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At least 73 records · Page 4

An Analysis of the Speed Commands from an Interval Management Algorithm during the ATD-1 Flight Test

NASA's first Air Traffic Management Technology Demonstration (ATD-1) successfully completed a nineteen-day flight test under a NASA contract with Boeing, with Honeywell and United Airlines as sub-contractors. An Interval Management (IM) avionics prototype was built based on international IM standards, integrated into two test aircraft, and then flown in real-world conditions to determine if the goals of improving aircraft efficiency and airport throughput during high-density arrival operations could be met. This paper describes the speed behavior of the IM avionics prototype, focusing on the speed command rate and the number of speed increases.

Watters, Christine↗

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗

Contour maps of lunar remanent magnetic fields

The 2605 usable orbits of Apollo 15 and 16 subsatellite magnetometer data have been reexamined for intervals suitable for analysis of crustal magnetic anomalies. To minimize plasma-related disturbances, segments from 274 of these orbits were selected from times when the moon was either in a lobe of the geomagnetic tail or in the solar wind with the subsatellites in the lunar wake. External field contributions which remained in the selected intervals were minimized by (1) quadratic detrending of individual orbit segments with lengths much greater than anomaly wavelengths and (2) two-dimensional filtering with minimum passed wavelengths less than or equal to anomaly wavelengths. Improvements in coverage, accuracy, and resolution of previously published anomaly maps produced from these data are obtained. In addition to improved maps of the Reiner Gamma and Van de Graaff-Aitken anomalies studied previously, a third region of relatively high-amplitude anomalies centered near the crater Gerasimovich on the southeastern far side has been mapped. Both the Van de Graaff-Aitken region and the Gerasimovich region are marked by the general occurrence of extensive groups of Reiner Gamma-type swirls.

Hood, L. L.↗

KSC 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT) Report

This report documents analysis results of the Kennedy Space Center updated 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). This test was designed to demonstrate that the new DRWP operates in a similar manner to the previous DRWP for use as a situational awareness asset for mission operations at the Eastern Range to identify rapid changes in the wind environment that weather balloons cannot depict. Data examination and two analyses showed that the updated DRWP meets the specifications in the OAT test plan and performs at least as well as the previous DRWP. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 5,426 wind component reports from 49 concurrent DRWP and balloon profiles presented root mean square (RMS) wind component differences around 2.0 m/s. The DRWP's effective vertical resolution (EVR) was found to be 300 m for both the westerly and southerly wind component, which the best EVR possible given the DRWP's vertical sampling interval. A third analysis quantified the sensitivity to rejecting data that do not have adequate signal by assessing the number of first-guess propagations at each altitude. This report documents the data, quality control procedures, methodology, and results of each analysis. It also shows that analysis of the updated DRWP produced results that were at least as good as the previous DRWP with proper rationale. The report recommends acceptance of the updated DRWP for situational awareness usage as per the OAT's intent.

Profiler↗

A Comment on the Suspected Solar Neutrino-Solar Activity Connection

Recently, it has been proposed that there exists a highly statistically significant (at greater than or equal to 98% level of confidence) relationship between Ar-37 production rate (viz., solar neutrinos) and the Ap geomagnetic index (viz., solar particles), based on the (chi)-square goodness-of-fit test and correlation analysis, for the interval 1970-1990. While a relationship between the two parameters, indeed, seems to be discernible, the strength of the relationship has been overstated. Instead of being significant at the afore-mentioned level of confidence, the relationship is found to be significant at only greater than or equal to 95% level of confidence, based on Yates' modification to the (chi)-square test for 2 x 2 contingency tables. Likewise, while correlation analysis yields a value of r = 0.2691, it is important to note that such a value suggests that only about 7% of the variance can be 'explained' by the inferred correlation and that the remaining 93% of the variance must be attributed to other sources.

