeing-designed, transonic, truss-braced-wing aircraft in cruise (clean) and landing configurations are leveraged to generate synthetic microphone-phased-array data for airframe noise prediction and assessment. These data sets are used to compute source localization (beamform) maps to determine the location and strength of primary and secondary airframe noise sources associated with this unique configuration. The synthetic phased-array implementation mimics the setup of a flight test. As this study is ongoing, preliminary integrated far-field spectra for the cruise configuration obtained at multiple spatial resolutions revealed significant tonal content that lacked convergence with increased resolution. The origin of several of these tones and their unusual convergence behavior was traced to the larger-than-normal trailing-edge thickness of the “as-tested” cruise model being simulated. Reducing the trailing-edge thickness to more realistic values eliminated most of the tones at low to moderate frequencies and improved spectrum convergence significantly. Applying lessons learned from the cruise simulations, several modifications to the geometry of the landing configuration were made and are described in this work. Results from permeable and solid Ffowcs-Williams and Hawkings surfaces at two different spatial resolutions (coarse and medium) are used to illustrate the major noise sources and determine convergence of the CLEAN integrated noise levels for the entire aircraft as well as major subcomponents. We demonstrate that the low-frequency content of the far-field spectrum is dominated by noise generated from the main landing gear, while the medium- and high-frequency content is dominated by the wing-leading-edge Krueger flaps. Since analysis of the acoustic maps for the landing configuration revealed several clusters of multiple sources along the wing leading edge, “high resolution” processing of the array data was used to distinguish more accurately the locations of sources.

Transonic Truss-Braced Wing↗
NASA NTRSDate not supplied

Physics-Informed Broadband Noise Source Identification and Prediction of an Ideally Twisted Rotor

This work aims to provide a physics-based approach for the prediction and isolation of broadband noise emanating from different regions of an ideally twisted rotor. A preliminary prediction was conducted using a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) implemented within the software suite, PowerFLOW. Regions of particular interest to broadband noise were investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor. These regions were then treated as individual Ffowcs Williams and Hawkings (FW-H) surfaces and simulated for three run conditions at a finer spatial resolution to identify the broadband noise from these separate regions and isolate it from the total acoustic spectra. These predictions were then compared to experimentally acquired data and to semiempirical prediction methods to highlight the acoustic contributions of various broadband noise generation mechanisms as well as to exemplify and explain shortcomings in the semiempirical methodology.

Christopher S Thurman↗
NASA NTRS1987

Rotor blade-vortex interaction impulsive noise source identification and correlation with rotor wake predictions

An acoustic source localization scheme applicable to noncompact moving sources is developed and applied to the blade-vortex interaction (BVI) noise data of a 40-percent scale BO-105 model rotor. A generalized rotor wake code is employed to predict possible VBI locations on the rotor disk and is found quite useful in interpreting the acoustic localization results. The highly varying directivity patterns of different BVI impulses generated at the same test condition are explained by both the localization results and predicted tip vortex trajectories. The effects of rotor tip-path-plane angle and advance ratio on the BVI source positions is studied. Decreasing tip-path-plane angle (at constant advance ratio) moves the general interaction region upwind on the rotor disk, significantly changing the interaction geometry. Increasing advance ratio (at constant tip-path-plane angle) shifts the general source region downwind on the rotor disk with the increased convection of the vortices until about 60 deg azimuth, where the BVI sources appear to become acoustically less effective. The region of strongest BVI sources lies between 60 and 70 deg azimuth and 80 and 90 percent radius for the moderate range of advance ratios studied.

Splettstoesser, W. R.↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 3 - Aerodynamic Validation and Noise Source Identification

Wind tunnel test data were used to validate the predicted aerodynamic behavior of a 15%-scale version of a generic, low-boom aircraft. The test was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel to determine the low-speed aerodynamic characteristics of the model. Measured steady surface pressures and global forces were used to validate predicted aerodynamic results obtained from high-fidelity simulations of the model as installed in the tunnel. Very good agreement between predicted and measured aerodynamic trends was demonstrated, providing the impetus to proceed with companion airframe noise simulations that were conducted in a free-air setting. Computed near-field flow variables acquired on a permeable data surface were used to generate synthetic pressure records for two 800-element phased microphone arrays positioned overhead and to the side of the model. The array data were beamformed to generate noise source localization maps for the clean model and several landing configurations. Primary and secondary airframe sources were identified and their relative strengths were determined. Far-field integrated noise spectra for the full aircraft, as well as individual components, were obtained from the source maps via integration of tailored regions. The analysis showed that noise produced by the landing gear was the dominant contributor to the far-field acoustic signature of the model, followed by flap noise. The effects of permeable data surface end caps, spatial resolution, array orientation, angle of attack, component interaction, velocity scaling, and numerical precision on synthetic far-field spectra were also evaluated.

low boom↗
NASA NTRS1988

A noise source identification technique using an inverse Helmholtz integral equation method

A technique is developed which utilizes numerical models and field pressure information to characterize acoustic fields and identify acoustic sources. The numerical models are based on boundary element numerical procedures. Either pressure, velocity, or passive boundary conditions, in the form of impedance boundary conditions, may be imposed on the numerical model. Alternatively, if no boundary information is known, a boundary condition can be left unspecified. Field pressure data may be specified to overdetermine the numerical problem. The problem is solved numerically for the complete sound field from which the acoustic sources may be determined. The model can then be used to idenfify acoustic intensity paths in the field. The solution can be modified and the model used to evaluate design alternatives. In this investigation the method is tested analytically and verified. In addition, the sensitivity of the method to random and bias error in the input data is demonstrated.

