Search NASA⌕ Search

SEARCH · Search NASA

Results for “data quality”

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 181 records · Page 10

Surface Energy Balance System (SEBS) Instrument Handbook

A surface energy balance system (SEBS) has been installed collocated with each deployed eddy correlation flux measurement system (ECOR) after 2010 at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Southern Great Plains (SGP) observatory, North Slope of Alaska (NSA) observatory, Eastern North Atlantic (ENA) observatory, and the first, second, and third ARM Mobile Facilities (AMF1, AMF2, AMF3). A SEBS was also deployed at the Tropical Western Pacific (TWP) site, before it was decommissioned. Data from these sites, including the retired TWP, are available in the ARM Data Center. The SEBS consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil temperature, soil moisture, and soil heat flow measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

54 ENVIRONMENTAL SCIENCES↗

PV Operations Software Transparency: A PVMAC Industry Snapshot

The rapid growth of photovoltaic (PV) deployment has increased reliance on software platforms for monitoring, workflow automation, diagnostics, and performance analytics. As these tools play a central role in asset management and operations and maintenance (O&M), greater transparency in methodologies, data handling, and validation practices benefits the broader PV ecosystem. To better understand current practices and identify opportunities for improved clarity and interoperability, 24 software providers contributed detailed responses through the PV O&M Analytics Collaborative (PVMAC) initiative, the first structured questionnaire of its kind in the industry, covering onboarding, interoperability, data quality, diagnostics, AI/ML, and other operational categories. These providers represent over 1.1 TW of solar assets under management. The analysis shows broad adoption of digital twins, AI/ML, and API integrations, but also highlights challenges in onboarding processes, inconsistent definitions and methodologies, variability in key performance indicator (KPI) calculations, and limited independent validation. Greater standardization, clearer documentation, and stronger validation frameworks could improve transparency, comparability, and trust across PV operations software platforms.

14 SOLAR ENERGY↗

Effect of Surrogate Fission Products on Thermal Conductivity and Viscosity of NaCl-UCl 3

Thermophysical properties of salt systems relevant to molten salt reactors (MSRs) are experimentally measured in support of the US Department of Energy Office of Nuclear Energy (DOE-NE) MSR campaign within the Advanced Reactor Technology (ART) Program. These property measurements also support the development of the thermophysical arm of the Molten Salt Database (MSD) within DOE-NE’s Nu clear Energy Advanced Modeling and Simulation (NEAMS) Program. Several US Department of Energy (DOE) laboratories, including Oak Ridge National Laboratory (ORNL), have been capitalizing on modern methodologies and sample characterization techniques to conduct thermophysical property measurements to support these programs and to provide MSR developers and modelers with more recent and higher-quality data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ARM Radiosondes for SNPP/JPSS Validation Field Campaign Report

This field campaign extension has been a coordinated effort involving the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility, the University of Wisconsin at Madison, and the Joint Polar Satellite System (JPSS) project to validate NOAA Unique Combined Atmospheric Processing System (NUCAPS) temperature and moisture sounding products from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments on board the NOAA-20 and NOAA-21 satellite platforms. In this arrangement, funding for radiosondes and balloons was provided by the JPSS project to ARM. These radiosondes were launched coincident with NOAA-20 and NOAA-21 satellite overpasses at the ARM field sites at Eastern North Atlantic (ENA), North Slope Alaska (NSA), and Southern Great Plains (SGP). Combined with other ARM data, an assessment of the radiosonde data quality was performed and post-processing corrections applied. The dedicated radiosondes were integrated into the NOAA Products Validation System (NPROVS+), which collocated the radiosondes with satellite products (NOAA, National Aeronautics and Space Administration [NASA], European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], Geostationary Operational Environmental Satellite [GOES], Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) and numerical weather prediction (NWP) forecasts for use in product assessment and algorithm development. This work is a part of the NOAA-20 and NOAA-21 satellite retrieval validation efforts and provides critical accuracy assessments of the temperature and water vapor soundings.

