Search NASA⌕ Search

SEARCH · Search NASA

Results for “temperature 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 793 records · Page 44

Cosmic topology. Part I. Limits on orientable Euclidean manifolds from circle searches

The Einstein field equations of general relativity constrain the local curvature at every point in spacetime, but say nothing about the global topology of the Universe. Cosmic microwave background anisotropies have proven to be the most powerful probe of non-trivial topology since, within ΛCDM, these anisotropies have well-characterized statistical properties, the signal is principally from a thin spherical shell centered on the observer (the last scattering surface), and space-based observations nearly cover the full sky. The most generic signature of cosmic topology in the microwave background is pairs of circles with matching temperature and polarization patterns. No such circle pairs have been seen above noise in the WMAP or Planck temperature data, implying that the shortest non-contractible loop around the Universe through our location is longer than 98.5% of the comoving diameter of the last scattering surface. We translate this generic constraint into limits on the parameters that characterize manifolds with each of the nine possible non-trivial orientable Euclidean topologies, and provide a code which computes these constraints. In all but the simplest cases, the shortest non-contractible loop in the space can avoid us, and be shorter than the diameter of the last scattering surface by a factor ranging from 2 to at least 6. Further, this result implies that a broader range of manifolds is observationally allowed than widely appreciated. Probing these manifolds will require more subtle statistical signatures than matched circles, such as off-diagonal correlations of harmonic coefficients.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of the inter-species power balance in JET plasmas

Most auxiliary heating methods provide heating to more than one particle species (electrons, ions, impurities) in a fusion plasma. This can lead to substantial temperature differences between species, depending on conditions such as heating power to the different species and collisionality, with temperature differences between species limited by inter-species thermal equipartition and transport. The analysis of the steady-state electron-ion and impurity-ion power balances presented in this paper are used for consistency-checking experimental ion and electron temperature measurements and for inferring the main ion temperature from measured impurity temperatures. As ion temperature measurements by charge exchange spectroscopy (CXS) based on impurity ions have become more difficult and time-consuming since the installation of the ITER-like wall (ILW) with Be and W PFC's, knowing the maximum sustainable temperature difference between ions and electrons, |T i -T e | allows rejecting erroneous measurements. It also obviates the need for an ion temperature measurement, if an electron temperature measurement is available and |T i - T e | cannot be larger than the combined errors of the underlying measurements. A power balance analysis is also required for estimating the errors of the ion and electron heat fluxes prior to any species-resolved transport analysis. The ion-impurity temperature differences are usually found to be small due to strong thermal equipartition between ion species. However, they can approach 10% in JET-ILW low density, high power discharges, such the ones under development for a future JET deuterium–tritium campaign (Joffrin et al 2019 Nucl. Fusion). This has a generally small, but not always negligible effect on the calculation of fusion reaction rates, which depend on main ion temperatures. An important outcome of this analysis is that temperature differences between impurity species are always much smaller than between the impurities and hydrogenic species and can usually be neglected. The article presents two methods for calculating the impurity-to-main ion temperature ratio. Finally, this analysis leads to a method for the reconstruction ion temperature profiles from ion temperature data available at only one or a small number of spatial locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Design and Analysis Progress of ITER Diagnostic Equatorial Port #09

ITER is the world's largest fusion device currently under construction in the South of France with >50 diagnostic systems to be installed inside the port plugs (PPs), the interspace (IS), or the port cell region of various diagnostic ports. The plasma facing diagnostic first wall (DFW) and its supporting diagnostic shield modules (DSM) are designed to protect front-end diagnostics from plasma neutron and plasma radiation, while providing apertures for diagnostic access to the plasma. The design of ITER port plug structures including the DFW and the DSM is largely driven by the electromagnetic loads included on the PP structural components during plasma major disruptions and the vertical displacement events (VDEs). Unlike DFW and DSM, the design of diagnostic system, however, is likely driven by the steady-state thermal loads from plasma volumetric and surface heating and the dynamic response of the in-port components attached to the port-specific DSM or closure plate under transient loads induced on the vacuum vessel and the port extension during asymmetric VDEs. Three tenant diagnostic systems are integrated into the equatorial port 09. The toroidal interferometer/polarimeter, or TIP system, is installed in the left drawer (DSM3, left looking from plasma) for measuring the plasma density so to control the fuel input. The electron cyclotron emission (ECE) system is installed in the middle drawer (DSM2) to provide the high spatial and temporal resolution measurements of electron temperature evolution and the electron thermal transport inferences. The visible/infrared wide angle viewing system is installed in the right drawer (DSM1) to provide visible and infrared viewing and temperature data of the first wall for its protection in support of machine operation. The port plug integration design and multiphysics analyses are performed following port integration requirements including the weight limit (45 tones total), shut down dose rate limits, the cooling/heating and structural integrity validation. Mass distribution for TIP and ECE DSMs has been optimized to minimize the total weight by a new design of the boron carbide shielding pocket. Furthermore, the lightened DSM maintains its front-end load distribution and the structural stiffness with minimum impact to the DFW so to better protect on-board diagnostics; while still provides sufficient front-end stiffness for its structural integrity as well as the diagnostics function requirements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Snow-eater heat waves of the western United States