Gardner, B. K.↗
NASA NTRS2014

Identification of Noise Sources in a Rocket Engine Test Stand using Microphone Phased Array

A new, phased array of microphones, suitable for the harsh environment of a rocket launch, was built and tested during a static firing of a RS-25 engine. It uses 70 piezo-resistive, dynamic pressure sensors, optimally distributed on a 10.5ft diameter open frame dome structure, and has a 200-ft long cable bundle to carry the signals to a weather-protected cabinet containing the data systems. The test stand was imaged using an infra-red camera and a visible wavelength camera, and the beamformed noise maps were superimposed on the photographs. The first-time data from a full-scale engine test stand showed that the plume deflector at the bottom of the engine to be the primary noise source. The openings of the test stand around the nozzle exit were also found to be noise sources particularly at higher frequencies. The final goal is to use the array during NASA’s Artemis-II launch at Kennedy Space Center.

Identification of Noise Source↗
NASA NTRS2005

Identification of Noise Sources in High Speed Jets via Correlation Measurements: A Review

Significant advancement has been made in the last few years to identify noise sources in high speed jets via direct correlation measurements. In this technique turbulent fluctuations in the flow are correlated with far field acoustics signatures. In the 1970 s there was a surge of work using mostly intrusive probes, and a few using Laser Doppler Velocimetry, to measure turbulent fluctuations. The later experiments established "shear noise" as the primary source for the shallow angle noise. Various interpretations and criticisms from this time are described in the review. Recent progress in the molecular Rayleigh scattering based technique has provided a completely non-intrusive means of measuring density and velocity fluctuations. This has brought a renewed interest on correlation measurements. We have performed five different sets of experiments in single stream jets of different Mach number, temperature ratio and nozzle configurations. The present paper tries to summarize the correlation data from these works.

Bridges, James↗
NASA NTRS2013

Identification of Noise Sources During Rocket Engine Test Firings and a Rocket Launch Using a Microphone Phased-Array

A 70 microphone, 10-foot by 10-foot, microphone phased array was built for use in the harsh environment of rocket launches. The array was setup at NASA Wallops launch pad 0A during a static test firing of Orbital Sciences' Antares engines, and again during the first launch of the Antares vehicle. It was placed 400 feet away from the pad, and was hoisted on a scissor lift 40 feet above ground. The data sets provided unprecedented insight into rocket noise sources. The duct exit was found to be the primary source during the static test firing; the large amount of water injected beneath the nozzle exit and inside the plume duct quenched all other sources. The maps of the noise sources during launch were found to be time-dependent. As the engines came to full power and became louder, the primary source switched from the duct inlet to the duct exit. Further elevation of the vehicle caused spilling of the hot plume, resulting in a distributed noise map covering most of the pad. As the entire plume emerged from the duct, and the ondeck water system came to full power, the plume itself became the loudest noise source. These maps of the noise sources provide vital insight for optimization of sound suppression systems for future Antares launches.

acoustics↗
NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) GUI implementation via MATLAB Application Designer

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor wake interacting with the rotor blades. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of Blade-Vortex Interaction (BVI) noise. RABBIT enables engineers to quickly locate and understand designs or configurations that cause significant BVI noise. Furthermore, RABBIT can identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict only BVI noise. To date, RABBIT has been validated against CAMRAD II and ANOPP2/AARON for three NASA Revolutionary Vertical Lift Technology (RVLT) concept vehicles: the Quiet Single Main Rotor (QSMR), Side-by-Side, and Quadrotor. RABBIT has been shown to be a useful BVI prediction tool capable of visualizing BVI as a function of various parameters. Impulse factor and time rate of change of loading allows for a unique BVI prediction technique that provides information on impulse strength, location, and frequency. This presentation will highlight how MATLAB’s App Designer was utilized to enable users to navigate RABBIT easily and efficiently without prior experience with MATLAB or rotorcraft acoustics. RABBIT users can build and view rotors in real time with options to control blade chord, radius, phasing, and airfoil geometry. Furthermore, multiple rotors can be combined to create state-of-the-art multi-rotor vehicles or fleets. Editable tables, sliding bars, and push buttons were implemented within MATLAB’s App Designer for RABBIT’s GUI to allow engineers and designers to predict low order acoustic impact of BVI occurrences.

Natasha Lydia Schatzman↗
NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) Reimagined: Algorithm Improvement and User-Friendly Interface Implementation

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor blades interacting with the rotor wake. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of BVI noise. RABBIT enables engineers to quickly design and simulate UAM configurations and understand BVI occurrences for a desired flight condition. Furthermore, RABBIT can also identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict BVI aerodynamics. RABBIT algorithm has been further developed including reduction of computational time, accounting for BVI source time arrival, improved vortex strength modeling, and BVI impulse factor. A user-friendly app is presented with the intent of bringing RABBIT to the masses to allow engineers from various educational backgrounds to design and begin to understand BVI. Furthermore, RABBIT capabilities are highlighted by a parameter study highlighting key parameters that impact BVIalong with highlighting RABBIT’s ability to identify BVI occurrences from other rotors.

RApid↗