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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
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 NTRS2007

Noise Spectra and Directivity For a Scale-Model Landing Gear

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. DAMAS noise source distributions were determined. 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. Finally, 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.

Humphreys, William M., Jr.↗
NASA NTRS2007

Applications of Time-Reversal Processing for Planetary Surface Communications

Due to the power constraints imposed on wireless sensor and communication networks deployed on a planetary surface during exploration, energy efficient transfer of data becomes a critical issue. In situations where groups of nodes within a network are located in relatively close proximity, cooperative communication techniques can be utilized to improve the range, data rate, power efficiency, and lifetime of the network. In particular, if the point-to-point communication channels on the network are well modeled as frequency non-selective, distributed or cooperative beamforming can employed. For frequency-selective channels, beamforming itself is not generally appropriate, but a natural generalization of it, time-reversal communication (TRC), can still be effective. Time-reversal processing has been proposed and studied previously for other applications, including acoustical imaging, electromagnetic imaging, underwater acoustic communication, and wireless communication channels. In this paper, we study both the theoretical advantages and the experimental performance of cooperative TRC for wireless communication on planetary surfaces. We give a brief introduction to TRC and present several scenarios where TRC could be profitably employed during planetary exploration. We also present simulation results illustrating the performance of cooperative TRC employed in a complex multipath environment and discuss the optimality of cooperative TRC for data aggregation in wireless sensor networks

Barton, Richard J.↗
DOE OSTI2021

Seismic Array Analysis Using Fiber-Optic Distributed Acoustic Sensing on Small Local and Regional Earthquakes

We examined the feasibility of using fiber-optic Distributed Acoustic Sensing (DAS) as an alternative to a traditional seismic array. Seismic arrays are used routinely globally to measure waveform propagation parameters and signal features including back-azimuth (BAZ) and apparent horizontal velocity through the process of beamforming or frequency-wavenumber (f-k) array analysis with the assumption that the signals travel across the array as a plane-wave. These measurements are useful for identifying signal detections as teleseismic, regional, or local distance seismic phases based on their velocities traveling across the array (e.g., Rost and Thomas, 2001). Signal enhancement is the main benefit of array processesing through the stacking of multiple channels as a phased array. This enhancement increases as the square root of the number of channels relative to a single seismic station (e.g., Rost and Thomas, 2001), which is a factor of 3 from a typical nine-channel array. DAS provides the potential of stacking waveforms from 100’s to 1000’s of channels. However, DAS is a novel technology designed for geophysical exploration and therefore has some limitations which we will explore. We started with the dataset from the PoroTomo project because of its unique experimental layout of colocated geophone array and DAS deployment so the two recording technologies can be compared side-by-side.

58 GEOSCIENCES↗
NASA NTRS2016

Wavenumber-frequency deconvolution of aeroacoustic microphone phased array data of arbitrary coherence

Deconvolution of aeroacoustic data acquired with microphone phased arrays is a computationally-challenging task for distributed sources with arbitrary coherence. A new technique for performing such deconvolution is proposed. This technique relies on analysis of the array data in the wavenumber-frequency domain, allowing for fast convolution and reduced storage requirements when compared to traditional coherent deconvolution. A positive semidefinite constraint for the iterative deconvolution procedure is implemented and shows improved behavior in terms of quantifiable convergence metrics when compared to a standalone covariance inequality constraint. A series of simulations validates the method's ability to resolve coherence and phase angle relationships between partially-coherent sources, as well as determines convergence criteria for deconvolution analysis. Simulations for point sources near the microphone phased array show potential for handling such data in the wavenumber-frequency domain. In particular, a physics-based integration boundary calculation is described, and can successfully isolate sources and track the appropriate integration bounds with and without the presence of flow. Magnitude and phase relationships between multiple sources are successfully extracted. Limitations of the deconvolution technique are determined from the simulations, particularly in the context of a simulated acoustic field in a closed test section wind tunnel with strong boundary layer contamination. A final application to a trailing edge noise experiment conducted in an open-jet wind tunnel matches best estimates of acoustic levels from traditional calculation methods and qualitatively assesses the coherence characteristics of the trailing edge noise source.