Abrupt snowmelt, triggered by rain-on-snow events or "snow-eater heat waves," can cause flooding, initiate or accelerate snow drought, and affect water availability. However, the characteristics (e.g., area, duration, and frequency), impacts, and trends of snow-eater heat waves have received little attention. To address this gap, we developed a method to identify snow-eater heat waves and estimate their melt potential using 20th Century Reanalysis version 3 air temperature data, the TempestExtremes algorithm, and an operational snowmelt model (SNOW-17) across 1850-2015. Melt season snow-eater heat waves typically last 3 to 5 days, with three to five events, doubling snowmelt rates. Seven of 11 spring superfloods are shown to coincide with snow-eater heat waves. Since the 1850s, snow-eater heat waves have increased in area and frequency, decreased in duration, and shifted earlier in the melt season. Incorporating snow-eater heat-wave impacts into SNOW-17 enhances extreme melt estimates, improving water management support tools.

Rhoades, Alan M↗

Exploration of Use of Copulas in Analysing the Relationship between Precipitation and Meteorological Drought in Beijing, China

Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI. The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.

54 ENVIRONMENTAL SCIENCES↗

Three-Dimensional Convective–Stratiform Echo-Type Classification and Convectivity Retrieval from Radar Reflectivity

The Echo Classification from COnvectivity (ECCO) algorithm identifies convective and stratiform types of radar echo in three dimensions. It is based on the calculation of reflectivity texture—a combination of the intensity and the heterogeneity of the radar echoes on each horizontal plane in a 3D Cartesian volume. Reflectivity texture is translated into convectivity, which is designed to be a quantitative measure of the convective nature of each 3D radar grid point. It ranges from 0 (100% stratiform) to 1 (100% convective). By thresholding convectivity, a more traditional qualitative categorization is obtained, which classifies radar echoes as convective, mixed, or stratiform. In contrast to previous algorithms, these echo-type classifications are provided on the full 3D grid of the reflectivity field. The vertically resolved classifications, in combination with temperature data, allow for subclassifications into shallow, mid-, deep, and elevated convective features, and low, mid-, and high stratiform regions—again in three dimensions. The algorithm was validated using datasets collected over the U.S. Great Plains during the PECAN field campaign. An analysis of lightning counts shows ~90% of lightning occurring in regions classified as convective by ECCO. A statistical comparison of ECCO echo types with the well-established GPM radar precipitation-type categories show 84% (88%) of GPM stratiform (convective) echo being classified as stratiform (convective) or mixed by ECCO. ECCO was applied to radar grids for the continental United States, the United Arab Emirates, Australia, and Europe, illustrating its robustness and adaptability to different radar grid characteristics and climatic regions.

Radars/Radar observations↗

Estimated Darcy Velocities Using Temperature Time Series for Meander A of East River, Colorado

Heat was used as a tracer to quantify seasonal changes in vertical Darcy velocity through the streambed at three different locations about Meander A of East River, Colorado. The file Raw_Temp.csv represents raw temperature data (in degrees Celsius) collected from the three locations, A, B, and C, at depths of 5, 10, 20, and 35 cm below the sediment-water interface. Darcy velocity estimates were calculated from these data using 1DTempPro and are shown in 1DTempPro_estimates.csv file. Positive values represent upwelling conditions, while negative values indicate downwelling conditions.

54 ENVIRONMENTAL SCIENCES↗

Development and Evaluation of Algorithms to Improve Small- and Medium-Size Commercial Building Operations

Small- and medium-sized (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically utilize packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the U.S. for many reasons, chief among them is to mitigate the climate change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short-cycling, where an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and lead to premature failure of the compressor or its components. The short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Also, SMBs use a time-of-day scheduling is to start the RTUs before the building will be occupied and shut it off when unoccupied. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this report describes three algorithms for detecting the zone set point temperature, RTU cycling rate and occupancy schedule detection that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique and occupancy schedule using symbolic aggregate approximation technique. The report describes the three algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Residential Indoor Temperature Study

In this study, we are adding to the body of knowledge around answering the question: What are good assumptions for HVAC set points in U.S. homes? We collected and analyzed indoor temperature data from US homes using funding from the U.S. Department of Energy's Building America (BA) program, due to the program's reliance on accurate energy simulation of homes. Simulations are used to set Building America goals, predict the impact of new building techniques and technologies, inform research objectives, evaluate home performance, optimize efficiency packages to meet savings goals, customize savings approaches to specific climate zones, and myriad other uses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Low Temperature Time-to-Explosion Experiments in the LLNL’s ODTX/P-ODTX System

