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Results for “field reliability data”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

Schultz, Howard↗
DOE OSTI2020

Report on Oak Ridge National Laboratory Testing of Ambient Cure TransPowr E3X®

A key to industry acceptance of a new technology is extensive validation in field trials. The Powerline Conductor Accelerated Test facility (PCAT) at Oak Ridge National Laboratory (ORNL) is specifically designed to evaluate the performance and reliability of novel overhead conductor and conductor instrumentation under field conditions. The facility is set up to capture large amounts of data during testing. General Cable used the ORNL PCAT facility to validate the performance of TransPowr® with Ambient Cure E3X™ Technology—a standard overhead conductor with a high emissivity, low absorptivity ambient cure surface coating. Extensive testing has demonstrated a significant improvement in conductor performance across a wide range of operating temperatures with respect to uncoated conductor of the same type, indicating that E3X Technology can provide a reduction in temperature, a reduction in sag, and an increase in ampacity when applied to the surface of any overhead conductor. This report provides results of that testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1975

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗
DOE OSTI2023

From Images to Dark Matter: End-to-end Inference of Substructure from Hundreds of Strong Gravitational Lenses

Abstract Constraining the distribution of small-scale structure in our universe allows us to probe alternatives to the cold dark matter paradigm. Strong gravitational lensing offers a unique window into small dark matter halos (<10 10 M ⊙ ) because these halos impart a gravitational lensing signal even if they do not host luminous galaxies. We create large data sets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST’s COSMOS field. Using a simulation-based inference pipeline, we train a neural posterior estimator of the subhalo mass function (SHMF) and place constraints on populations of lenses generated using a separate set of galaxy sources. We find that by combining our network with a hierarchical inference framework, we can both reliably infer the SHMF across a variety of configurations and scale efficiently to populations with hundreds of lenses. By conducting precise inference on large and complex simulated data sets, our method lays a foundation for extracting dark matter constraints from the next generation of wide-field optical imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluation of Anodized and Electroplated Radioactive Check Sources for Radiological Monitoring Instruments

Radioactive check sources are often used for source checking calibrated instruments to confirm accurate readings are obtained from radiological monitoring instruments. Because of the importance of check sources and their application, PNNL conducted a study to evaluate the effectiveness and accuracy of active sources produced using different construction methods. Eleven, randomly selected check sources of both anodized (five) and electroplated (six) construction were evaluated, along with their calculated decay curves, to determine how well they withstand consistent, multi-year use in the field. Results show that the anodized and electroplated check sources evaluated hold up well enough to continue their use, regardless of wear and tear sustained over years of use. This report provides the source information, empirical data for the 11 anodized and electroplated check sources and their representative decay curves, and it documents the conclusion that anodized and electroplated check sources are reliable for routine use in the field over multiple years.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2023

Operation and Maintenance of PV Systems: Data Science, Analysis, and Standards

This effort improves the effectiveness and reduce uncertainty in O&M cost through four primary objectives/tasks: 1) institutionalize standards for reliability and availability reporting for large PV power plants; 2) bridge systemic O&M knowledge gaps around important topics affecting O&M; 3) characterize systemic failure modes and patterns and accelerate O&M experiential learning cycles using field data; and 4) establish a baseline understanding of UPVS O&M cost drivers. Key results of this effort include publication of IEC standards, published topical papers on O&M topics, training, and characterize field data for climate- and service-related patterns (additional details below). Integrating these results serves to reduce performance risk and facilitate improvement in the way solar projects are operated and maintained. Results are well received and two publications are among the most successful SETO publications at NREL ("Model of Operation and Maintenance Costs for Photovoltaic Systems with over 40,000 downloads and "Best Practices in Operation and Maintenance of PV Systems, 3rd Ed." with over 90,000 downloads).