54 ENVIRONMENTAL SCIENCES↗

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗

LSST Scheduler & Progress Monitoring

The NSF-DOE Vera C. Rubin Observatory scheduling team is providing a set of tools for monitoring the scheduler and progress on the Legacy Survey of Space and Time (LSST). These slides provide an overview of available pages and assorted figures on them: the night summary provides an overview of a completed night of observing, including maps of exposures and plots of data quality metrics; the pre-night briefing, an analysis of a simulation of an upcoming night; and a handful of figures that provide information on long-term progress toward LSST survey goals.

H.Neilsen, Eric, Jr. [Fermilab] (ORCID:00000002735↗

AI-Optimized Polarization at Jefferson Lab

The AI-Optimized Polarization project seeks to develop experimental control applications for polarized targets and beams at Jefferson Lab using AI/ML. This paper will focus on two ongoing efforts involving a cryogenic polarized target and a linearly-polarized photon beam. Firstly, cryogenic targets, such as those used in Halls B and C (and approved for Hall D), are complex systems that are sensitive to a number of factors, including the temperature, beam currents, and the microwave and NMR apparatus. Secondly, the Hall D photon beam polarization depends on the optimal orientation of a diamond radiator, which produces coherent bremsstrahlung radiation from the electron beam incident upon it. Manual operation of both systems is tedious and error prone; implementing well-designed, interpretable control systems that incorporate AI is expected to lead to improved real-time polarization. AI optimization of nuclear physics experiments will lead, not just to cost-savings, but also to more efficient and higher-quality data, and this project will help to lay the foundation for future autonomous experiments.

Moran, Patrick [College of William and Mary, Willi↗

Characterization of Gramicidin A in Triblock and Diblock Polymersomes and Hybrid Vesicles via Continuous Wave Electron Paramagnetic Resonance Spectroscopy

Studying membrane proteins in a native environment is crucial to understanding their structural and/or functional studies. Often, widely accepted mimetic systems have limitations that prevent the study of some membrane proteins. Micelles, bicelles, and liposomes are common biomimetic systems but have problems with membrane compatibility, limited lipid composition, and heterogeneity. To overcome these limitations, polymersomes and hybrid vesicles have become popular alternatives. Polymersomes form from amphiphilic triblock or diblock copolymers and are considered more robust than liposomes. Hybrid vesicles are a combination of lipids and block copolymers that form vesicles composed of a mixture of the two. These hybrid vesicles are appealing because they have the native lipid environment of bilayers but also the stability and customizability of polymersomes. Gramicidin A was incorporated into these polymersomes and characterized using continuous wave electron paramagnetic resonance (CW-EPR) and transmission electron microscopy (TEM). EPR spectroscopy is a powerful biophysical technique used to study the structure and dynamic properties of membrane proteins in their native environment. Spectroscopic studies of gramicidin A have been limited to liposomes; in this study, the membrane peptide is studied in both polymersomes and hybrid vesicles using CW-EPR spectroscopy. Lineshape analysis of spin-labeled gramicidin A revealed linewidth broadening, suggesting that the thicker polymersome membranes restrict the motion of the spin label more when compared to liposome membranes. Statement of Significance: Understanding membrane proteins’ structures and functions is critical in the study of many diseases. In order to study them in a native environment, membrane mimetics must be developed that can be suitable for obtaining superior biophysical data quality to characterize structural dynamics while maintaining their native functions and structures. Many currently widely accepted methods have limitations, such as a loss of native structure and function, heterogeneous vesicle formation, restricted lipid types for the vesicle formation for many proteins, and experimental artifacts, which leaves rooms for the development of new biomembrane mimetics. The triblock and diblock polymersomes and hybrid versicles utilized in this study may overcome these limitations and provide the stability and customizability of polymersomes, keeping the biocompatibility and functionality of liposomes for EPR studies of membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Powering the Woods Hole X-Spar Buoy with Ocean Wave Energy—A Control Co-Design Feasibility Study

