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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Assessment of Current Jet Noise Prediction Capabilities

An assessment was made of the capability of jet noise prediction codes over a broad range of jet flows, with the objective of quantifying current capabilities and identifying areas requiring future research investment. Three separate codes in NASA s possession, representative of two classes of jet noise prediction codes, were evaluated, one empirical and two statistical. The empirical code is the Stone Jet Noise Module (ST2JET) contained within the ANOPP aircraft noise prediction code. It is well documented, and represents the state of the art in semi-empirical acoustic prediction codes where virtual sources are attributed to various aspects of noise generation in each jet. These sources, in combination, predict the spectral directivity of a jet plume. A total of 258 jet noise cases were examined on the ST2JET code, each run requiring only fractions of a second to complete. Two statistical jet noise prediction codes were also evaluated, JeNo v1, and Jet3D. Fewer cases were run for the statistical prediction methods because they require substantially more resources, typically a Reynolds-Averaged Navier-Stokes solution of the jet, volume integration of the source statistical models over the entire plume, and a numerical solution of the governing propagation equation within the jet. In the evaluation process, substantial justification of experimental datasets used in the evaluations was made. In the end, none of the current codes can predict jet noise within experimental uncertainty. The empirical code came within 2dB on a 1/3 octave spectral basis for a wide range of flows. The statistical code Jet3D was within experimental uncertainty at broadside angles for hot supersonic jets, but errors in peak frequency and amplitude put it out of experimental uncertainty at cooler, lower speed conditions. Jet3D did not predict changes in directivity in the downstream angles. The statistical code JeNo,v1 was within experimental uncertainty predicting noise from cold subsonic jets at all angles, but did not predict changes with heating of the jet and did not account for directivity changes at supersonic conditions. Shortcomings addressed here give direction for future work relevant to the statistical-based prediction methods. A full report will be released as a chapter in a NASA publication assessing the state of the art in aircraft noise prediction.

Hunter, Craid A.↗
NASA NTRS2002

High Speed Jet Noise Prediction Using Large Eddy Simulation

Current methods for predicting the noise of high speed jets are largely empirical. These empirical methods are based on the jet noise data gathered by varying primarily the jet flow speed, and jet temperature for a fixed nozzle geometry. Efforts have been made to correlate the noise data of co-annular (multi-stream) jets and for the changes associated with the forward flight within these empirical correlations. But ultimately these emipirical methods fail to provide suitable guidance in the selection of new, low-noise nozzle designs. This motivates the development of a new class of prediction methods which are based on computational simulations, in an attempt to remove the empiricism of the present day noise predictions.

Lele, Sanjiva K.↗
NASA NTRS2004

Mean Flow and Noise Prediction for a Separate Flow Jet With Chevron Mixers

Experimental and numerical results are presented here for a separate flow nozzle employing chevrons arranged in an alternating pattern on the core nozzle. Comparisons of these results demonstrate that the combination of the WIND/MGBK suite of codes can predict the noise reduction trends measured between separate flow jets with and without chevrons on the core nozzle. Mean flow predictions were validated against Particle Image Velocimetry (PIV), pressure, and temperature data, and noise predictions were validated against acoustic measurements recorded in the NASA Glenn Aeroacoustic Propulsion Lab. Comparisons are also made to results from the CRAFT code. The work presented here is part of an on-going assessment of the WIND/MGBK suite for use in designing the next generation of quiet nozzles for turbofan engines.

Koch, L. Danielle↗
NASA NTRS1999

Rocket Noise Prediction Program

A comprehensive, automated, and user-friendly software program was developed to predict the noise and ignition over-pressure environment generated during the launch of a rocket. The software allows for interactive modification of various parameters affecting the generated noise environment. Predictions can be made for different launch scenarios and a variety of vehicle and launch mount configurations. Moreover, predictions can be made for both near-field and far-field locations on the ground and any position on the vehicle. Multiple engine and fuel combinations can be addressed, and duct geometry can be incorporated efficiently. Applications in structural design are addressed.

