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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models de(ived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, Joseph↗
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models derived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, J.↗
NASA NTRS1983

The fundamental structure function of oscillator noise models

Continuous-time models of oscillator phase noise x(t) usually have stationary nth differences, for some n. The covariance structure of such a model can be characterized in the time domain by the structure function: D sub n (t;gamma sub 1, gamma sub 2) = E delta (n) sub gamma sub 1 x(s+t) delta(n) sub gamma sub 2 x (s). Although formulas for the special case D sub 2 (0;gamma,gamma) (the Allan variance times 2 gamma(2)) exist for power-law spectral models, certain estimation problems require a more complete knowledge of (0). Exhibited is a much simpler function of one time variable, D(t), from which (0) can easily be obtained from the spectral density by uncomplicated integrations. Believing that D(t) is the simplest function of time that holds the same information as (0), D(t) is called the fundamental structure function. D(t) is computed for several power-law spectral models. Two examples are D(t) = K/t/(3) for random walk FM, D(t) = Kt(2) 1n/t/ for flicker FM. Then, to demonstrate its use, a BASIC program is given that computes means and variances of two Allan variance estimators, one of which incorporates a method of frequency drift estimation and removal.

Greenhall, C. A.↗
NASA NTRS2011

The Effects of Ambient Conditions on Helicopter Rotor Source Noise Modeling

A new physics-based method called Fundamental Rotorcraft Acoustic Modeling from Experiments (FRAME) is used to demonstrate the change in rotor harmonic noise of a helicopter operating at different ambient conditions. FRAME is based upon a non-dimensional representation of the governing acoustic and performance equations of a single rotor helicopter. Measured external noise is used together with parameter identification techniques to develop a model of helicopter external noise that is a hybrid between theory and experiment. The FRAME method is used to evaluate the main rotor harmonic noise of a Bell 206B3 helicopter operating at different altitudes. The variation with altitude of Blade-Vortex Interaction (BVI) noise, known to be a strong function of the helicopter s advance ratio, is dependent upon which definition of airspeed is flown by the pilot. If normal flight procedures are followed and indicated airspeed (IAS) is held constant, the true airspeed (TAS) of the helicopter increases with altitude. This causes an increase in advance ratio and a decrease in the speed of sound which results in large changes to BVI noise levels. Results also show that thickness noise on this helicopter becomes more intense at high altitudes where advancing tip Mach number increases because the speed of sound is decreasing and advance ratio increasing for the same indicated airspeed. These results suggest that existing measurement-based empirically derived helicopter rotor noise source models may give incorrect noise estimates when they are used at conditions where data were not measured and may need to be corrected for mission land-use planning purposes.

Schmitz, Frederic H.↗
NASA NTRSDate not supplied

Simultaneous Use of Ground Reflection and Lateral Attenuation Noise Models

Ground reflections and lateral attenuation due to refraction and scattering are two effects of acoustic propagation that can strongly influence noise received by an observer. Software that predicts community aviation noise can be reliant on ground reflection models to predict noise at receivers. However, empirical lateral attenuation models often include the influence of ground reflections implicitly, so a double-bookkeeping error can exist if one is used together with a reflection model. An accounting method that reconciles this bookkeeping issue for the Chien and Soroka reflection model and a Society of Automotive Engineers lateral attenuation model is presented. Importance to emerging supersonic civil aircraft is discussed.

noise↗
NASA NTRSDate not supplied

Simultaneous use of Ground Reflection and Lateral Attenuation Noise Models

Ground reflections and lateral attenuation due to refraction and scattering are two effects of acoustic propagation that can strongly influence noise received by an observer. Software that predicts community aviation noise can be reliant on ground reflection models to predict noise at receivers. However, empirical lateral attenuation models often include the influence of ground reflections implicitly, so a double-bookkeeping error can exist if one is used together with a reflection model. An accounting method that reconciles this bookkeeping issue for the Chien and Soroka reflection model and a Society of Automotive Engineers lateral attenuation model is presented. Importance to emerging supersonic civil aircraft is discussed.

noise↗
NASA NTRS2012

A Comparison of Combustor-Noise Models

The current status of combustor-noise prediction in the NASA Aircraft Noise Prediction Program (ANOPP) for current-generation (N) turbofan engines is summarized. Best methods for near-term updates are reviewed. Long-term needs and challenges for the N+1 through N+3 timeframe are discussed. This work was carried out under the NASA Fundamental Aeronautics Program, Subsonic Fixed Wing Project, Quiet Aircraft Subproject.