Despite its success in measuring air–sea exchange, the Woods Hole Oceanographic Institution’s (WHOI) X-Spar Buoy faces operational limitations due to energy constraints, motivating the integration of an energy harvesting apparatus to improve its deployment duration and capabilities. This work explores the feasibility of an augmented, self-powered system in two parts. Part 1 presents the collaborative design between X-Spar developers and wave energy researchers translating user needs into specific functional requirements. Based on requirements like desired power levels, deployability, survivability, and minimal interference with environmental data collection, unsuitable concepts are pre-eliminated from further feasibility study consideration. In part 2, we focus on one of the promising concepts: an internal rigid body wave energy converter. We apply control co-design methods to consider commercial of the shelf hardware components in the dynamic models and investigate the concept’s power conversion capabilities using linear 2-port wave-to-wire models with concurrently optimized control algorithms that are distinct for every considered hardware configuration. During this feasibility study we utilize two different control algorithms, the numerically optimal (but acausal) benchmark and the optimized damping feedback. We assess the sensitivity of average power to variations in drive-train friction, a parameter with high uncertainty, and analyze stroke limitations to ensure operational constraints are met. Our results indicate that a well-designed power take-off (PTO) system could significantly extend the WEC-Spar’s mission by providing additional electrical power without compromising data quality.

autonomous systems↗

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas

Abstract. Drought has long posed an existential threat to society. Engineering and technological advancements have enabled the development of complex, interconnected water supply systems that buffer societies from the impacts of drought, enabling growth and prosperity. However, increasing water demand from population growth and economic development, combined with more extreme and prolonged droughts due to climate change, poses significant challenges for governments in the 21st century. Improved understanding of the cascading multisectoral impacts and adaptive responses resulting from extreme drought can aid in adaptive planning and highlight key processes in modeling drought impacts. The record drought spanning 2008 to 2015 in the Colorado Basin in the state of Texas, United States, serves as an outstanding illustration to assess multisectoral impacts and responses to severe, multi-year drought. The basin faces similar water security challenges to those across the western US, such as groundwater depletion and sustainability, resource competition between agriculture and growing urban populations, limited options for additional reservoir expansion, and the heightened risk of more severe and frequent droughts due to climate change. By analyzing rich, high-quality data sourced from nine different local, state, and federal sources, we demonstrate that characterizing regional multisector dynamics is crucial to predicting and understanding future vulnerability and possible approaches to reduce impacts to human and natural systems in the face of extreme drought conditions. This review reveals that, despite the severe hydrometeorological conditions of the drought, the region's advanced economy and existing water infrastructure effectively mitigated economic and societal impacts.

54 ENVIRONMENTAL SCIENCES↗

On optimizing the sensor spacing for pressure measurements on wind turbine airfoils

This research article presents a robust approach to optimizing the layout of pressure sensors around an airfoil. A genetic algorithm and a sequential quadratic programming algorithm are employed to derive a sensor layout best suited to represent the expected pressure distribution and, thus, the lift force. The fact that both optimization routines converge to almost identical sensor layouts suggests that an optimum exists and is reached. By comparing against a cosine-spaced sensor layout, it is demonstrated that the underlying pressure distribution can be captured more accurately with the presented layout optimization approach. Conversely, a 39 %–55 % reduction in the number of sensors compared to cosine spacing is achievable without loss in lift prediction accuracy. Given these benefits, an optimized sensor layout improves the data quality, reduces unnecessary equipment and saves cost in experimental setups. While the optimization routine is demonstrated based on the generic example of the IEA 15 MW reference wind turbine, it is suitable for a wide range of applications requiring pressure measurements around airfoils.

