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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Aeroacoustic flowfield and acoustics of a model helicopter tail rotor at high advance ratio

Some results, relevant to rotorcraft noise generation process at high advance ratio, are presented in this paper from schlieren flow visualization and acoustic tests of a model tail rotor. The measured in-plane noise trends are consistent with the growth of the tip supersonic region seen in the schlieren visuals. Schlieren flow visuals reveal a propagating pressure wave in the second quadrant. Simultaneously measured acoustic data and the results of two-dimensional transonic Blade-Vortex Interaction analysis code ATRAN-2 indicate that this pressure wave is attributable to BVI activity in the first quadrant. This paper establishes that the transonic Blade-Vortex Interactions contribute to noise at high advance ratio level flight conditions.

Shenoy, Rajarama K.↗
NASA NTRS2009

Noise Control in Space Shuttle Orbiter

Acoustic limits in habitable space enclosures are required to ensure crew safety, comfort, and habitability. Noise control is implemented to ensure compliance with the acoustic requirements. The purpose of this paper is to describe problems with establishing acoustic requirements and noise control efforts, and present examples of noise control treatments and design applications used in the Space Shuttle Orbiter. Included is the need to implement the design discipline of acoustics early in the design process, and noise control throughout a program to ensure that limits are met. The use of dedicated personnel to provide expertise and oversight of acoustic requirements and noise control implementation has shown to be of value in the Space Shuttle Orbiter program. It is concluded that to achieve acceptable and safe noise levels in the crew habitable space, early resolution of acoustic requirements and implementation of effective noise control efforts are needed. Management support of established acoustic requirements and noise control efforts is essential.

Goodman, Jerry R.↗
NASA NTRS2018

A Recording-Based Method for Auralization of Rotorcraft Flyover Noise

Rotorcraft noise is an active field of study as the sound produced by these vehicles is often found to be annoying. A means to auralize rotorcraft flyover noise is sought to help understand the factors leading to annoyance. Previous work by the authors focused on auralization of rotorcraft fly-in noise, in which a simplification was made that enabled the source noise synthesis to be based on a single emission angle. Here, the goal is to auralize a complete flyover event, so the source noise synthesis must be capable of traversing a range of emission angles. The synthesis uses a source noise definition process that yields periodic and aperiodic (modulation) components at a set of discrete emission angles. In this work, only the periodic components are used for the source noise synthesis for the flyover; the inclusion of modulation components is the subject of ongoing research. Propagation of the synthesized source noise to a ground observer is performed using the NASA Auralization Framework. The method is demonstrated using ground recordings from a flight test of the AS350 helicopter for the source noise definition.

Pera, Nicholas M.↗
NASA NTRS1991

Propulsive lift noise

Propulsive life noise is the increase in noise that occurs when airframe surfaces are placed in the propulsive system's exhaust to increase their lift force. Increased local flow velocities and turbulence levels, due to the propulsive system exhaust gases passing along the airframe lifting surfaces, cause an increase in maximum lift coefficient. The airplane's flight speed required for takeoff and landing can then be significantly reduced, allowing operation from shorter runways than those of conventional commercial airports. Unfortunately, interaction of high velocity turbulent exhaust flow with the airframe's solid surfaces generates additional noise radiation. Aeroacoustic processes that cause propulsive lift noise also are present in airframe noise and propulsive system installation noise. Research studies of propulsive lift noise led to development of improved methods of predicting noise radiation from surfaces in turbulent flows. Noise reduction and prediction methods of aircraft noise are discussed.

Fink, Martin R.↗
NASA NTRS1994

Empirical modeling for intelligent, real-time manufacture control

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

Xu, Xiaoshu↗
DOE OSTI2022

DAISY Variant and Tether Tests, Admirality Inlet, WA

Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Admiralty Inlet (connecting Puget Sound to the Strait of San Juan de Fuca) in July 2022. Tests focused on occurrences of flow noise for three hydrophone package variants and on the potential for alternative tether materials.