Margasahayam, Ravi↗
NASA NTRS1982

Empirical source noise prediction method with application to subsonic coaxial jet mixing noise

A general empirical method, developed for source noise predictions, uses tensor splines to represent the dependence of the acoustic field on frequency and direction and Taylor's series to represent the dependence on source state parameters. The method is applied to prediction of mixing noise from subsonic circular and coaxial jets. A noise data base of 1/3-octave-band sound pressure levels (SPL's) from 540 tests was gathered from three countries: United States, United Kingdom, and France. The SPL's depend on seven variables: frequency, polar direction angle, and five source state parameters: inner and outer nozzle pressure ratios, inner and outer stream total temperatures, and nozzle area ratio. A least-squares seven-dimensional curve fit defines a table of constants which is used for the prediction method. The resulting prediction has a mean error of 0 dB and a standard deviation of 1.2 dB. The prediction method is used to search for a coaxial jet which has the greatest coaxial noise benefit as compared with an equivalent single jet. It is found that benefits of about 6 dB are possible.

Zorumski, W. E.↗
NASA NTRS2011

Design of the Next Generation Aircraft Noise Prediction Program: ANOPP2

The requirements, constraints, and design of NASA's next generation Aircraft NOise Prediction Program (ANOPP2) are introduced. Similar to its predecessor (ANOPP), ANOPP2 provides the U.S. Government with an independent aircraft system noise prediction capability that can be used as a stand-alone program or within larger trade studies that include performance, emissions, and fuel burn. The ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software. The design of the system is described in terms of its functionality and capability to perform predictions accounting for distributed sources, installation effects, and propagation through a non-uniform atmosphere including refraction and the influence of terrain. The philosophy of mixed fidelity noise prediction through the use of nested Ffowcs Williams and Hawkings surfaces is presented and specific issues associated with its implementation are identified. Demonstrations for a conventional twin-aisle and an unconventional hybrid wing body aircraft configuration are presented to show the feasibility and capabilities of the system. Isolated model-scale jet noise predictions are also presented using high-fidelity and reduced order models, further demonstrating ANOPP2's ability to provide predictions for model-scale test configurations.

Lopes, Leonard V., Dr.↗
NASA NTRS2004

Development in Source Modeling and Sound Propagation for Jet Noise Predictions

The purpose of the research carried out under this cooperative agreement was to develop tools that could be used to improve upon the current state of the art in the prediction of noise emitted by turbulent exhaust jets. Both the source modeling and sound propagation aspects of the prediction of jet noise by acoustic analogy were examined with a view toward the development of methods which yield improved predictions over a wider range of operating conditions.

Leib, Steward↗
NASA NTRS1997

Fan Noise Prediction: Status and Needs

The prediction of fan noise is an important part to the prediction of overall turbofan engine noise. Advances in computers and better understanding of the flow physics have allowed researchers to compute sound generation from first principles and rely less on empirical correlations. While progress has been made, there are still many aspects of the problem that need to be explored. This paper presents some recent advances in fan noise prediction and suggests areas that still need further development. Fan noise predictions that support the recommendations are taken from existing publications.

Huff, Dennis L.↗
NASA NTRS2016

Auralization of NASA N+2 Aircraft Concepts from System Noise Predictions

Auralization of aircraft flyover noise provides an auditory experience that complements integrated metrics obtained from system noise predictions. Recent efforts have focused on auralization methods development, specifically the process by which source noise information obtained from semi-empirical models, computational aeroacoustic analyses, and wind tunnel and flight test data, are used for simulated flyover noise at a receiver on the ground. The primary focus of this work, however, is to develop full vehicle auralizations in order to explore the distinguishing features of NASA's N+2 aircraft vis-à-vis current fleet reference vehicles for single-aisle and large twin-aisle classes. Some features can be seen in metric time histories associated with aircraft noise certification, e.g., tone-corrected perceived noise level used in the calculation of effective perceived noise level. Other features can be observed in sound quality metrics, e.g., loudness, sharpness, roughness, fluctuation strength and tone-to-noise ratio. A psychoacoustic annoyance model is employed to establish the relationship between sound quality metrics and noise certification metrics. Finally, the auralizations will serve as the basis for a separate psychoacoustic study aimed at assessing how well aircraft noise certification metrics predict human annoyance for these advanced vehicle concepts.