17 WIND ENERGY↗

Exploring the Intersection of AI and Visualization in the Nuclear Industry

This presentation explores the impact of AI and visualization in advancing the nuclear industry by improving safety, operational efficiency, and decision-making processes. It highlights key applications such as real-time monitoring, predictive maintenance, and immersive training, while addressing challenges like data quality, regulatory hurdles, and the need for explainable AI. Additionally, the presentation outlines future directions, emphasizing the potential of AI-driven reactor design, advanced simulation tools, and ethical considerations to drive innovation and sustainability in nuclear operations.

99 GENERAL AND MISCELLANEOUS↗

High temperature electrical property measurements of ceramics

Emerging applications in energy and aerospace systems require high quality data on the high temperature electrical properties of ceramics, particularly oxides, to guide material selection, design, and modeling. This presentation demonstrates the functionality of a specially designed sample fixture that enables electrical measurements to be conducted up to temperatures as high as 1600°C. Utilizing the mismatch in the coefficient of thermal expansion between two materials, a purely mechanical method for establishing electrical contact in the van der Pauw geometry is used to measure the bulk resistivity of ceramic materials. Measurements conducted on a number of common high temperature materials will be presented, including 20 mol % Gd-doped cerium oxide. Measurements are performed using multiple techniques and compared to literature values finding excellent agreement. The approach described in this work enables the van der Pauw method to be applied to many ceramic materials over a wide range of temperatures and environments.

Cann, David P.↗

FGMS-poster

Idaho National Laboratory (INL) performs post irradiation examination (PIE) of tri-structural isotropic (TRISO)-coated particle fuel to help qualify it for high temperature gas cooled reactors. TRISO fuel compacts are re-irradiated in the Neutron Radiography Reactor (NRAD) to generate the short lived fission products needed for fission product release testing. The Fuel Accident Condition Simulator (FACS) furnace and newly added Screen Neutron Irradiated Fuel for Failure (SNIFF) furnace heat the compacts in helium to temperatures of up to 2,000°C, prompting fission product release—predominantly gaseous xenon and krypton isotopes and condensable products such as cesium—from failed particles. These released isotopes are transported to a fission gas monitoring system (FGMS 1 or FGMS 3), where they accumulate in cryogenic cold traps and are quantified using high-purity germanium (HPGe) detectors. The addition of SNIFF and FGMS 3 increases throughput by enabling simultaneous testing of multiple compacts. Furthermore, automated INL developed software provides continuous, near-real time monitoring of fission product inventories and manages the liquid nitrogen cooling of the traps. These system enhancements improve the efficiency, data quality, and testing capacity of TRISO fuel performance evaluations.

07 - ISOTOPES AND RADIATION SOURCES↗

Strong Lensing Cosmology with Population-level Calibrated Neural Ratio Estimation

Strong gravitational lensing contains key information about cosmic acceleration. Modern and next-generation galaxy imaging surveys are expected to provide high-quality data on $\mathcal{O}(10^5)$ galaxy-galaxy lensing systems. The plethora and complexity of the data are likely to present computational challenges for parameter inference methods for fitting high-dimensional likelihoods, which are often analytically intractable. Neural Ratio Estimation (NRE) efficiently computes individual likelihood ratios that can be combined into population-level posteriors. We use simulations to study the capacity of NRE to jointly predict the dark energy equation-of-state parameter $w$ and the total matter density $Ω_{m}$ from lensing images and companion spectroscopic information. We also introduce a post hoc posterior coverage calibration procedure that mitigates the model overconfidence that is typically found in neural density estimation applications. Our experiments show that the errors on both parameters decrease with increasing inference population sizes. In particular, for 100 lenses in a standard $Λ$CDM Universe, our calibrated NRE model achieves median fractional uncertainty of $22.8\%$ in $w$ and $2.9\%$ in $Ω_{m}$. This proof of concept demonstrates a potentially scalable approach for efficient cosmological parameter inference with large populations of galaxy-scale lenses observed in future surveys.