Hultgren, Lennart, S.↗
NASA NTRS1983

Aircraft interior noise models - Sidewall trim, stiffened structures, and cabin acoustics with floor partition

As part of the continuing development of an aircraft interior noise prediction model, in which a discrete modal representation and power flow analysis are used, theoretical results are considered for inclusion of sidewall trim, stiffened structures, and cabin acoustics with floor partition. For validation purposes, predictions of the noise reductions for three test articles (a bare ring-stringer stiffened cylinder, an unstiffened cylinder with floor and insulation, and a ring-stringer stiffened cylinder with floor and sidewall trim) are compared with measurements.

Pope, L. D.↗
NASA NTRS2006

Measurement of Model Noise in a Hard-Wall Wind Tunnel

Identification, analysis, and control of fluid-mechanically-generated sound from models of aircraft and automobiles in special low-noise, semi-anechoic wind tunnels are an important research endeavor. Such studies can also be done in aerodynamic wind tunnels that have hard walls if phased microphone arrays are used to focus on the noise-source regions and reject unwanted reflections or background noise. Although it may be difficult to simulate the total flyover or drive-by noise in a closed wind tunnel, individual noise sources can be isolated and analyzed. An acoustic and aerodynamic study was made of a 7-percent-scale aircraft model in a NASA Ames 7-by-10-ft (about 2-by-3-m) wind tunnel for the purpose of identifying and attenuating airframe noise sources. Simulated landing, takeoff, and approach configurations were evaluated at Mach 0.26. Using a phased microphone array mounted in the ceiling over the inverted model, various noise sources in the high-lift system, landing gear, fins, and miscellaneous other components were located and compared for sound level and frequency at one flyover location. Numerous noise-alleviation devices and modifications of the model were evaluated. Simultaneously with acoustic measurements, aerodynamic forces were recorded to document aircraft conditions and any performance changes caused by geometric modifications. Most modern microphone-array systems function in the frequency domain in the sense that spectra of the microphone outputs are computed, then operations are performed on the matrices of microphone-signal cross-spectra. The entire acoustic field at one station in such a system is acquired quickly and interrogated during postprocessing. Beam-forming algorithms are employed to scan a plane near the model surface and locate noise sources while rejecting most background noise and spurious reflections. In the case of the system used in this study, previous studies in the wind tunnel have identified noise sources up to 19 dB below the normal background noise of the wind tunnel. Theoretical predictions of array performance are used to minimize the width and the side lobes of the beam pattern of the microphone array for a given test arrangement. To capture flyover noise of the inverted model, a 104-element microphone array in a 622-mm-diameter cluster was installed in a 19-mm-thick poly(methyl methacrylate) plate in the ceiling of the test section of the wind tunnel above the aircraft model (see Figure 1). The microphones were of the condenser type, and their diaphragms were mounted flush in the array plate, which was recessed 12.7 mm into the ceiling and covered by a porous aromatic polyamide cloth (not shown in the figure) to minimize boundary-layer noise. This design caused the level of flow noise to be much less than that of flush-mount designs. The drawback of this design was that the cloth attenuated sound somewhat and created acoustic resonances that could grow to several dB at a frequency of 10 kHz.

Soderman, Paul T.↗
NASA NTRS1984

Propeller aircraft interior noise model

An analytical model was developed to predict the interior noise of propeller-driven aircraft. The fuselage model is that of a cylinder with a structurally-integral floor. The cabin sidewall is stiffened by stringers and ring frames, and the floor by longitudinal beams. The cabin interior is covered with a sidewall treatments consisting of layers of porous material and an impervious trim septum. Representation of the propeller pressure field is utilized as input data in the form of the propeller noise signature at a series of locations on a grid over the fuselage structure. Results obtained from the analytical model are compared with test data measured by NASA in a scale model cylindrical fuselage excited by a model propeller.

