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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Effects of axisymmetric and normal air jet plumes and solid plume on cylindrical afterbody pressure distributions at Mach numbers from 1.65 to 2.50

A wind tunnel investigation of the interference effects of axisymmetric nozzle air plumes, a solid plume, and normal air jet plumes on the afterbody pressure distributions and base pressures of a cylindrical afterbody model was conducted at Mach numbers from 1.65 to 2.50. The axisymmetric nozzles, which varied in exit lip Mach number from 1.7 to 2.7, and the normal air jet nozzle were tested at jet pressure ratios from 1 (jet off) to 615. The tests were conducted at an angle of attack of 0 deg and a Reynolds number per meter of 6.56 million. The results of the investigation show that the solid plume induces greater interference effects than those induced by the axisymmetric nozzle plumes at the selected underexpanded design conditions. A thrust coefficient parameter based on nozzle lip conditons was found to correlate the afterbody disturbance distance and the base pressure between the different axisymmetric nozzles. The normal air jet plume and the solid plume induce afterbody disturbance distances similar to those induced by the axisymmetric air plumes when base pressure is held constant.

Covell, P. F.↗
DOE OSTI2015

Fast model of electron transport for radiographic spectrum simulation

Correctly modeling the continuous photon spectrum of X-ray tubes requires detailed knowledge of the probability distribution of electron properties at the time of X-ray photon creation, in particular electron energy, depth within the target, and direction of movement. Semi-analytical X-ray spectrum models frequently assume a very simplified or even uniform distribution of electron direction. In the case of thick targets and small deviations from normal incidence this is a useful approximation. For thin targets or large deviations from normal incidence the correct distribution of electron directions becomes more important. As calculation speed is an important aspect of semi-analytical models compared to Monte Carlo simulations, fast evaluation of the distribution of electron properties is highly desirable. The approach presented here numerically evaluates the evolution of a discrete probability distribution of electron properties due to single electron scatter interactions within a plane target. This allows capturing the important aspects of the electron distribution while achieving runtimes of a few seconds up to a minute on a standard office PC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Normalizing Flows for Microscopic Many-Body Calculations: An Application to the Nuclear Equation of State

We report that normalizing flows are a class of machine learning models used to construct a complex distribution through a bijective mapping of a simple base distribution. We demonstrate that normalizing flows are particularly well suited as a Monte Carlo integration framework for quantum many-body calculations that require the repeated evaluation of high-dimensional integrals across smoothly varying integrands and integration regions. As an example, we consider the finite-temperature nuclear equation of state. An important advantage of normalizing flows is the ability to build highly expressive models of the target integrand, which we demonstrate enables precise evaluations of the nuclear free energy and its derivatives. Furthermore, we show that a normalizing flow model trained on one target integrand can be used to efficiently calculate related integrals when the temperature, density, or nuclear force is varied. This work will support future efforts to build microscopic equations of state for numerical simulations of supernovae and neutron star mergers that employ state-of-the-art nuclear forces and many-body methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1980

Interaction between a normal shock wave and a turbulent boundary layer at high transonic speeds. I - Pressure distribution

Asymptotic solutions are derived for the pressure distribution in the interaction of a weak normal shock wave with a turbulent boundary layer. The undisturbed boundary layer is characterized by the law of the wall and the law of the wake for compressible flow. In the limiting case considered, for 'high' transonic speeds, the sonic line is very close to the wall. Comparisons with experiment are shown, with corrections included for the effect of longitudinal wall curvature and for the boundary-layer displacement effect in a circular pipe.

Messiter, A. F.↗
NASA NTRS1995

The magnetic field in LYNDS 1457: Multiband photopolarimetry

We have performed multiband photopolarimetry toward stars behind the molecular cloud L1457 (MBM 12). This cloud is the nearest known molecular cloud (65 pc) and thought to be contained within the local 'hot bubble.' The polarization shows a regular structure, indicating that the cloud is threaded by an ordered magnetic field. The wavelength dependence of the polarization seems to indicate that the grains in L1457 have higher indices of refraction than normal for interstellar clouds. However, the wavelength of maximum polarization indicates that their size distribution is close to normal.

Andersson, B-G↗
NASA NTRS1994

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗
DOE OSTI2017

Distributed hierarchical control architecture for integrating smart grid assets during normal and disrupted operations

Disclosed herein are representative embodiments of methods, apparatus, and systems for facilitating operation and control of a resource distribution system (such as a power grid). Among the disclosed embodiments is a distributed hierarchical control architecture (DHCA) that enables smart grid assets to effectively contribute to grid operations in a controllable manner, while helping to ensure system stability and equitably rewarding their contribution. Embodiments of the disclosed architecture can help unify the dispatch of these resources to provide both market-based and balancing services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Investigation on target normal sheath acceleration through measurements of ions energy distribution

An experimental campaign aiming at investigating the ion acceleration mechanisms through laser-matter interaction in femtosecond domain has been carried out at the Intense Laser Irradiation Laboratory facility with a laser intensity of up to 2 × 10{sup 19} W/cm{sup 2}. A Thomson parabola spectrometer was used to obtain the spectra of the ions of the different species accelerated. Here, we show the energy spectra of light-ions and we discuss their dependence on structural characteristics of the target and the role of surface and target bulk in the acceleration process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Performance Comparison of Circular and Spherical Error Probable Estimators