16 TIDAL AND WAVE POWER↗
NASA NTRS1990

Reduced-order filtering for flexible space structures

There is a need for feedback control of the large flexible space structures which are going to be increasingly important in the future of the space program. These structures are very lightly damped, and vibrations may persist for a long time when the system is disturbed unless an active feedback control strategy is used to damp out the vibrations. The system is best described by a partial differential equation description, but the more common approach is to use a large set of second order differential equations, where a large number of modes must be retained if the mathematics is to provide an adequate description of the dynamical process. Sensors, such as accelerometers and rate gyros, may provide data to the feedback controller so that it may respond appropriately to control the system. The data from the sensors is not perfect, but is subject to noise, called measurement noise, and the dynamical process itself is subject to disturbances referred to as process noise. Filtering the sensor signals to remove the measurement noise, and using the resulting state estimates to control the system are investigated.

Sims, Craig S.↗
NASA NTRS2017

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗
DOE OSTI2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification

With increased adoption of supervised deep learning methods for work with cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) and the development of methods that increase model robustness are increasingly important. In the context of morphological classification of galaxies, we study the effects of perturbations in imaging data. In particular, we examine the consequences of using neural networks when training on baseline data and testing on perturbed data. We consider perturbations associated with two primary sources: (a) increased observational noise as represented by higher levels of Poisson noise and (b) data processing noise incurred by steps such as image compression or telescope errors as represented by one-pixel adversarial attacks. We also test the efficacy of domain adaptation techniques in mitigating the perturbation-driven errors. We use classification accuracy, latent space visualizations, and latent space distance to assess model robustness in the face of these perturbations. For deep learning models without domain adaptation, we find that processing pixel-level errors easily flip the classification into an incorrect class and that higher observational noise makes the model trained on low-noise data unable to classify galaxy morphologies. On the other hand, we show that training with domain adaptation improves model robustness and mitigates the effects of these perturbations, improving the classification accuracy up to 23% on data with higher observational noise. Domain adaptation also increases up to a factor of ${\approx}2.3$ the latent space distance between the baseline and the incorrectly classified one-pixel perturbed image, making the model more robust to inadvertent perturbations. Successful development and implementation of methods that increase model robustness in astronomical survey pipelines will help pave the way for many more uses of deep learning for astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Automated scanning probe microscopy of combinatorial ferroelectric libraries: Gaussian-process-guided exploration and noise-aware experiment planning

Combinatorial materials libraries provide an efficient route for mapping composition–property relationships, but their broader impact depends on rapid, quantitative, and functionally relevant characterization. Scanning Probe Microscopy (SPM), including piezoresponse force microscopy (PFM), offers significant potential for quantitative, functionally relevant combi-library readouts. Here, we implement a fully automated SPM workflow for ferroelectric combinatorial libraries and benchmark Gaussian-process-based Bayesian optimization strategies for autonomous experiment planning. The workflow integrates automated probe motion, contact optimization, imaging, and dual amplitude resonance tracking-PFM spectroscopy, and uses scalarized spectroscopic observables to guide subsequent measurements. Stage motion, probe engagement, in-contact tuning, imaging, spectroscopy, and the choice of the next measurement location all proceed without human input. We demonstrate the approach on Sm-doped BiFeO 3 and Zn x Mg 1−x O libraries. By comparing vanilla Bayesian optimization with a measured-noise variant, we show that explicit treatment of local reproducibility can improve modeling of composition-dependent response when the measured variance is physically meaningful, but can also reduce robustness when variability is dominated by outliers or topographic artifacts. Furthermore, these results establish automated SPM as a bridge between combinatorial synthesis and quantitative functional characterization.

Liu, Yu [University of Tennessee, Knoxville, TN (U↗
NASA NTRS2019

Auralization of Amplitude Modulated Helicopter Flyover Noise

Rotorcraft noise is an active field of study as the sound produced by these vehicles is often found to be annoying. A means to auralize rotorcraft flyover noise is sought to help understand the factors leading to annoyance. Previous work by the authors auralized a complete flyover event in which the source noise synthesis traversed a range of emission angles. The source noise definition process for the synthesis used helicopter flyover recordings. Although this process yielded both periodic and aperiodic (modulation) components at a set of discrete emission angles, only the periodic components were used in the previous work to synthesize the sound of the flyover event. In the current work, aperiodic amplitude modulation is incorporated into the source noise synthesis to improve its fidelity toward assessing rotorcraft noise annoyance. The method is demonstrated using ground recordings from a flight test of the AS350 helicopter for the source noise definition.

