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At least 271 records · Page 15

DSN Beowulf Cluster-Based VLBI Correlator

The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database used to delegate parallel tasks between nodes and storage areas (see Figure 2). This script forks into three processes: extract, translate, and correlate. Each of these processes iterates on available scan data and updates the status database as the work for each scan is completed. The extract process coordinates and monitors the transfer of data from each of the Mark5s to the Beowulf RAID storage systems. The translate process monitors and executes the data conversion processes on available scan files, and writes the translated files to the slave nodes. The correlate process monitors the execution of SoftC correlation processes on the slave nodes for scans that have completed translation. A comparison of the JVC and the legacy Block II correlator outputs reveals they are well within a formal error, and that the data are comparable with respect to their use in flight navigation. The processing speed of the JVC is improved over the Block II correlator by a factor of 4, largely due to the elimination of the reel-to-reel tape drives used in the Block II correlator.

Rogstad, Stephen P.↗

Effect of Initial Condition on Subsonic Jet Noise from Two Rectangular Nozzles

Differences in jet noise data from two small 8:1 aspect ratio nozzles are investigated experimentally. The interiors of the two nozzles are identical but one has a thin-lip at the exit while the has a perpendicular face at the exit (thick-lip). It is found that the thin-lip nozzle is substantially noisier throughout the subsonic Mach number range. As much as 5dB difference in OASPL is noticed around Mj =0.96. Hot-wire measurements are carried out for the characteristics of the exit boundary layer and, overall, the noise difference can be ascribed to differences in the boundary layer state. The boundary layer of the quieter (thick-lip) nozzle goes through transition around M(sub j) =0.25 and at higher M(sub j) it remains "nominally turbulent". In comparison, the boundary layer of the thin-lip nozzle is found to remain "nominally laminar". at high subsonic conditions. The nominally laminar state involves significantly larger turbulence intensities commensurate with the higher radiated noise.

Zaman, K. B. M. Q.↗

Seasat over-land scatterometer data. II - Selection of extended area land-target sites for the calibration of spaceborne scatterometers

The post-launch performance verification for future scatterometers can use extended area land targets to calibrate antenna gain patterns and to verify and monitor deployment configurations. For the Ku-band Seasat scatterometer, a region of tropical rain forest in the Amazon basin was used as a homogeneous extended-area land target. As this region is continuously being deforested, other regions are investigated for calibrating scatterometers. The global backscatter coefficients (sigma0) are compared to classifications of natural vegetation and cultivation intensity and the variability with time during the three-month mission is studied. The statistical variability of sigma0 is compared with prior estimates resulting from the known variability of the instrument parameters and communication noise. Data from selected forested regions with relatively homogeneous sigma0 and little time-dependence are presented.

Kennett, Rosemary G.↗

Computation of Engine Noise Propagation and Scattering Off an Aircraft

The paper presents a comparison of experimental noise data measured in flight on a two-engine business jet aircraft with Kulite microphones placed on the suction surface of the wing with computational results. Both a time-domain discontinuous Galerkin spectral method and a frequency-domain spectral element method are used to simulate the radiation of the dominant spinning mode from the engine and its reflection and scattering by the fuselage and the wing. Both methods are implemented in computer codes that use the distributed memory model to make use of large parallel architectures. The results show that trends of the noise field are well predicted by both methods.

Xu, J.↗

Noise measurements for various configurations of a model of a mixer nozzle externally blown flap system

Noise data were taken for variations to a large scale model of an externally blown flap lift augmentation system. The variations included two different mixer nozzles (7 and 8 lobes), two different wing models (2 and 3 flaps), and different lateral distances between the wing chord line and the nozzle centerline. When the seven lobe was used with the trailing flap in the 60 deg position, increasing the wing to nozzle distance had no effect on the sound level. When the eight lobe nozzle was used there was a decrease in sound level. With the 20 deg flap setting the noise level decreased when the distance was increased using either nozzle.

Goodykoontz, J. H.↗

Ground Measurements of the Shock-Wave Noise from Airplanes in Level Flight at Mach Numbers to 1.4 and at Altitudes to 45000 Feet

Time histories of noise pressures near ground level were measured during flight tests of fighter-type airplanes over fairly flat, partly wooded terrain in the e Mach number range between 1.13 and 1.4 and at altitudes from 25,000 to 45,000 feet. Atmospheric soundings and radar tracking studies were made for correlation with the measured noise data. The measured and calculated values of the pressure rise across the shock wave were generally in good agreement. There is a tendency for the theory to overestimate the pressure at locations remote from the track and to underestimate the pressures for conditions of high tailwind at altitude. The measured values of ground-reflection factor averaged about 1.8 f or the surface tested as compared to a theoretical value of 2.0. P o booms were measured in all cases. The observers also generally reported two booms; although, in some cases, only one boom was reported. The shock-wave noise associated with some of the flight tests was judged to be objectionable by ground observers, and in one case the cracking of a plate-glass store window was correlated in time with the passage of the airplane at an altitude of 25,000 feet.

