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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dark energy survey: Modeling strategy for multiprobe cluster cosmology and validation for the full six-year dataset

Here, we introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3×2 pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (i) identification of modeling and parametrization choices and impact studies using simulated analyses with each possible model misspecification and (ii) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3×2 pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy–galaxy lensing and cosmic shear two-point statistics) and the CL+3×2 pt+BAO+SN (combination of CL+3×2 pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Statistical Strength Analysis of Dissimilar AA2024-T6 and AA6061-T6 Friction Stir Welded Joints

Friction stir welding has been emerged as one of the most reliable processes for joining aerospace-grade aluminum alloys. However, limited studies have been focused so far on the reliability of these joint types. In this study, the effect of welding parameters (traverse and rotation speeds) on the fracture strength of dissimilar AA2024-T6 and AA6061-T6 friction stir welded joints was statistically analyzed by the Weibull approach. Based on the results, the Weibull approach was found to be much more accurate than widely used standard deviation for evaluating the scatter of the fracture strength data. The improper selection of the process parameters not only decreased the average fracture strengths of the joints, but also scattered them around the mean value, and increased the failure probability under the same applied tension. According to the microscopic and macroscopic examinations and microhardness measurements, although the microstructural inhomogeneities caused by the improper setting of the welding parameters negatively affected the joints hardness and fracture strength, the welding defects were likely to be the most responsible factor affecting the fracture strength and its reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment

This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics. As an example, results are shown for 3.2 fb –1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. Furthermore, no significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1972

Assessment of and standardization for quantitative nondestructive test

Present capabilities and limitations of nondestructive testing (NDT) as applied to aerospace structures during design, development, production, and operational phases are assessed. It will help determine what useful structural quantitative and qualitative data may be provided from raw materials to vehicle refurbishment. This assessment considers metal alloys systems and bonded composites presently applied in active NASA programs or strong contenders for future use. Quantitative and qualitative data has been summarized from recent literature, and in-house information, and presented along with a description of those structures or standards where the information was obtained. Examples, in tabular form, of NDT technique capabilities and limitations have been provided. NDT techniques discussed and assessed were radiography, ultrasonics, penetrants, thermal, acoustic, and electromagnetic. Quantitative data is sparse; therefore, obtaining statistically reliable flaw detection data must be strongly emphasized. The new requirements for reusable space vehicles have resulted in highly efficient design concepts operating in severe environments. This increases the need for quantitative NDT evaluation of selected structural components, the end item structure, and during refurbishment operations.

Neuschaefer, R. W.↗
NASA NTRS1984

An experimental evaluation of the Sternberg task as a workload metric for helicopter Flight Handling Qualities (FHQ) research

The objective was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopters engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗
NASA NTRS1984

The Sternberg Task as a Workload Metric in Flight Handling Qualities Research

The objective of this research was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopers engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to a workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗
NASA NTRS1986

IRAS observations of comets

The moderate spatial resolution and high sensitivity of the Infrared Astronomical Satellite (IRAS), which surveyed the celestial sphere during 1983 at wavelengths of 12, 25, 60, and 100 microns, were particularly well suited to detecting extended thermal emission from cometary dust. Sources with infrared color temperatures characteristic of solar system bodies, and at the ephemerides position of known comets were selected for analysis by the IRAS Asteroid Data Analysis System (ADAS). The data base is now available for use by researchers. This paper describes the development of the data base, details its entries, and presents a statistical analysis of its contents. The IRAS survey contains multiple observations of many periodic comets. A brief description and analysis is given of the observed infrared and derived physical properties for several comets of special interest.

Walker, R. G.↗
NASA NTRS1993

Anthropometric survey of the astronaut applicants and astronauts from 1985 to 1991

The Anthropometry and Biomechanics Laboratory at the Johnson Space Center has been collecting anthropometric data from astronaut applicants since 1977. These anthropometric measurements had been taken from 473 applicants. Based on the position they applied for, these applicants were classified as either mission specialists, payload specialists, pilots, or observers. The main objective was to document the variations among these applicants and tabulate the percentile data for each anthropometric dimension. The percentile and the descriptive statistics data were tabulated and graphed for the whole astronaut candidate population; for the male and female groups; for each subject classification such as pilot, mission specialist, and payload specialist; and finally, for those who were selected as astronauts.