Rizzi, Stephen A.↗
NASA NTRS2015

Variability in the Propagation Phase of CFD-Based Noise Prediction: Summary of Results From Category 8 of the BANC-III Workshop

The usage of Computational Fluid Dynamics (CFD) in noise prediction typically has been a two part process: accurately predicting the flow conditions in the near-field and then propagating the noise from the near-field to the observer. Due to the increase in computing power and the cost benefit when weighed against wind tunnel testing, the usage of CFD to estimate the local flow field of complex geometrical structures has become more routine. Recently, the Benchmark problems in Airframe Noise Computation (BANC) workshops have provided a community focus on accurately simulating the local flow field near the body with various CFD approaches. However, to date, little effort has been given into assessing the impact of the propagation phase of noise prediction. This paper includes results from the BANC-III workshop which explores variability in the propagation phase of CFD-based noise prediction. This includes two test cases: an analytical solution of a quadrupole source near a sphere and a computational solution around a nose landing gear. Agreement between three codes was very good for the analytic test case, but CFD-based noise predictions indicate that the propagation phase can introduce 3dB or more of variability in noise predictions.

Lopes, Leonard↗
NASA NTRS2008

Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

Nark, Douglas M.↗
NASA NTRS1980

A unique coannular plug nozzle jet noise prediction procedure

The work presents a method for predicting jet mixing and shock noise spectra from coannular plug nozzles operated in the inverted velocity profile mode. It is shown that the jet mixing noise prediction method is based on the physics of the flow and its noise radiating characteristics, modeling the source spectrum, eddy convection, and fluid shrouding in a simplistic fashion. Further, the shock noise prediction procedure is described, noting that it is an extension of the Fisher-Harper-Bourne method for conical nozzles. Finally, it is concluded that the method has the potential of being extended to suppressors of complex geometries.

Bhutiani, P. K.↗
NASA NTRS2011

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Liu, Yi↗
NASA NTRS1978

Helicopter external noise prediction and correlation with flight test

Mathematical analysis procedures for predicting the main and tail rotor rotational and broadband noise are presented. The aerodynamic and acoustical data from Operational Loads Survey (OLS) flight program are used for validating the analysis and noise prediction methodology. For the long method of rotational noise prediction, the spanwise, chordwise, and azimuthwise airloading is used. In the short method, the airloads are assumed to be concentrated at a single spanwise station and for higher harmonics an airloading harmonic exponent of 2.0 is assumed. For the same flight condition, the predictions from long and short methods of rotational noise prediction are compared with the flight test results. The short method correlates as well or better than the long method.

Gupta, B. P.↗
NASA NTRS1982

Aircraft noise prediction program user's manual

The Aircraft Noise Prediction Program (ANOPP) predicts aircraft noise with the best methods available. This manual is designed to give the user an understanding of the capabilities of ANOPP and to show how to formulate problems and obtain solutions by using these capabilities. Sections within the manual document basic ANOPP concepts, ANOPP usage, ANOPP functional modules, ANOPP control statement procedure library, and ANOPP permanent data base. appendixes to the manual include information on preparing job decks for the operating systems in use, error diagnostics and recovery techniques, and a glossary of ANOPP terms.

Gillian, R. E.↗
NASA NTRS1989

Users' manual for the Langley high speed propeller noise prediction program (DFP-ATP)

The use of the Dunn-Farassat-Padula Advanced Technology Propeller (DFP-ATP) noise prediction program which computes the periodic acoustic pressure signature and spectrum generated by propellers moving with supersonic helical tip speeds is described. The program has the capacity of predicting noise produced by a single-rotation propeller (SRP) or a counter-rotation propeller (CRP) system with steady or unsteady blade loading. The computational method is based on two theoretical formulations developed by Farassat. One formulation is appropriate for subsonic sources, and the other for transonic or supersonic sources. Detailed descriptions of user input, program output, and two test cases are presented, as well as brief discussions of the theoretical formulations and computational algorithms employed.

Dunn, M. H.↗
NASA NTRS1977

An empirical model for inverted-velocity-profile jet noise prediction

It is known that the noise generated by inverted-velocity-profile coaxial (without center plug) and coannular (with center plug) nozzles should be modeled as the combined contributions of various source regions and noise generation mechanisms. In this paper, an empirical noise-prediction model is described which considers the noise generated by two jet-mixing regions and two potential regions of shock/turbulence interaction. Results calculated from the empirical model are compared with model-scale experimental data for static and simulated flight conditions. These comparisons are made for cases where both streams are subsonic, where the outer stream is supersonic with the inner stream subsonic, and where both streams are supersonic. The cases considered cover a range of inner-to-outer-stream area ratios and include both coaxial and coannular nozzles. It is shown that the model gives reasonable predictions of absolute noise spectra and even better predictions of incremental changes.

Stone, J. R.↗
NASA NTRS2004

The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

Farassat, F.↗