Incidents caused by fire and some operations can heat energetic materials that may lead to thermal explosion and result in structural damage and casualty. Thus, explosive thermal sensitivity is an important topic for oilfield perforating operations and impacts perforating system performance and safety. Explosives have time-dependent temperature limits which can lead to thermal decomposition when exceeded and, under some circumstances, can result in performance losses and safety hazards. The One-Dimensional-Time to Explosion (ODTX) system at the Lawrence Livermore National Laboratory (LLNL) has been used for decades to characterize thermal safety of energetic materials. In this study, an integration of a pressure monitoring element has been added into the ODTX system (P-ODTX) to perform extended thermal experiments on HMX at three temperatures 160 °C, 170 °C and 185 °C. The tests generate time-temperature data as well as useful gas pressure data to assist with the thermal safety assessment of the energetics and systems that use the energetics. This report summarizes results of the 3 tests that were performed from July 2018 to November 2018.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NRC Multiphysics Analysis Capability Deployment (FY2021 - Part 2)

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” Task 4b was completed for this report. INL developed a sample problem showing how to use Serpent 2 to calculate macroscopic cross sections for use in Griffin for a typical sodium fast reactor Unprotected Loss of Flow (ULOF) transient. The complicating factor is the relatively large axial gradient of the coolant (and hence fuel) temperature and its evolution during the transient. A 3D Griffin model of the Advanced Burner Test Reactor (ABTR) is coupled to the System Analysis Module (SAM) to perform the ULOF transient. The model includes various explicit feedback mechanisms for fast reactors, including Doppler, radial expansion from the displacement of the support plate, and axial expansion from the displacement of the fuel pins. The results for the ULOF transient are consistent with published values. We observed small effects in the transient results that arise from the superhomogenization equivalence correction of uniform and nonuniform temperature data sets, but they diminish as more dominant reactivity mechanisms are added to the model. Potential improvements to the neutronics model include: adding the differential control rod and sodium feedback mechanisms, implementing cross section re-homogenization based on the partial volume of the various materials, and enhancing the kinetics parameters. Furthermore, the fluids model only includes four subchannels to represent the entire active core due to performance limitations in SAM when attempting to model one subchannel per assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Psychrometric Analysis for New NuMI Evaporator Weather Station

Tritium (H-3) is a weakly radioactive isotope of hydrogen and is a byproduct of accelerator operations at Fermi National Accelerator Laboratory (Fermilab). The Neutrinos at the Main Injector (NuMI) target produced tritiated condensate exhausted via the MI-65 building evaporators. Re-condensation of tritium evaporate was observed on the MI-65 rooftop, on nearby buildings, and on the surrounding grounds due to inefficiency of the existing evaporator system. A new evaporator system is being designed to eliminate re-condensation, and psychrometric data (temperature, humidity and dew point) plays a vital role in determining the location of a weather station to control the new evaporator system.

Alvarado-Anderson, Chase↗

Bryan Mound Collar Compression Study

This report presents a study of collar compression for the wells at the Bryan Mound site. The study includes a comprehensive review of all available Multi-Arm Caliper (MAC) logs from the site, which has been used to identify specific wells that are experiencing casing restrictions at collar joints. Additional site-wide analysis of Bryan Mound well temperature data, proximity to sulphur wells, pulsed eddy current (PEC) logs, and a general spatial analysis has been included.

02 PETROLEUM↗

Mechanical Solution for Existing Conductors

The rapid growth in energy demand, driven by advancements in AI technology, renewable energy integration, and increased industrial activity, highlights the need for innovative solutions to improve the resiliency and efficiency of the power grid. This report details the fire testing of GridWrap’s Composite WiRe Wrap, to evaluate the wrap's ability to enhance conductor performance under wildfire-simulated conditions. Conductors were prepared and tested in a controlled environment at 400°C for 18 minutes, during which sag and temperature data were recorded. The results demonstrated that the unwrapped conductor sagged 3/16ths of an inch, while the WiRe Wrapped conductor sagged only 1/16th of an inch under identical conditions, indicating a significant improvement in mechanical performance. This project, conducted as part of a collaborative effort between BEA (Idaho National Laboratory’s managing contractor) and GridWrap, Inc., demonstrates the potential of grid-enhancing technologies like WiRe Wrap to reduce sag, increase grid resiliency, and support the future energy landscape. By validating the performance of such technologies in real-world scenarios, this work provides critical insights for industry adoption, benefiting both grid operators and U.S. taxpayers through improved reliability, reduced emissions, and enhanced energy delivery.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Post Access Report: Initial testing of wave energy powered UV-C LED anti-biofouling system