14 SOLAR ENERGY↗
NASA NTRS1994

Stellar populations in edge-on galaxies from deep CCD surface photometry, 1: NGC 5907

We present extremely deep charge coupled device (CCD) surface photometry of the edge-on Sc galaxy NGC 5907. Our data reach reliably to a surface brightness of R=27 mag/sq arcsec, some two magnitudes fainter than any previous work. We obtained this improvement using a 2048X2048 CCD with a wide (approximately 24 min) field, which made it possible to sky subtract directly from the galaxy frame, and by taking many dark sky flatfields. Our analysis of these data, using a full 2D model fitting procedure with a detailed error model, confirm the thin disk parameters of van der Kruit & Searle (1981). In particular, we confirm that the galaxy's disk has a radial cutoff and a constant scale height with radius. We find evidence for a stellar warp in this system, which has the same orientation as the H I warp. Our deep data also confirm that NGC 5907 has no thick disk. This suggests that theories of thick disk formation from star formation in the early stages of disk collapse, or by secular heating mechanisms, are unlikely to be correct, because they would predict that every galaxy would have a thick disk. Thick disk formation from the accretion of satellite galaxies is more likely.

Morrison, Heather L.↗
DOE OSTI2020

The cosmological analysis of the SDSS/BOSS data from the Effective Field Theory of Large-Scale Structure

The Effective Field Theory of Large-Scale Structure is a formalism that allows us to predict the clustering of Cosmological Large-Scale Structure in the mildly non-linear regime in an accurate and reliable way. In this paper, after validating our technique against several sets of numerical simulations, we perform the analysis for the cosmological parameters of the DR12 BOSS data. We assume Λ CDM, a fixed value of the baryon/dark-matter ratio, Ω b /Ω c , and of the tilt of the primordial power spectrum, n s , and no significant input from numerical simulations. By using the one-loop power spectrum multipoles, we measure the primordial amplitude of the power spectrum, A s , the abundance of matter, Ω m , and the Hubble parameter, H 0 , {to about 13% , 3.2% and 3.2% respectively, obtaining ln (10 10 A s )=2.72± 0.13 , 0Ω m =0.309± 0.01 , H 0 =68.5± 2.2 km/(s Mpc) at 68% confidence level. If we then add a CMB prior on the sound horizon, the error bar on H 0 is reduced to 1.6% .} These results are a substantial qualitative and quantitative improvement with respect to former analyses, and suggest that the EFTofLSS is a powerful instrument to extract cosmological information from Large-Scale Structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enabling robust offline active learning for machine learning potentials using simple physics-based priors

Abstract Machine learning surrogate models for quantum mechanical simulations have enabled the field to efficiently and accurately study material and molecular systems. Developed models typically rely on a substantial amount of data to make reliable predictions of the potential energy landscape or careful active learning (AL) and uncertainty estimates. When starting with small datasets, convergence of AL approaches is a major outstanding challenge which has limited most demonstrations to online AL. In this work we demonstrate a Δ-machine learning (ML) approach that enables stable convergence in offline AL strategies by avoiding unphysical configurations with initial datasets as little as a single data point. We demonstrate our framework’s capabilities on a structural relaxation, transition state calculation, and molecular dynamics simulation, with the number of first principle calculations being cut down anywhere from 70%–90%. The approach is incorporated and developed alongside AMP torch , an open-source ML potential package, along with interactive Google Colab notebook examples.

Shuaibi, Muhammed↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Transition probabilities and Stark-broadening parameters of neutral and singly ionized lead

Strengths and Stark widths of the prominent visible PbI and PbII lines are measured in emission by means of a gas-driven shock tube. Absolute ionic line strengths for 7s-7p and 7p-7d arrays conform well to quantum-mechanical sum rules and agree with theoretical predictions, but 6d-5f results differ markedly from central-field approximations. Neutral-line strengths agree satisfactorily with available comparison data. Semiempirical theory predicts the widths of PbII lines with characteristic reliability of better than 25%.

