Search NASA⌕ Search

SEARCH · Search NASA

Results for “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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

TMS 2023 - Methodology and Density of PuCl3-NaCl Mixtures

The development of molten salt reactors and their associated components demands reliable and accurate thermophysical property data for design and validation. A candidate fuel salt, PuCl3-NaCl (36 mol% PuCl3) has been synthesized and studied at the Idaho National Laboratory. This study has determined the density of PuCl3-NaCl at multiple compositions and temperatures, providing data for validation of modeling efforts and making improvements on the buoyancy method for density measurements of actinide-bearing molten salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

IEA PVPS Task 13 Techno-Economic Study of Bifacial Photovoltaic Systems on Single Axis Trackers

The International Energy Agency PVPS Task 13 has assembled an international team of photovoltaic (PV) researchers from government labs, academia, and industry to study the specific application of bifacial PV modules deployed on tracking systems. This configuration is of particular interest as it has been identified as the PV system design with the lowest Levelized Cost of Electricity (LCOE) for over 90% of the world [1]. As such, much research, development, and commercial activity are focused on further optimizing this system design for different regions and markets, including field deployment and advanced modeling activities. Despite these efforts, many challenges remain to overcome with this system design. This conference paper will report on several areas the team is working on as part of this project. The first part of this study focuses on extensive interviews with PV tracker companies (we have identified 35) and customers worldwide to identify emerging technology trends, design diversity, market environments, and the reliability and performance of these systems. We will provide a market summary of technologies such as advanced tracking algorithms, methods for dealing with topography within the PV plant, different system configurations and layouts, backside irradiance optimization from albedo enhancement, and ground sculpting. We will also review dual-use applications of tracked bifacial systems, such as Agrivoltaics and Building-Integrated PV. These interviews are underway now, and we will be able to report our initial findings at the conference. The second part of the study focuses on summarizing performance monitoring and evaluation methods, with particular attention to capacity and acceptance testing for such systems. The third part of the study reviews performance modeling and yield assessment methods for these tracked bifacial PV systems. The final part of the study covers reliability and operations, and maintenance data from these systems.

albedo↗
DOE OSTI2025

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2026

Measurement of the galaxy-velocity power spectrum of DESI tracers with the kinematic Sunyaev-Zeldovich effect using DESI DR2 and ACT DR6

Joint analyses of high-resolution CMB temperature maps with galaxy surveys provide a unique way to reconstruct the radial velocity field of the underlying matter distribution via the kinematic Sunyaev-Zeldovich (kSZ) effect. Using data from the Atacama Cosmology Telescope (ACT) DR6 and the Dark Energy Spectroscopic Instrument (DESI) DR2, we present radial velocity reconstructions for luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasars (QSOs). Leveraging the spectroscopic data, we are able to reliably model the foreground contamination and report a negligible impact on our main observables. We detect the velocity-galaxy cross-correlation at $17.0σ$ for LRGs, and for the first time, at $8.3σ$ for ELGs and $6.8σ$ for QSOs. We further report the first detection of the velocity-velocity correlation using LRGs at $3.1σ$, as well as the highest cumulative detection of the kSZ effect to date at $20.8 σ$. Similarly to previous results, we find a lower amplitude of the kSZ signal compared to our fiducial halo model prediction and electron profile assuming a Battaglia profile. Combining these new observables, we obtain constraints on local-type primordial non-Gaussianity (PNG): $f_{\rm NL}^{\rm loc} = 15.9_{-34.4}^{+34.6}$ at 68% confidence, which represents the tightest constraint to date derived from the velocity field. The measurements presented here already exhibit lower noise on a per-mode basis than the galaxy auto-correlation on the largest scales, $k<0.004~\rm{Mpc^{-1}}$, highlighting the key role these observables will play in the context of future CMB experiments such as the Simons Observatory.

Chaussidon, Edmond [LBL, Berkeley] (ORCID:00000001↗
DOE OSTI2022

Sizing ramping reserve using probabilistic solar forecasts: A data-driven method

Ramping products have been introduced or proposed in several U.S. power markets to mitigate the impact of load and renewable uncertainties on market efficiency and reliability. Current methods often rely on historical data to estimate the requirements of ramping products and fail to take into account the effects of the latest weather conditions and their uncertainties, which could lead to overly conservative or insufficient requirements. This study proposes a k-nearest-neighbor-based method to give weather-informed estimates of ramping needs based on short-term probabilistic solar irradiance forecasts. Forecasts from multiple sites are employed in conjunction with principal component analysis to derive numerical classifiers to characterize system-level weather conditions. In addition, we develop a data-driven method to optimize the model parameters in a rolling-forward manner. By using real-world data from the California Independent System Operator, we design two metrics to evaluate method performance: 1) frequency of shortage and 2) oversupply of ramping product. Our proposed method presents advantages in comparison with the baseline and a set of benchmark methods: without compromising system reliability, it reduces system ramping requirements by up to 25%, therefore improving both system reliability and economics.