Wilson, Robert M.↗

Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction

BACKGROUND: Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. METHODS AND RESULTS: Time and frequency domain heart rate (HR) variability measures, along with short- and long-term correlation (fractal) properties of R-R intervals (exponents alpha(1) and alpha(2)) and power-law scaling of the power spectra (exponent beta), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction </=35%). During a mean+/-SD follow-up period of 685+/-360 days, 114 patients died (25.6%), with 75 deaths classified as arrhythmic (17.0%) and 28 as nonarrhythmic (6.3%) cardiac deaths. Several traditional and fractal measures of R-R interval variability were significant univariate predictors of all-cause mortality. Reduced short-term scaling exponent alpha(1) was the most powerful R-R interval variability measure as a predictor of all-cause mortality (alpha(1) <0.75, relative risk 3.0, 95% confidence interval 2.5 to 4.2, P<0.001). It remained an independent predictor of death (P<0.001) after adjustment for other postinfarction risk markers, such as age, ejection fraction, NYHA class, and medication. Reduced alpha(1) predicted both arrhythmic death (P<0.001) and nonarrhythmic cardiac death (P<0.001). CONCLUSIONS: Analysis of the fractal characteristics of short-term R-R interval dynamics yields more powerful prognostic information than the traditional measures of HR variability among patients with depressed left ventricular function after an acute myocardial infarction.

Non-NASA Center↗

A comment on the suspected solar neutrino -- solar activity connection

Recently, it has been proposed that there exists a highly statistically significant (at greater than or equal to 98% level of confidence) relationship between Ar-37 production rate (namely, solar neutrinos) and the Ap geomagnetic index (namely, solar particles), based on the chi-square goodness-of-fit test and correlation analysis, for the interval 1970-1990. While a relationship between the two parameters, indeed, seems to be discernible, the strength of the relationship has been overstated. Instead of being significant at the afore-mentioned level of confidence, the relationship is found to be significant at only greater than or equal to 95% level of confidence, based on Yates' modification to the chi-square test for 2 x 2 contingency tables. Likewise, while correlation analysis yields a value of r = 0.2691, it is important to note that such a value suggests that only about 7% of the variance can be 'explained' by the inferred correlation and that the remaining 93% of the variance must be attributed to other sources.

Wilson, Robert M.↗

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Overwrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter uncertainties are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

Grimes-Ledesma, Lorie↗

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Ovenvrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter error are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

stress ratios↗

Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability margins. At each time point, the system was linearized about the current operating point using Simulink's built-in solver. Each linearized system in time was evaluated for its rigid-body gain margin (high frequency gain margin), rigid-body phase margin, and aero gain margin (low frequency gain margin) for each control axis. Using the stability margins derived from the baseline linearization approach, the time domain derived stability margins were determined by executing time domain simulations in which axis-specific incremental gain and phase adjustments were made to the nominal system about the expected neutral stability point at specific flight times. The baseline stability margin time histories were used to shift the system gain to various values around the zero margin point such that a precise amount of expected gain margin was maintained throughout flight. When assessing the gain margins, the gain was applied starting at the time point under consideration, thereafter following the variation in the margin found in the linear analysis. When assessing the rigid-body phase margin, a constant time delay was applied to the system starting at the time point under consideration. If the baseline stability margins were correctly determined via the linear analysis, the time domain simulation results should contain unstable behavior at certain gain and phase values. Examples will be shown from repeated simulations with variable added gain and phase lag. Faithfulness of margins calculated from the linear analysis to the nonlinear system will be demonstrated.

Kiefer, J. M.↗

Observations of Mantle Seismic Anisotropy Using Array Techniques: Shear-Wave Splitting of Beamformed SmKS Phases

Shear-wave splitting measurements are commonly used to resolve seismic anisotropy in both the upper and lowermost mantle. Typically, such techniques are applied to SmKS phases that have reflected (m-1) times off the underside of the core-mantle boundary before being recorded. Practical constraints for shear-wave splitting studies include the limited number of suitable phases as well as the large fraction of available data discarded because of poor signal-to-noise ratios (SNRs) or large measurement uncertainties. Array techniques such as beamforming are commonly used in observational seismology to enhance SNRs, but have not been applied before to improve SmKS signal strength and coherency for shear wave splitting studies. Here, we investigate how a beamforming methodology, based on slowness and backazimuth vespagrams to determine the most coherent incoming wave direction, can improve shear-wave splitting measurement confidence intervals. Through the analysis of real and synthetic seismograms, we show that (a) the splitting measurements obtained from the beamformed seismograms (beams) reflect an average of the single-station splitting parameters that contribute to the beam; (b) the beams have (on average) more than twice as large SNRs than the single-station seismograms that contribute to the beam; (c) the increased SNRs allow the reliable measurement of shear wave splitting parameters from beams down to average single-station SNRs of 1.3. Beamforming may thus be helpful to more reliably measure splitting due to upper mantle anisotropy. Moreover, here we show that beamforming holds potential to greatly improve detection of lowermost mantle anisotropy by demonstrating differential SKS–SKKS splitting analysis using beamformed USArray data.