This report compares the performance of three Circular Error Probable (CEP) estimators: the Grubbs-Patnaik estimator, a new, non-iterative, radial-integration estimator, and a median estimator. It also compares the performance of two Spherical Error Probable (SEP) estimators. The performance of each estimator is assessed in terms of bias, uncertainty, robustness, and computational complexity. Robustness is evaluated with respect to outliers, variations in the underlying statistical distribution characterizing munition impact positions, and impact-position measurement errors. The performance assessments indicate the radial-integration and Grubbs-Patnaik estimators perform nearly identically providing the statistical distribution of impact-position coordinates is jointly normal with zero means. In that case, both estimators outperform the median estimator by about 2% relative to the true CEP in terms of estimator uncertainty. The bias performance of the radial-integration and median estimators is close to zero for jointly normal impacts, however, the Grubbs-Patnaik estimator can be significantly biased for jointly normal impacts with non-zero means. When the statistical distribution characterizing impact positions is known, but not jointly normal, the radial-integration estimator is superior. In this case, the median estimator also outperforms the Grubbs-Patnaik estimator but is not quite as good as the radial-integration estimator. If the statistical distribution characterizing impacts is unknown and not jointly normal, or if distribution parameters are difficult or impractical to estimate, or if test data is corrupted with outliers, then the median estimator dramatically outperforms the other estimators, especially in terms of estimation bias. Unexpectedly, measurement noise did not significantly degrade the performance of any of the estimators, except for cases with signal to noise ratios less than five. Although the Grubbs-Patnaik estimator has remained the gold standard for CEP estimation for over half a century, the performance assessments indicate the new, non-iterative, radial-integration estimator and the median estimator offer significant advantages and, in most practical real-world conditions, are superior estimators. These estimators are also useful for SEP estimation whereas the Grubbs-Patnaik estimator does not extend to three dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Quantifying Graph Uncertainty from Communication Data

Graphs are a widely used abstraction for representing a variety of important real-world problems including emulating cyber networks for situational awareness, or studying social networks to understand human interactions or pandemic spread. Communication data is often converted into graphs to help understand social and technical patterns in the underlying communication data. However, prior to this project, little work had been performed analyzing how best to develop graphs from such data. Thus, many critical, national security problems were being performed against graph representations of questionable quality. Herein, we describe our analyses that were precursors to our final statistically grounded technique for creating static graph snapshots from a stream of communication events. The first analyzes the statistical distribution properties of a variety of real-world communication datasets generally fit best by Pareto, log normal, and extreme value distributions. The second derives graph properties that can be estimated given the expected statistical distribution for communication events and the communication interval to be viewed node observability, edge observability, and expected accuracy of node degree. Unfortunately, as that final process is under review for publication, we can't publish it here at this time.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Equivalent Longitudinal Area Distributions of the B-58 and XB-70-1 Airplanes for Use in Wave Drag and Sonic Boom Calculations

A detailed geometric description, in wave drag format, has been developed for the Convair B-58 and North American XB-70-1 delta wing airplanes. These descriptions have been placed on electronic files, the contents of which are described in this paper They are intended for use in wave drag and sonic boom calculations. Included in the electronic file and in the present paper are photographs and 3-view drawings of the two airplanes, tabulated geometric descriptions of each vehicle and its components, and comparisons of the electronic file outputs with existing data. The comparisons include a pictorial of the two airplanes based on the present geometric descriptions, and cross-sectional area distributions for both the normal Mach cuts and oblique Mach cuts above and below the vehicles. Good correlation exists between the area distributions generated in the late 1950s and 1960s and the present files. The availability of these electronic files facilitates further validation of sonic boom prediction codes through the use of two existing data bases on these airplanes, which were acquired in the 1960s and have not been fully exploited.

Tinetti, Ana F.↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗
NASA NTRS2021

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗
DOE OSTI2017

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE SIGNATURE OF THE WARM-HOT INTERGALACTIC MEDIUM IN WMAP AND THE FORTHCOMING PLANCK DATA

We compute the cross-correlation between the Warm-Hot Intergalactic Medium and maps of cosmic microwave background temperature anisotropies using a log-normal probability density function to describe the weakly nonlinear matter density field. We search for this contribution in the data measured by the Wilkinson Microwave Anisotropy Probe. We use a template of projected matter density reconstructed from the Two-Micron All-Sky Redshift Survey as a tracer of the electron distribution. The spatial distribution of filaments is modeled using the recently developed Augmented Lagrangian Perturbation Theory. On the scales considered here, the reconstructed density field is very well described by the assumed log-normal distribution function. We predict that the cross-correlation will have an amplitude of 0.03-0.3 {mu}K. The measured value is close to 1.5 {mu}K, compatible with random alignments between structure in the template and in the temperature anisotropy data. Using the W1 Differencing Assembly to remove this systematic gives a residual correlation dominated by Galactic foregrounds. Planck could detect the Warm-Hot Medium if it is well traced by the density field reconstructed from galaxy surveys. The 217 GHz channel will allow to eliminate spurious contributions and its large frequency coverage can show the sign change from the Rayleigh-Jeans to the Wien part of the spectrum, characteristic of the thermal Sunyaev-Zel'dovich effect.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Far-infrared /FIR/ optical black bidirectional reflectance distribution function /BRDF/

A nonspecular reflectometer and its operation at far-infrared wavelengths are described. Large differences in nonspecular reflectance were found to exist between different optically black coatings. Normal incidence bidirectional reflectance distribution function /BRDF) measurements at wavelengths between 12 and 316 microns of three black coatings show that their mean BRDFs increase with wavelength. The specularity of two of these coatings also showed a strong wavelength dependence, while the specularity of one coating seemed independent of wavelength. The BRDF of one coating depended on the angle of incidence at 12 and 38 microns, but not at 316 microns. Beyond 200 microns, it was found necessary to correct the measurements for the beam spread of the instrument.

Smith, S. M.↗