phased array↗
NASA NTRSDate not supplied

A Microphone Phased Array for Launch Acoustics Application

A new, portable, phased array of microphones is built at NASA Ames Research Center specifically for the harsh environment encountered in launch pads of rocket vehicles. It uses 70 piezoresistive, dynamic pressure sensors, optimally distributed on a 10.5ft diameter open frame dome structure. The open frame is light yet robust to sustain the high wind load of typical seaside launch pads, and the blast and acoustic loads from the launch. A 200-ft long cable bundle carries the microphone signals to a weather-protected cabinet containing the data systems, and allows for the placement of the array tall structures. The array is equipped with an infra-red camera and a visible wavelength camera for imaging the launch pad. The beamformed noise maps will be superimposed on the video footages collected by the cameras for correct identification of the noise sources. The array is tested with very loud speaker sources to determine the beamforming ability using different schemes, such as the conventional beamforming, orthogonal-functional beamforming, and spectral element methods. A comparative study was conducted to determine the minimum attainable spatial resolution. Data from a validation test in an outdoor setup, where the array was placed on a Telehandler at several different heights and distances from either a single or a pair of speakers, is presented in this paper. The final goal is to use the array during NASA’s Artemis-II launch to determine the distribution of noise sources on the Mobile Launcher.

Acoustics↗
NASA NTRSDate not supplied

A Microphone Phased Array for Launch Acoustics Application

A new, portable, phased array of microphones is built at NASA Ames Research Center specifically for the harsh environment encountered in launch pads of rocket vehicles. It uses 70 rugged, piezo-electric, dynamic pressure sensors optimally distributed on a 10.5ft diameter open frame dome structure. The open frame is light yet robust to sustain the high wind load of typical seaside launch pads, and the blast and acoustic loads from the launch. A 200-ft long cable bundle carries the microphone signals to a weather-protected electronic cabinet containing the data acquisition system, computers, and other equipment. The array is equipped with an infra-red camera and a visible wavelength camera for imaging the launch site. The beamformed noise maps will be superimposed on the video footages collected by the cameras for correct identification of the noise sources. The array is tested with very loud noise sources to determine the beamforming ability. Multiple mathematical models, such as the conventional beamforming, orthogonal-functional beamforming, spectral element method etc. are used to determine the minimum spatial resolution of the sound sources that can be measured at different frequencies. Additionally, the array hardware is being tested for different environmental conditions and electro-magnetic compliance. The goal is to use the array for NASA’s Artemis/SLS vehicle that will be launched from a newly built Mobile Launch platform and a modified launch pad. Data from a couple of validation tests will be presented in this paper. The first test involves an outdoor setup where the array was placed on a crane at several different heights and distances from a pair of very loud noise sources. The second test from the static firing of the RS25 engines in an outdoor test stand.

Acoustics↗
NASA NTRS2010

Deconvolution methods and systems for the mapping of acoustic sources from phased microphone arrays

A method and system for mapping acoustic sources determined from a phased microphone array. A plurality of microphones are arranged in an optimized grid pattern including a plurality of grid locations thereof. A linear configuration of N equations and N unknowns can be formed by accounting for a reciprocal influence of one or more beamforming characteristics thereof at varying grid locations among the plurality of grid locations. A full-rank equation derived from the linear configuration of N equations and N unknowns can then be iteratively determined. A full-rank can be attained by the solution requirement of the positivity constraint equivalent to the physical assumption of statically independent noise sources at each N location. An optimized noise source distribution is then generated over an identified aeroacoustic source region associated with the phased microphone array in order to compile an output presentation thereof, thereby removing the beamforming characteristics from the resulting output presentation.