14 SOLAR ENERGY↗
DOE OSTI2020

Reliability of emergency and standby diesel generators: Impact on energy resiliency solutions

Emergency diesel generators are the most common form of backup power for critical loads when the grid fails and are most often deployed as stand-alone generators (<2000 kW) tied to individual buildings for hospitals, emergency services, military bases, ports, airports, industries, and commercial facilities. Understanding the finite reliability of emergency diesel generators during continuous operation is critical for energy planners, managers, and end-users. A new analysis of two large non-public emergency diesel generator operational data sets shows that commonly used reliability metrics are inadequate to predict the performance during a grid outage. Additional metrics addressing the likelihood of an emergency diesel generator to be available at the time an outage starts, successfully start and carry load, and constantly run for the duration of the outage are needed to predict the continuous run-time reliability of emergency diesel generators during a grid outage. This is the first analysis of the reliability of modern generators that follow standard maintenance protocols commonly used for backup power and these new metrics are shown to be dependent on the level of emergency diesel generator maintenance with values that can vary by more than an order of magnitude. Even using the new metrics for well-maintained emergency diesel generators, the analysis shows that the single emergency diesel generators configurations are only 80% likely to provide power for the duration of a two-week grid outage.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
NASA NTRS1983

Packet telemetry and packet telecommand - The new generation of spacecraft data handling techniques

Because of rising costs and reduced reliability of spacecraft and ground network hardware and software customization, standardization Packet Telemetry and Packet Telecommand concepts are emerging as viable alternatives. Autonomous packets of data, within each concept, which are created within ground and space application processes through the use of formatting techniques, are switched end-to-end through the space data network to their destination application processes through the use of standard transfer protocols. This process may result in facilitating a high degree of automation and interoperability because of completely mission-independent-designed intermediate data networks. The adoption of an international guideline for future space telemetry formatting of the Packet Telemetry concept, and the advancement of the NASA-ESA Working Group's Packet Telecommand concept to a level of maturity parallel to the of Packet Telemetry are the goals of the Consultative Committee for Space Data Systems. Both the Packet Telemetry and Packet Telecommand concepts are reviewed.

Hooke, A. J.↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
NASA NTRS2012

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and Other Meteorological Measurements

The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements.

Schultz, Christopher J.↗
NASA NTRS2012

A Bayesian Framework for Reliability Analysis of Spacecraft Deployments

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.

Evans, John W.↗
NASA NTRS2011

Experimental and Modeling Studies of the Combustion Characteristics of Conventional and Alternative Jet Fuels. Final Report

The objectives of this project have been to develop a comprehensive set of fundamental data regarding the combustion behavior of jet fuels and appropriately associated model fuels. Based on the fundamental study results, an auxiliary objective was to identify differentiating characteristics of molecular fuel components that can be used to explain different fuel behavior and that may ultimately be used in the planning and design of optimal fuel-production processes. The fuels studied in this project were Fischer-Tropsch (F-T) fuels and biomass-derived jet fuels that meet certain specifications of currently used jet propulsion applications. Prior to this project, there were no systematic experimental flame data available for such fuels. One of the key goals has been to generate such data, and to use this data in developing and verifying effective kinetic models. The models have then been reduced through automated means to enable multidimensional simulation of the combustion characteristics of such fuels in real combustors. Such reliable kinetic models, validated against fundamental data derived from laminar flames using idealized flow models, are key to the development and design of optimal combustors and fuels. The models provide direct information about the relative contribution of different molecular constituents to the fuel performance and can be used to assess both combustion and emissions characteristics.

Meeks, Ellen↗
DOE OSTI2026

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗
DOE OSTI2017

Design Science Methodology Applied to a Chemical Surveillance Tool

Public health surveillance systems gain significant benefits from integrating existing early incident detection systems,supported by closed data sources, with open source data.However, identifying potential alerting incidents relies on finding accurate, reliable sources and presenting the high volume of data in a way that increases analysts work efficiency; a challenge for any system that leverages open source data. In this paper, we present the design concept and the applied design science research methodology of ChemVeillance, a chemical analyst surveillance system.Our work portrays a system design and approach that translates theoretical methodology into practice creating a powerful surveillance system built for specific use cases.Researchers, designers, developers, and related professionals in the health surveillance community can build upon the principles and methodology described here to enhance and broaden current surveillance systems leading to improved situational awareness based on a robust integrated early warning system.