Jarugula, Sreevani [Fermilab] (ORCID:0000000253867↗

Cleaned 5-Minute Resolution Air Quality and Meteorological Data from Nine TCEQ CAMS Sites in Houston, Texas (Nov 2021 – Oct 2022)

These data encompass 5-minute air monitoring and meteorological observations collected in the greater Houston, Texas metropolitan region, at nine (9) Continuous Ambient Monitoring Stations (CAMS) operated by the Texas Commission on Environmental Quality (TCEQ) between November 1, 2021 and October 31, 2022. The CAMS sites (CAMS 1, 8, 35, 45, 148, 403, 405, 410, and 1052) were chosen because their instrumentation includes measurements of PM2.5. These sites also provide continuous multi-parameter air-quality and meteorological measurements. Particulate matter (PM2.5, PM10) was sampled along with several trace gases, including ozone (O3), nitrogen oxides (NO, NO2, NOx), sulfur dioxide (SO2), and carbon monoxide (CO). The data set also contains standard surface meteorological parameters (temperature, humidity, pressure, wind speed, and wind direction). Several sites also include AutoGC-based measurements of volatile organic compounds (VOCs). Air monitoring instruments deployed at the selected sites comprise the following systems: BAM-1020 or TEOM (PM2.5), Thermo Scientific TEI 49i (O3), TEI 42i (NOx), and AutoGCs (VOCs). This data set is similar to the data included within the houairq5mX1.00 datastream, except for a few additional quality control steps. A systematic data cleaning and verification process was performed on the data set to ensure its quality and preparation for analysis. Removal of non-numeric status flags (e.g., [LIM], [QAS], [SPZ], [CAL], [PMA], [AQI], [SPN], [MAL]) was accomplished by employing rule-based string parsing to extract valid numerical values. Missing entries were set to -9999; however, invalid or anomalous values (e.g., 99999) were retained as originally reported by the TCEQ to preserve data provenance. The time sequence was verified for completeness, removal of duplicates, and uniformity at 5-minute intervals. Column labeling was standardized, and corresponding values were assessed for physical plausibility. All timestamps in the data set were reported in Coordinated Universal Time (UTC) as provided by the TCEQ. Further, the latitude and longitude coordinates were added for each CAMS site. A subset of the data (June 1–September 30, 2022) has been used in the following publication: Subba et al. 2025. “Implications of sea breeze circulations on boundary layer aerosols in the southern coastal Texas region.” EGUsphere 2025: 1–49, https://doi.org/10.5194/egusphere-2025-2659.

latitude↗

CHESS 2025: Post-survey report for 2025 NEON AOP Assignable Asset collection of East River and Washington Gulch, Almont and Upper Taylor watersheds at Crested Butte, CO

This report contains details of the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) Research Support Services (RSS) Assignable Asset (AA) flights of the East River, Almont and Upper Taylor watersheds near Crested Butte, CO, June–July 2025. The Rocky Mountain Biological Laboratory (RMBL) contracted the NEON AOP AA flights to observe watersheds of interest near Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The report includes a summary of the acquired flight lines over the planned survey areas, results of calibration flights, and results of the acquired data. The report details how the AOP has met the contracted delivery requirements in terms of the data delivered, quality of the data, and describes issues that resulted in data degradation or data loss. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

ML Classifier Fusion for Three Data Streams with Quality Inversely Proportional to Time Resolution

We consider a monitoring scenario of phenomenon using three different streams of measurements whose quality is proportional to their constant inter-arrival times. Each measurement of a stream needs to be binary-classified to reflect the state of interest of the phenomenon. A set of classifiers is separately trained and fused for each stream at its time resolution using measurements collected under known states. We present a machine learning method to fuse the outputs of these fusers to provide a final classification at the finest time resolution. We show that this fused-fusers method provides decisions with likely superior classification probability compared to the best individual classifiers and fused-classifiers. We derive generalization equations that guarantee a superior classification probability of fused-fusers with a confidence probability specified by the classifiers’ generalization equations. We apply these results to study a practical problem of classifying Pu/Np target dissolution events at a radiochemical processing facility using gamma spectral measurements of effluent flows.

Rao, Nageswara↗