Krishnamurthy, Siddhartha↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2021

Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise

X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2016

The Role of Flow Diagnostic Techniques in Fan and Open Rotor Noise Modeling

A principal source of turbomachinery noise is the interaction of the rotating and stationary blade rows with the perturbations in the airstream through the engine. As such, a lot of research has been devoted to the study of the turbomachinery noise generation mechanisms. This is particularly true of fan and open rotors, both of which are the major contributors to the overall noise output of modern aircraft engines. Much of the research in fan and open rotor noise has been focused on developing theoretical models for predicting their noise characteristics. These models, which run the gamut from the semi-empirical to fully computational ones, are, in one form or another, informed by the description of the unsteady flow-field in which the propulsors (i.e., the fan and open rotors) operate. Not surprisingly, the fidelity of the theoretical models is dependent, to a large extent, on capturing the nuances of the unsteady flowfield that have a direct role in the noise generation process. As such, flow diagnostic techniques have proven to be indispensible in identifying the shortcoming of theoretical models and in helping to improve them. This presentation will provide a few examples of the role of flow diagnostic techniques in assessing the fidelity and robustness of the fan and open rotor noise prediction models.

Noise Prediction↗
NASA NTRS1979

Airframe noise component interaction studies

Acoustic wind tunnel tests were conducted to examine the noise-generating processes of an airframe during approach flight. The airframe model was a two-dimensional wing section, to which highlift leading and trailing edge devices and landing gear could be added. Far field conventional microphones were utilized to determine component spectrum levels. An acoustic mirror directional microphone was utilized to examine noise source distributions on airframe components extended separately and in combination. Measured quantities are compared with predictions inferred from aircraft flyover data. Aeroacoustic mechanisms for each airframe component are identified. Component interaction effects on total radiated noise generally were small (within about 2 dB). However, some interactions significantly redistributed the local noise source strengths by changing local flow velocities and turbulence levels. Possibilities for noise reduction exist if trailing edge flaps could be modified to decrease their noise radiation caused by incident turbulent flow.

Fink, M. R.↗
NASA NTRS1995

Signal-processing theory for the TurboRogue receiver

Signal-processing theory for the TurboRogue receiver is presented. The signal form is traced from its formation at the GPS satellite, to the receiver antenna, and then through the various stages of the receiver, including extraction of phase and delay. The analysis treats the effects of ionosphere, troposphere, signal quantization, receiver components, and system noise, covering processing in both the 'code mode' when the P code is not encrypted and in the 'P-codeless mode' when the P code is encrypted. As a possible future improvement to the current analog front end, an example of a highly digital front end is analyzed.

Thomas, J. B.↗
NASA NTRSDate not supplied

Medium-Sized Helicopter Noise Abatement Flight Test

An extensive flight test campaign was recently completed which aims to reduce the noise generated by helicopters in an effort to improve community acceptance. Using a ground-based microphone array, acoustic measurements were acquired on helicopters in the medium-size vehicle weight class over a number of flight conditions including steady level flight, steady descents, and approaches. While data were collected across four helicopters, the Leonardo AW139 and Sikorsky S-76D will be the focus of this paper. The extent of measured ground noise con- tours was limited due to the site constraints. Thus, the Noise Informed Community Environment Operations Planning System (NICEOPS) in conjunction with the flight test data was used to estimate how changes in the operating procedures impact noise exposure over a wider area during approaches. It was found that even small longitudinal accelerations can have a substantial influence on the noise generation processes during approach and must be modeled appropriately to develop new flight procedures which minimize the acoustic impact on the ground.

Flight Testing↗
NASA NTRS1996

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

NASA Discipline Cardiopulmonary↗