Maglieri, Domenic J.↗

Measuring Greenland Ice Mass Variation With Gravity Recovery and the Climate Experiment Gravity and GPS

The response of the Greenland ice sheet to climate change could significantly alter sea level. The ice sheet was much thicker at the last glacial maximum. To gain insight into the global change process and the future trend, it is important to evaluate the ice mass variation as a function of time and space. The Gravity Recovery and Climate Experiment (GRACE) mission to fly in 2001 for 5 years will measure gravity changes associated with the current ice variation and the solid earth's response to past variations. Our objective is to assess the separability of different change sources, accuracy and resolution in the mass variation determination by the new gravity data and possible Global Positioning System (GPS) bedrock uplift measurements. We use a reference parameter state that follows a dynamic ice model for current mass variation and a variant of the Tushingham and Peltier ICE-3G deglaciation model for historical deglaciation. The current linear trend is also assumed to have started 5 kyr ago. The Earth model is fixed as preliminary reference Earth model (PREM) with four viscoelastic layers. A discrete Bayesian inverse algorithm is developed employing an isotropic Gaussian a priori covariance function over the ice sheet and time. We use data noise predicted by the University of Texas and JPL for major GRACE error sources. A 2 mm/yr uplift uncertainty is assumed for GPS occupation time of 5 years. We then carry out covariance analysis and inverse simulation using GRACE geoid coefficients up to degree 180 in conjunction with a number of GPS uplift rates. Present-day ice mass variation and historical deglaciation are solved simultaneously over 146 grids of roughly 110 km x 110 km and with 6 time increments of 3 kyr each, along with a common starting epoch of the current trend. For present-day ice thickness change, the covariance analysis using GRACE geoid data alone results in a root mean square (RMS) posterior root variance of 2.6 cm/yr, with fairly large a priori uncertainties in the parameters and a Gaussian correlation length of 350 km. Simulated inverse can successfully recover most features in the reference present-day change. The RMS difference between them over the grids is 2.8 cm/yr. The RMS difference becomes 1.1 cm/yr when both are averaged with a half Gaussian wavelength of 150 km. With a fixed Earth model, GRACE alone can separate the geoid signals due to past and current load fairly well. Shown are the reference geoid signatures of direct and elastic effects of the current trend, the viscoelastic effect of the same trend starting from 5 kyr ago, the Post Glacial Rebound (PGR), and the predicted GRACE geoid error. The difference between the reference and inverse modeled total viscoelastic signatures is also shown. Although past and current ice mass variations are allowed the same spatial scale, their geoid signals have different spatial patterns. GPS data can contribute to the ice mass determination as well. Additional information is contained in the original.

Wu, Xiao-Ping↗

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.↗

The Noise of a Forward Swept Fan

A forward swept fan, designated the Quiet High Speed Fan (QHSF), was tested in the NASA Glenn 9-by 15-foot Low Speed Wind Tunnel to investigate its noise reduction relative to a baseline fan of the same aerodynamic performance. The objective of the Quiet High Speed Fan was a 6 decibel reduction in the Effective Perceived Noise relative to the baseline fan at the takeoff condition. The intent of the Quiet High Speed Fan design was to provide both a multiple pure tone noise reduction from the forward sweep of the fan rotor and a rotor-stator interaction blade passing tone noise reduction from a leaned stator. The tunnel noise data indicted that the Quiet High Speed Fan was quieter than the baseline fan for a significant portion of the operating line and was 6 dB quieter near the takeoff condition. Although reductions in the multiple pure tones were observed, the vast majority of the EPNdB reduction was a result of the reduction in the blade passing tone and its harmonics. The baseline fan's blade passing tone was dominated by the rotor-strut interaction mechanism. The observed blade passing tone reduction could be the result of either the redesign of the Quiet High Speed Fan Rotor or the redesigned stator. The exact cause of this rotor-strut noise reduction, whether from the rotor or stator redesign, was not discernable from this experiment.

Dittmar, James H.↗

Aircraft Noise and Performance Data for a Notional Supersonic Business Jet

The International Civil Aviation Organization recently completed a study that determined the global environmental impact of adding several hypothetical supersonic aircraft types to the existing subsonic fleet. NASA supported this study by designing a notional 55-tonne supersonic business jet. The airplane is named the Supersonic Technology Concept Aeroplane by the international community. Performance, noise, and exhaust emission predictions for this transport were used to inform development of new environmental standards for future supersonic civil aircraft. The behavior of the aircraft in an operational setting is considered. Calculation of aircraft noise and performance data for this aircraft is the focus of this paper. Noise abatement departure procedures, stage length performance, and noise-power-distance data are determined using NASA tools. Also investigated are some of the anticipated behaviors and requirements of supersonic aircraft in the commercial airspace.

Aircraft noise↗

Jet Mixing Noise Scaling Laws SHJAR Data Vs. Predictions

High quality jet noise spectral data measured at the anechoic dome at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent as well as convergent-divergent axisymmetric nozzles. The spectral measurements are shown in narrow band and cover 8193 equally spaced points in a typical Strouhal number range of (0.01 10.0). Measurements are reported as lossless (i.e. atmospheric attenuation is added to as-measured data), and at 24 equally spaced angles (50deg to 165deg) on a 100-diameter arc. Following the work of Viswanathan [Ref. 1], velocity power laws are derived using a least square fit on spectral power density as a function of jet temperature and observer angle. The goodness of the fit is studied at each angle, and alternative relationships are proposed to improve the spectral collapse when certain conditions are met. On the application side, power laws are extremely useful in identifying components from various noise generation mechanisms. From this analysis, jet noise prediction tools can be developed with physics derived from the different spectral components.