Rajulu, Sudhakar L.↗
NASA NTRS1991

Probabilistic micromechanics for metal matrix composites

A probabilistic micromechanics-based nonlinear analysis procedure is developed to predict and quantify the variability in the properties of high temperature metal matrix composites. Monte Carlo simulation is used to model the probabilistic distributions of the constituent level properties including fiber, matrix, and interphase properties, volume and void ratios, strengths, fiber misalignment, and nonlinear empirical parameters. The procedure predicts the resultant ply properties and quantifies their statistical scatter. Graphite copper and Silicon Carbide Titanlum Aluminide (SCS-6 TI15) unidirectional plies are considered to demonstrate the predictive capabilities. The procedure is believed to have a high potential for use in material characterization and selection to precede and assist in experimental studies of new high temperature metal matrix composites.

Engelstad, S. P.↗
NASA NTRS1994

Gross spectral differences between bright and dim gamma-ray bursts

We find that dim gamma-ray bursts (GRBs) are softer than bright GRBs, as indicated on average by data from the Burst and Transient Source Experiment (BATSE) on board the Compton Gamma Ray Observatory (CGRO). We show that this correlation is statistically significant with respect to variations due to random differences between GRBs. This effect is discernible using a variety of methods and data sets, including public domain data. We analyze several types of systematic errors and selection effects in the BATSE data and conclude that the observed effect is not dominated by any of them. We therefore assert that this dim/soft effect is a real property of GRBs. It is possible that this correlation is a consequence of the time dilation and that the burst sources are located at cosmological distances.

Nemiroff, R. J.↗
NASA NTRS1994

The Experimental Cloud Lidar Pilot Study (ECLIPS) for cloud-radiation research

The Experimental Cloud Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on cloud-base height, extinction, optical depth, cloud brokenness, and surface fluxes. Two observational phases have taken place, in October-December 1989 and April-July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community. This article describes the scale of the study in terms of its international involvement and in the range of data being recorded. Lidar observations of cloud height and backscatter coefficient have been taken from a number of ground-based stations spread around the globe. Solar shortwave and infrared longwave fluxes and infrared beam radiance have been measured at the surface wherever possible. The observations have been tailored to occur around the overpass times of the NOAA weather satellites. This article describes in some detail the various retrieval methods used to obtain results on cloud-base height, extinction coefficient, and infrared emittance, paying particular attention to the uncertainties involved.

Platt, C. M.↗
NASA NTRS1996

Global and Local Distortion Inference During Embedded Zerotree Wavelet Decompression

This paper presents algorithms for inferring global and spatially local estimates of the squared-error distortion measures for the Embedded Zerotree Wavelet (EZW) image compression algorithm. All distortion estimates are obtained at the decoder without significantly compromising EZW's rate-distortion performance. Two methods are given for propagating distortion estimates from the wavelet domain to the spatial domain, thus giving individual estimates of distortion for each pixel of the decompressed image. These local distortion estimates seem to provide only slight improvement in the statistical characterization of EZW compression error relative to the global measure, unless actual squared errors are propagated. However, they provide qualitative information about the asymptotic nature of the error that may be helpful in wavelet filter selection for low bit rate applications.

Huber, A. Kris↗
NASA NTRS1998

An Investigation of Candidate Sensor-Observable Wake Vortex Strength Parameters for the NASA Aircraft Vortex Spacing System (AVOSS)

The counter-rotating pair of wake vortices shed by flying aircraft can pose a threat to ensuing aircraft, particularly on landing approach. To allow adequate time for the vortices to disperse/decay, landing aircraft are required to maintain certain fixed separation distances. The Aircraft Vortex Spacing System (AVOSS), under development at NASA, is designed to prescribe safe aircraft landing approach separation distances appropriate to the ambient weather conditions. A key component of the AVOSS is a ground sensor, to ensure, safety by making wake observations to verify predicted behavior. This task requires knowledge of a flowfield strength metric which gauges the severity of disturbance an encountering aircraft could potentially experience. Several proposed strength metric concepts are defined and evaluated for various combinations of metric parameters and sensor line-of-sight elevation angles. Representative populations of generating and following aircraft types are selected, and their associated wake flowfields are modeled using various wake geometry definitions. Strength metric candidates are then rated and compared based on the correspondence of their computed values to associated aircraft response values, using basic statistical analyses.