Huang, Zhuanyi↗
DOE OSTI2018

Renewable Energy Data, Analysis, and Decisions: A Guide for Practitioners

High-quality renewable energy resource data and other geographic information system (GIS) data are essential for the transition to a clean energy economy that prioritizes local resources, improves resiliency, creates jobs, and promotes energy independence. These data are crucial for making informed decisions—ranging from policy and investment decisions to reliable power sector planning. Decisions that are data-driven reflect appropriate ambition, maximize cost-effectiveness, and enable successful implementation of renewable energy investments. This guide is intended to support policymakers and planners, as well as technical experts, consultants, and academics in incorporating improved data and analysis into renewable energy decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2017

Kepler Certified False Positive Table

This document describes the Kepler Certied False Positive table hosted at the Exoplanet Archive1, herein referred to as the CFP table. This table is the result of detailed examination by the Kepler False Positive Working Group (FPWG) of declared false positives in the Kepler Object of Interest (KOI) tables (see, for example, Batalha et al. (2012); Burke et al.(2014); Rowe et al. (2015); Mullally et al. (2015); Coughlin et al. (2015b)) at the Exoplanet Archive. A KOI is considered a false positive if it is not due to a planet orbiting the KOI's target star. The CFP table contains all KOIs in the Exoplanet Archive cumulative KOI table. The purpose of the CFP table is to provide a list of certified false positive KOIs. A KOI is certified as a false positive when, in the judgement of the FPWG, there is no plausible planetary interpretation of the observational evidence, which we summarize by saying that the evidence for a false positive is compelling. This certification process involves detailed examination using all available data for each KOI, establishing a high-reliability ground truth set. The CFP table can be used to estimate the reliability of, for example, the KOI tables which are created using only Kepler photometric data, so the disposition of individual KOIs may differ in the KOI and CFP tables. Follow-up observers may find the CFP table useful to avoid observing false positives.

Kepler↗
DOE OSTI2023

Measurement of Beam Energy in the Fermilab&#x27;s Linac taken at the transfer Line

Linac is the first machine in the Accelerator chain at Fermilab where 𝐻− particles are accelerated from 35 keV to 400 MeV and travel to the Booster where they are stripped. of the extra electrons to become protons. The Booster requires stable beam energy at injection. The Linac extraction energy tuning has been performed using two Beam Velocity Monitors (a.k.a Griffin detectors) to maintain stable relative energy between the Booster and the Linac. Our goal is to control the Linac energy parameters using Machine Learning techniques to increase reliability and quality of beam delivered from Linac. The first step is to understand the data from the Linac extraction diagnostics; and develop reliable, accurate methods for energy measurement and control before implementing machine learning. There were two methods of energy measurement implemented, and the results of these are compared. The first method was time of flight measurements using the Phase probes inside B eam Position Monitors (BPM) that provide the beam’s phase of arrival data. The second method used the relation between beam position data from the BPMs and dispersion values from the 400MeV MAD-X model to calculate momentum variation. The results of these two energy measurement methods compare well as the Linac energy is varied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Fast and Accurate Frequency Response Estimation for Large Power System Disturbances Using Second Derivative of Frequency Data

Accurate Frequency Response Estimation (FRE) is critical to reliability risk management of large power system disturbances. This letter proposes a measurement-driven approach for FRE by calculating the second derivative of frequency from synchrophasor data. Compared with conventional methods, the proposed method has major advantages of low computational burden and high accuracy, which makes it appropriate for real-time FRE in bulk power systems. The effectiveness of this method is validated with actual synchrophasor data on 96 confirmed historical power system disturbances in the U.S. eastern interconnection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1974

Data on incident solar energy

Instrumentation for solar irradiance monitoring, and radiation scales are discussed in a survey of incident solar energy data. The absolute accuracy and intrinsic reliability of the values of the solar constant and zero air mass solar spectrum proposed by the Institute of Environmental Sciences as an ASTM standard are evaluated. Extraterrestrial observations are used for deriving solar irradiance data at ground level for widely varying atmospheric parameters, with special reference to air pollution. The effects of diffuse sky radiance and those of varying slopes of the solar energy collecting surface are examined. Average values of solar energy available at different locations in the United States are included.

Thekaekara, M. P.↗