Brooks, Thomas F.↗
NASA NTRSDate not supplied

A Microphone Phased Array for Launch Acoustics Application

A new, portable, phased array of microphones is built at NASA Ames Research Center specifically for the harsh environment encountered in launch acoustics applications. It uses 70 rugged, piezo-electric, dynamic pressure sensors optimally distributed on a 10.5ft diameter open frame dome structure. The open frame is light yet robust to sustain the high wind load of typical seaside launch pads, and the blast and acoustic loads from the launch. A 200-ft long cable bundle carries the microphone signals to a weather-protected electronic cabinet containing the data acquisition system, computers, and other equipment. The array is equipped with an infra-red camera and a visible wavelength camera for imaging the launch site. The beamformed noise maps will be superimposed on the video footages collected by the cameras for correct identification of the noise sources. The array is tested with very loud noise sources to determine the beamforming ability. Multiple mathematical models, such as the conventional beamforming, functional beamforming, spectral element method etc. are used to determine the minimum spatial resolution of the sound sources that can be measured at different frequencies. Additionally, the array hardware is being tested for different environmental conditions and electro-magnetic compliance. The immediate goal is to use the array for NASA’s Artemis/SLS vehicle that will be launched from a newly built Mobile Launch platform and a modified launch pad.

microphone phased-array↗
DOE OSTI2023

An Analysis of Published DAS Studies for Application to SPE Phase III

Distributed Acoustic Sensing (DAS) is an emerging technology capable of recording the acoustic wavefield at unprecedented spatial resolution. However, this new tool requires significant refinements before it becomes operational for explosion monitoring objectives. Recent studies have shown significant development of array processing with DAS data. In this report we explore three such array processing methods including DAS strain-rate data versus geophone measured ground motion, beamforming for event parameters, and machine learning based denoising. Prior to applying these algorithms to the Source Physics Experiment Phase II and Phase III data, we validate these methods through replication analysis.

47 OTHER INSTRUMENTATION↗
NASA NTRS2011

Aeroacoustic Characterization of the NASA Ames Experimental Aero-Physics Branch 32- by 48-Inch Subsonic Wind Tunnel with a 24-Element Phased Microphone Array

The Aero-Physics Branch at NASA Ames Research Center utilizes a 32- by 48-inch subsonic wind tunnel for aerodynamics research. The feasibility of acquiring acoustic measurements with a phased microphone array was recently explored. Acoustic characterization of the wind tunnel was carried out with a floor-mounted 24-element array and two ceiling-mounted speakers. The minimum speaker level for accurate level measurement was evaluated for various tunnel speeds up to a Mach number of 0.15 and streamwise speaker locations. A variety of post-processing procedures, including conventional beamforming and deconvolutional processing such as TIDY, were used. The speaker measurements, with and without flow, were used to compare actual versus simulated in-flow speaker calibrations. Data for wind-off speaker sound and wind-on tunnel background noise were found valuable for predicting sound levels for which the speakers were detectable when the wind was on. Speaker sources were detectable 2 - 10 dB below the peak background noise level with conventional data processing. The effectiveness of background noise cross-spectral matrix subtraction was assessed and found to improve the detectability of test sound sources by approximately 10 dB over a wide frequency range.

Costanza, Bryan T.↗
NASA NTRS2015

Removing Background Noise with Phased Array Signal Processing

Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

Background Noise↗
NASA NTRS2012

NASA Tech Briefs, December 2012

The topics include: Pattern Generator for Bench Test of Digital Boards; 670-GHz Down- and Up-Converting HEMT-Based Mixers; Lidar Electro-Optic Beam Switch with a Liquid Crystal Variable Retarder; Feedback Augmented Sub-Ranging (FASR) Quantizer; Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring; Software Modules for the Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol; Description and User Instructions for the Quaternion to Orbit v3 Software; AdapChem; Mars Relay Lander and Orbiter Overflight Profile Estimation; Extended Testability Analysis Tool; Interactive 3D Mars Visualization; Rapid Diagnostics of Onboard Sequences; MER Telemetry Processor; pyam: Python Implementation of YaM; Process for Patterning Indium for Bump Bonding; Archway for Radiation and Micrometeorite Occurrence Resistance; 4D Light Field Imaging System Using Programmable Aperture; Device and Container for Reheating and Sterilization; Radio Frequency Plasma Discharge Lamps for Use as Stable Calibration Light Sources; Membrane Shell Reflector Segment Antenna; High-Speed Transport of Fluid Drops and Solid Particles via Surface Acoustic Waves; Compact Autonomous Hemispheric Vision System; A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring; Wideband Single-Crystal Transducer for Bone Characterization; Numerical Simulation of Rocket Exhaust Interaction With Lunar Soil; Motion Imagery and Robotics Application (MIRA): Standards-Based Robotics; Particle Filtering for Model-Based Anomaly Detection in Sensor Networks; Ka-band Digitally Beamformed Airborne Radar Using SweepSAR Technique; Composite With In Situ Plenums; Multi-Beam Approach for Accelerating Alignment and Calibration of HyspIRI-Like Imaging Spectrometers; JWST Lifting System; Next-Generation Tumbleweed Rover; Pneumatic System for Concentration of Micrometer-Size Lunar Soil.