54 ENVIRONMENTAL SCIENCES↗

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Upper limits on the cyclotron lines from Her X-1 as observed with OSO-8

Observations of Her X-1 were obtained during its ON-state in September, 1977, with the high-energy X-ray detector on board OSO-8. Upper limits on the line fluxes at 60 and 135 keV based on these observations are above, and hence consistent with, the positive results reported by Trumper, et al from a balloon flight during the same time interval. A detailed analysis of the time-variable et al background spectrum suggests that the line emission, especially in the time-averaged spectrum of Her X-1 previously reported by other workers at 25, 60, and 135 keV, is due to instrumental effects. The spectrum obtained with OSO-8 in September, 1977, is considerably steeper than that observed in pre-1976 balloon flights. These results are consistent with the results obtained by Trumper showing a decrease in the effective temperature of Her X-1 between May, 1976, and September, 1977.

Dennis, B. R.↗

Magnetic fields in flowing magnetotail plasmas and their significance for magnetic reconnection

A statistical study is made of the magnetic field components that occur in the presence of high-velocity flows. Results are reported for a statistical analysis of 324 intervals of intense bulk plasma flows in the plasma sheet of the geomagnetic tail, measured by the Imp 6 spacecraft. A pronounced tendency for southward fields to be associated with tailward flow more often than with earthward flow yields support for the merging concept, though not in its simplest form. Histograms of 15.36-s averages of vector magnetic field measurements during plasma flows reveal no significant changes in the distribution of beta-y between earthward or tailward plasma flow directions.

Caan, M. N.↗

Further isotopic studies of heavy nuclei in the 9/23/78 solar flare

The isotopes considered range from He to Mg (Z from 2 to 12). A more accurate value of the Ne-22/Ne-20 ratio is obtained by extending the energy interval for isotope analysis. A significant difference persists between the Ne-22/Ne-20 ratio in this flare and that for the solar wind. How the sun can apparently emit two distinct isotopic components remains a question. Although relatively little is known about the solar wind isotopic composition, it does not appear that the solar wind isotopes have been altered by a simple mass-dependent fractionation process. Reference is made to models that have been proposed which might produce selective enhancements.

Mewaldt, R. A.↗

A high-resolution study of the isotopes of solar flare nuclei

Individual isotopes of the elements He, C, N, O, Ne, and Mg with energies from 5 to 50 MeV per nucleon have been resolved in energetic flare particles during the September 23, 1978 solar flare event. In addition, an earlier determination of Ne-22/Ne-20 in this flare was improved on by extending the energy interval for isotope analysis. A significant difference between the isotopic composition of solar flare and solar wind neon is found, which is compared to similar evidence from studies of solar energetic particles implanted in lunar and meteoritic samples. Although limited by statistics, the measurements of He, C, N, O, and Mg isotopes are consistent with typical isotopic abundances found in other samples of solar system material. The ensemble of these results is used to test for the possibility of mass-dependent fractionation during solar flare acceleration and propagation.

Mewaldt, R. A.↗

Laser tracking for vertical control

The Global Laser Tracking Network has provided LAGEOS ranging data of high accuracy since the first MERIT campaign in late 1983 and we can now resolve centimeter-level three dimensional positions of participating observatories at monthly intervals. In this analysis, the station height estimates have been considered separately from the horizontal components, and can be determined by the strongest stations with a formal standard error of 2 mm using eight years of continuous observations. The rate of change in the vertical can be resolved to a few mm/year, which is at the expected level of several geophysical effects. In comparing the behavior of the stations to that predicted by recent models of post-glacial rebound, we find no correlation in this very small effect. Particular attention must be applied to data and survey quality control when measuring the vertical component, and the survey observations are critical components of the geodynamic results. Seasonal patterns are observed in the heights of most stations, and the possibility of secular motion at the level of several millimeters per year cannot be excluded. Any such motion must be considered in the interpretation of horizontal inter-site measurements, and can help to identify mechanisms which can cause variations which occur linearly with time, seasonally, or abruptly.

Dunn, Peter↗