Pope, L. D.↗
NASA NTRS2016

Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models

The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.

Jet↗
NASA NTRS2016

Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models

The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.

Aircraft↗
NASA NTRS2020

A Machine Learning Approach to Jet-Surface Interaction Noise Modeling

This paper investigates using machine learning to rapidly develop empirical models suitable for system-level aircraft noise studies. In particular, machine learning is used to train a neural network to predict the noise spectra produced by a round jet near a surface over a range of surface lengths, surface standoff distances, jet Mach numbers, and observer angles. These spectra include two sources, jet-mixing noise and jet-surface interaction (JSI) noise, with different scale factors as well as surface shielding and reflection effects to create a multi- dimensional problem. A second model is then trained using data from three rectangular nozzles to include nozzle aspect ratio in the spectral prediction. The training and validation data are from an extensive jet-surface interaction noise database acquired at the NASA Glenn Research Center's Aero-Acoustic Propulsion Laboratory. Although the number of training and validation points is small compared a typical machine learning application, the results of this investigation show that this approach is viable if the underlying data are well behaved.

Brown, Cliff↗
NASA NTRS2016

Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models

The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.

Aircraft↗
NASA NTRS2014

Enhanced Fan Noise Modeling for Turbofan Engines

This report describes work by consultants to Diversitech Inc. for the NASA Glenn Research Center (GRC) to revise the fan noise prediction procedure based on fan noise data obtained in the 9- by 15 Foot Low-Speed Wind Tunnel at GRC. The purpose of this task is to begin development of an enhanced, analytical, more physics-based, fan noise prediction method applicable to commercial turbofan propulsion systems. The method is to be suitable for programming into a computational model for eventual incorporation into NASA's current aircraft system noise prediction computer codes. The scope of this task is in alignment with the mission of the Propulsion 21 research effort conducted by the coalition of NASA, state government, industry, and academia to develop aeropropulsion technologies. A model for fan noise prediction was developed based on measured noise levels for the R4 rotor with several outlet guide vane variations and three fan exhaust areas. The model predicts the complete fan noise spectrum, including broadband noise, tones, and for supersonic tip speeds, combination tones. Both spectra and directivity are predicted. Good agreement with data was achieved for all fan geometries. Comparisons with data from a second fan, the ADP fan, also showed good agreement.

aircraft↗
NASA NTRS1985

Propeller aircraft interior noise model: User's manual for computer program

A computer program entitled PAIN (Propeller Aircraft Interior Noise) has been developed to permit calculation of the sound levels in the cabin of a propeller-driven airplane. The fuselage is modeled as a cylinder with a structurally integral floor, the cabin sidewall and floor being stiffened by ring frames, stringers and floor beams of arbitrary configurations. The cabin interior is covered with acoustic treatment and trim. The propeller noise consists of a series of tones at harmonics of the blade passage frequency. Input data required by the program include the mechanical and acoustical properties of the fuselage structure and sidewall trim. Also, the precise propeller noise signature must be defined on a grid that lies in the fuselage skin. The propeller data are generated with a propeller noise prediction program such as the NASA Langley ANOPP program. The program PAIN permits the calculation of the space-average interior sound levels for the first ten harmonics of a propeller rotating alongside the fuselage. User instructions for PAIN are given in the report. Development of the analytical model is presented in NASA CR 3813.

Wilby, E. G.↗
NASA NTRS1977

Theoretical jet exhaust noise model for the duct burning turbofan

A model was developed to predict the acoustic power spectrum for a Duct Burning Turbofan (DBTF) whose cycle results in a high velocity, high temperature fan stream and a lower velocity, lower temperature primary stream. Model tests have demonstrated that a DBTF may produce substantially less noise than a conventional turbojet with the same thrust and weight flow. Predictions from the model agreed well with measured data from the model tests. The characteristics of the DBTF acoustic power spectrum were shown to be related to the rapid mixing of the fan and primary streams. The effects of fan to primary velocity ratio, temperature ratio, area ratio, and the effect of nozzle geometry on DBTF jet noise were determined.

Larson, R. S.↗