Source record↗
NASA NTRS2016

Development and Calibration of a Field-Deployable Microphone Phased Array for Propulsion and Airframe Noise Flyover Measurements

A new aeroacoustic measurement capability has been developed consisting of a large channelcount, field-deployable microphone phased array suitable for airframe noise flyover measurements for a range of aircraft types and scales. The array incorporates up to 185 hardened, weather-resistant sensors suitable for outdoor use. A custom 4-mA current loop receiver circuit with temperature compensation was developed to power the sensors over extended cable lengths with minimal degradation of the signal to noise ratio and frequency response. Extensive laboratory calibrations and environmental testing of the sensors were conducted to verify the design's performance specifications. A compact data system combining sensor power, signal conditioning, and digitization was assembled for use with the array. Complementing the data system is a robust analysis system capable of near real-time presentation of beamformed and deconvolved contour plots and integrated spectra obtained from array data acquired during flyover passes. Additional instrumentation systems needed to process the array data were also assembled. These include a commercial weather station and a video monitoring / recording system. A detailed mock-up of the instrumentation suite (phased array, weather station, and data processor) was performed in the NASA Langley Acoustic Development Laboratory to vet the system performance. The first deployment of the system occurred at Finnegan Airfield at Fort A.P. Hill where the array was utilized to measure the vehicle noise from a number of sUAS (small Unmanned Aerial System) aircraft. A unique in-situ calibration method for the array microphones using a hovering aerial sound source was attempted for the first time during the deployment.

Humphreys, William M., Jr.↗
DOE OSTI2023

Evaluation of Potential DAS Array Geometries for the Source Physics Experiment, Phase III

Distributed Acoustic Sensing (DAS) is a rapidly developing technology that can record acoustic wavefields at high sampling rates and with dense spatial spacing difficult to achieve with seismometers. However, the geophysical community has not fully explored DAS survey parameters to characterize the ideal array design. A better quantitative understanding of DAS array behavior prior to SPE Phase III acquisition can help improve the quality of the data recorded by guiding the DAS array design. Here we use array response functions as well as beamforming and backprojection results from forward modelling calculations to assess the performance of varying DAS array geometries to record regional and local sources. A seven-sided polygon DAS array demonstrated improved capabilities for recording regional sources over segmented linear arrays, with potential improvements in recording and locating local sources. These results help reveal DAS array performance as a function of geometry.

58 GEOSCIENCES↗
NASA NTRS2010

Improved Phased Array Imaging of a Model Jet

An advanced phased array system, OptiNav Array 48, and a new deconvolution algorithm, TIDY, have been used to make octave band images of supersonic and subsonic jet noise produced by the NASA Glenn Small Hot Jet Acoustic Rig (SHJAR). The results are much more detailed than previous jet noise images. Shock cell structures and the production of screech in an underexpanded supersonic jet are observed directly. Some trends are similar to observations using spherical and elliptic mirrors that partially informed the two-source model of jet noise, but the radial distribution of high frequency noise near the nozzle appears to differ from expectations of this model. The beamforming approach has been validated by agreement between the integrated image results and the conventional microphone data.

Dougherty, Robert P.↗
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↗