Miller, M. H.↗
NASA NTRS1992

Simultaneous observations of coronal bright points in X-ray and radio wavelengths

We present a first explicit comparison of coronal bright points in soft X-ray and radio wavelengths, using the Soft X-ray Telescope aboard the Yohkoh spacecraft and the Very Large Array. About half of the 33 compact sources identified in a 20-cm full-disk map appear as X-ray bright points in the X-ray data. The other half apparently corresponds to unipolar regions with enhanced magnetic fields. Thus, the identification of radio bright points alone cannot reliably serve as a proxy for X-ray bright points. A preliminary analysis reveals that bright points commonly observed at 20 cm and in X-rays have temperatures of (1.4-2.9) x 10 exp 6 K and emission measures of (0.4-2.5) x 10 exp 45/cu cm. The observed brightness temperatures at 20 cm (1-2.5) x 10 exp 5 K can be explained in terms of optically thin free-free emission from a plasma with these parameters.

Nitta, Nariaki↗
NASA NTRS2006

Interiors of Enceladus and Rhea

Measurement method and data set: Gravity field parameters determined by means of range rate measurements over multiple arcs across flyby. Optical imaging not required when reliable a priori estimates of spacecraft state vector are available. Interior of Enceladus: Density of 1605 +/-14 kg/cu m, higher than pre-Cassini estimates, requires a substantial amount of rock to warmer interior to enhance likelihood of differentiation of water from rock-metal. Assume no porosity. Assuming Io s mean density for the rock-metal component, one finds its fractional mass to be 0.52+/-0.06. There is evidence that Enceladus may be differentiated: a) Areas devoid of craters must be geologically young. b) Systems of ridges, fractures, and groove indicate that the surface has been tectonically altered. c) Viscous relaxation of craters has occurred, and d) The plumes near the South pole indicate venting of subsurface volatiles.

gravity fields↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11308-DND

The Lidar Atmospheric Sensing Experiment (LASE) system has operated on the NASA ER-2, P-3, and DC-8 aircraft during the past 16 years and participated in 13 field experiments. This system provides vertical profiles of water vapor mixing ratio and aerosol and cloud backscattering. A brief overview is presented on the upgrade of LASE that included refurbishment of laser diode seeding, control and data system, and zenith receiver system. These developments have enhanced the operational reliability of the system and improved its performance. The LASE system was deployed on the NASA DC-8 aircraft recently for the NASA GRIP (Genesis and Rapid Intensification Processes) field experiment, which was conducted during August and September 2010 from operational bases in Fort Lauderdale, FL and St. Croix, VI. Initial measurements from this field experiment are presented including distributions of water vapor, aerosol, and clouds. Temperature profiles from DC-8 dropsondes and nearby radiosondes are used to derive relative humidity profiles from the LASE water vapor mixing ratio profiles. Comparisons of LASE water vapor mixing ratio profiles with those measured by the new AVAPS-II dropsondes from the NASA DC-8 are also presented.

Susan A Kooi↗
NASA NTRS1994

Field verification of the wind tunnel coefficients

Accurate information about wind action on antennas is required for reliable prediction of antenna pointing errors in windy weather and for the design of an antenna controller with wind disturbance rejection properties. The wind tunnel data obtained 3 years ago using a scaled antenna model serves as an antenna industry standard, frequently used for the first purpose. The accuracy of the wind tunnel data has often been challenged, since they have not yet been tested in a field environment (full-aized antenna, real wind, actual terrain, etc.). The purpose of this investigation was to obtain selected field measurements and compare them with the available wind tunnel data. For this purpose, wind steady-state torques of the DSS-13 antenna were measured, and dimensionless wind torque coefficients were obtained for a variety of yaw and elevation angles. The results showed that the differences between the wind tunnel torque coefficients and the field torque coefficients were less than 10 percent of their values. The wind-gusting action on the antenna was characterized by the power spectra of the antenna encoder and the antenna torques. The spectra showed that wind gusting primarily affects the antenna principal modes.

Gawronski, W. K.↗
DOE OSTI2024

PVDeg: Development of a Streamlined Tool for PV Degradation Modeling

The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.

degradation↗