Tatnall, Chistopher R.↗
NASA NTRS2003

Multi-Temperature Emission and Abundances in the Hot Gaseous Halo

We present the results of XMM-Newton observations of NGC 507, a dominant elliptical galaxy in a small group of galaxies. After carefully considering various systematic effects on abundance measurements, we report 'super-solar' metal abundances (both Fe and a-elements) present in the hot ISM: ZFe = 2-3 times solar with an observational limit of as high as 4 times solar inside the D25 ellipse of NGC 507. This is the highest ZFe reported so far, and fully consistent with those expected by the stellar evolution models where heavy elements are enriched by both type II and Ia supernovae ejecta. No unusual constraint either on the SNe rate or IMF is required. Among various factors affecting the accurate abundance measurement, we find that selecting a proper emission model is most important. As opposed to the X-ray spectral data with limited s/n and poor spatial/spectral resolution obtained in the previous missions, the spatially resolved XMM spectra provide enough statistics to untie the model-Z degeneracy and statistically require at least 3 emission components in each concentric shell (2 thermal components representing a finite range of kT in the hot ISM + 1 hard LMXB component). We show that a simpler model (such as a two-component model) produce a much lower best-fit ZFe. The abundances of a-elements (most accurately determined by Si) is also found to be super-solar and its radio to Fe is close to the solar ratio, suggesting a considerably contribution of heavy elements from Type Ia SNe. We estimate approx. 70% of MFe in the hot ISM originate from Type Ia.

Kim, Dong-Woo↗
NASA NTRS2014

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

weather research and forecasting ===== The NASA Short‐term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2‐km northwestern‐hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra‐tropical cyclones with intense non‐convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified‐WRF (NU‐WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real‐time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU‐WRF, EMS, LIS, and GSI.

Case, Jonathan L.↗
NASA NTRS2019

Evaluation Analysis of NASA SMAP L3 and L4 and SPoRT-LIS Soil Moisture Data in the United States

Soil moisture has a critical role in the development, frequency and persistence of climatic and hydrologic extremes such as drought, heat wave and flooding events. In situ soil moisture data are uneven and sparse in time and space. This highlights the need to utilize other soil moisture sources to fill this spatiotemporal gap. The goal of this study is to validate one satellite-based and two model-based soil moisture datasets with in situ data across the United States. Soil moisture information from the Soil Moisture Active Passive (SMAP) enhanced level 3 (L3) (SMAP L3) and modeled level 4 (L4) (SMAP L4) data at 9-km resolution and Short-term Prediction Research and Transition-Land Information System (SPoRT-LIS) modeled at 3-km resolution were selected for evaluation. SPoRT-LIS is a near real-time, high resolution operational land analysis data. Ground-based data were obtained from the North American Soil Moisture Database (NASMD) for 362 stations. Seven statistical indicators including anomaly, Spearman, and Pearson correlation coefficients, the systematic error (Bias), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and normalized standard deviation (SDV) were used to evaluate the satellite- and model-derived soil moisture data. In addition, the triple collocation (TC) error model was used to measure the error among SMAP L4, SPoRT-LIS and ground-based data. This study assesses which satellite or modeled dataset is most appropriate for specific times and locations to use as a surrogate for in situ observations. Temporal and spatial analysis demonstrated that, overall, SMAP L4 performed better than SMAP L3 and SPoRT-LIS. Strong agreement was observed between SMAP L4 and in situ observations (ρ = 0.53, Bias = −0.006) in all seasons and most regions with various land covers, especially in winter and in the central regions of the United States. For croplands, SMAP L4 presented the best agreement with in situ data, analyzing all period (ρ = 0.60) and non-winter period (ρ = 0.61) separately.

Tavakol, Ameneh↗
NASA NTRS2020

Comparison of Extreme Value Distributions for Electrostatic Discharge Magnitudes in Spacecraft Charging Tests

Electrostatic Discharge (ESD) induced by the accumulation of charge in the space environment is known to cause spacecraft anomalies and failures. While it is critical to estimate the worst-case expected ESD, sensitive radar instruments can be impacted by high rates of occurrence of very small ESD. To estimate the correct extreme behavior, it is important to select the correct extreme value distribution for extrapolation of test results limited in time and sensitivity. Quantile-quantile (Q-Q) analysis is used to compare electron beam-induced ESD test data to several statistical distributions used in the published literature. The best-fit distribution is shown to vary from between tests on different materials; however, it is clear that power law distributions are not good approximations for low amplitude events. Q-Q analysis is a convenient graphical method for evaluating multiple theoretical extreme-value distributions simultaneously.

Kim, Wousik↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