Khavaran, Abbas↗

Advancing-side directivity and retreating-side interactions of model rotor blade-vortex interaction noise

Acoustic data are presented from a 40 percent scale model of the four-bladed BO-105 helicopter main rotor, tested in a large aerodynamic wind tunnel. Rotor blade-vortex interaction (BVI) noise data in the low-speed flight range were acquired using a traversing in-flow microphone array. Acoustic results presented are used to assess the acoustic far field of BVI noise, to map the directivity and temporal characteristics of BVI impulsive noise, and to show the existence of retreating-side BVI signals. The characterics of the acoustic radiation patterns, which can often be strongly focused, are found to be very dependent on rotor operating condition. The acoustic signals exhibit multiple blade-vortex interactions per blade with broad impulsive content at lower speeds, while at higher speeds, they exhibit fewer interactions per blade, with much sharper, higher amplitude acoustic signals. Moderate-amplitude BVI acoustic signals measured under the aft retreating quadrant of the rotor are shown to originate from the retreating side of the rotor.

Martin, R. M.↗

Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites

Phenolic resins are commonly used as carbon precursors for the fabrication of carbon/carbon composites due to their high carbon yield and aromatic nature. To decrease curing times, acid catalysts are generally used, but the addition of resorcinol was found to have a similar effect while being incorporated into the resin matrix with no contamination or corrosion issues. In this work, the curing kinetics of pure, 10, 20, and 30 wt% resorcinol-added phenolic resins were investigated through differential scanning calorimetry. Heating rates of 0.5, 1, 2.5, and 5°C min -1 were used with several curing models to predict isothermal curing. Averaged mean absolute error (MAE) for the isoconversional mathematical approaches namely Kissinger–Akahira–Sunose (MAE = 12.9 min), Flynn–Wall–Ozawa (15.8 min), and Vyazovkin (14 min) show that these methods provide the best predictions, attributed to their adoption of an activation energy that depends on the extent of cure (E a (α)). The Kissinger method (MAE = 36 min), which depends only on peak temperature with a constant activation energy assumption, and the data noise sensitive Friedman model (MAE = 1144.7 min) provide the least accurate results. Thermogravimetric analysis revealed that resorcinol decreases the curing times by up to 71% without lowering carbon yield.

36 MATERIALS SCIENCE↗

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗

On the analysis of signal peaks in pulse-height spectra

The estimation of the signal location and intensity of a peak in a pulse height spectrum is important for X- ray and γ-ray spectroscopy, charged-particle spectrometry, liquid chromatography, and many other subfields. However, both the ‘‘centroid’’ and ‘‘signal intensity’’ of a peak in a pulse-height spectrum are ill-defined quantities and different methods of analysis will yield different numerical results. Here, we apply three methods of analysis. Method A is based on simple count summation and is likely the technique most frequently applied in practice. The analysis is straightforward and fast, and does not involve any statistical modeling. We find that it provides reliable results only for high signal-to-noise data, but has severe limitations in all other cases. Method B employs a Bayesian model to extract signal counts and centroid from the measured total and background counts. The resulting values are derived from the respective posteriors and, therefore, have a rigorous statistical meaning. The method makes no assumptions about the peak shape. It yields reliable and relatively small centroid uncertainties. However, it provides relatively large signal count uncertainties. Method C makes a strong assumption regarding the peak shape by fitting a Gaussian function to the data. Furthermore, the fit is based again on a Bayesian model. Although Method C requires careful consideration of the Gaussian width (usually given by the detector resolution) used in the fitting, it provides reliable values and relatively small uncertainties both for the signal counts and the centroid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Clear-sky detection for PV degradation analysis using multiple regression

A method is presented to detect clear-sky periods for plane-of-array irradiance time-averaged data that is based on the algorithm originally described by Reno and Hansen. Here we show this new method improves the state-of-the-art by providing accurate detection at longer data averaging intervals. Moreover, our new method detects clear periods in plane-of-array data, which is novel. The new method is developed by applying a Design of Experiment approach to optimize the parameters used in the Reno method, and Monte Carlo simulations are used to understand the robustness of the found parameters. Clear-sky detection accuracy is compared among four methods: the Reno method, the default clear-sky filter in RdTools, the Ellis method, and the method outlined in this work, using a hand-labeled two-year data set of 1-min plane-of-array irradiance for a fixed tilt system. The RdTools clear-sky filter is marred by excessive false positives. The other methods all perform well at 1-min data intervals; the method developed here provides more accurate detection at longer data averaging intervals. We show that the parameters are directly linked to the data frequency in the hope that these input variables may not have to be optimized for every data frequency and location. However, only a single fixed system in one location was carefully examined. Finally, we illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

14 SOLAR ENERGY↗

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