In the experiment entitled “Initial Testing of Wave Energy Powered UV-C LED Anti-Biofouling System,” a UV-C LED was used to treat platinum-coated titanium coupons emulating CTD electrode material. An additional control set of coupons were exposed to seawater without the LED treatment. The experimental setup was deployed in seawater tanks at PNNL-Sequim’s Marine and Coastal Research Laboratory (MCRL) for the duration of six months. Tank seawater temperature data were collected for the duration of the experimental campaign. At two-month intervals triplicate sets of coupons were removed from both treatment and control test chambers and weighed to characterize biomass accumulation. After weighing, the coupons were photographed in initial condition, with a stain applied to highlight biofouling growth, and after rinsing off excess stain. These photographs were analyzed using PNNL’s Biofouling Growth Index (BGI) software and with a calculation of percentage dark pixels after conversion to grayscale. Additionally, at the final 6-month datapoint triplicate sets of control and test coupons were sent to PNNL-Richland’s Environmental Molecular Sciences Laboratory (EMSL) for scanning electron microscopy. All data organization and collection methods are described in further detail in the document “TEAMER_3newable_Data_Guide.pdf.” Biomass accumulation increased over time on both sets of coupons, and percent area biofouled demonstrated a similar trend. Analysis of the collected data resulted in the findings that treatment method has an impact on biofouling growth, though to a much less significant extent than time does. Additionally, qualitative findings included the presence of advanced life forms such as worms in the control test chamber, but not in the treated test chamber.

16 TIDAL AND WAVE POWER↗

UAV-Based High Resolution Thermal Imaging for Vegetation Monitoring, and Plant Phenotyping Using ICI 8640 P, FLIR Vue Pro R 640, and thermoMap Cameras

The growing popularity of Unmanned Aerial Vehicles (UAVs) in recent years, along with decreased cost and greater accessibility of both UAVs and thermal imaging sensors, has led to the widespread use of this technology, especially for precision agriculture and plant phenotyping. There are several thermal camera systems in the market that are available at a low cost. However, their efficacy and accuracy in various applications has not been tested. In this study, three commercially available UAV thermal cameras, including ICI 8640 P-series (Infrared Cameras Inc., USA), FLIR Vue Pro R 640 (FLIR Systems, USA), and thermoMap (senseFly, Switzerland) have been tested and evaluated for their potential for forest monitoring, vegetation stress detection, and plant phenotyping. Mounted on multi-rotor or fixed wing systems, these cameras were simultaneously flown over different experimental sites located in St. Louis, Missouri (forest environment), Columbia, Missouri (plant stress detection and phenotyping), and Maricopa, Arizona (high throughput phenotyping). Thermal imagery was calibrated using procedures that utilize a blackbody, handheld thermal spot imager, ground thermal targets, emissivity and atmospheric correction. A suite of statistical analyses, including analysis of variance (ANOVA), correlation analysis between camera temperature and plant biophysical and biochemical traits, and heritability were utilized in order to examine the sensitivity and utility of the cameras against selected plant phenotypic traits and in the detection of plant water stress. In addition, in reference to quantitative assessment of image quality from different thermal cameras, a non-reference image quality evaluator, which primarily measures image focus that is based on the spatial relationship of pixels in different scales, was developed. Our results show that (1) UAV-based thermal imaging is a viable tool in precision agriculture and (2) the three examined cameras are comparable in terms of their efficacy for plant phenotyping. Overall, accuracy, when compared against field measured ground temperature and estimating power of plant biophysical and biochemical traits, the ICI 8640 P-series performed better than the other two cameras, followed by FLIR Vue Pro R 640 and thermoMap cameras. Our results demonstrated that all three UAV thermal cameras provide useful temperature data for precision agriculture and plant phenotying, with ICI 8640 P-series presenting the best results among the three systems. Cost wise, FLIR Vue Pro R 640 is more affordable than the other two cameras, providing a less expensive option for a wide range of applications.

47 OTHER INSTRUMENTATION↗

Presenting a Model to Predict Changing Snow Albedo for Improving Photovoltaic Performance Simulation

As photovoltaic (PV) deployment increases worldwide, PV systems are being installed more frequently in locations that experience snow cover. The higher albedo of snow, relative to the ground, increases the performance of PV systems in northern and high-altitude locations by reflecting more light onto the PV modules. Accurate modeling of the snow’s albedo can improve estimates of PV system production. Typical modeling of snow albedo uses a simple two-value model that sets the albedo high when snow is present, and low when snow is not present. However, snow albedo changes over time as snow settles and melts and a binary model does not account for transitional changes, which can be significant. Here, we present and validate a model for estimating snow albedo as it changes over time. The model is simple enough to only require daily snow depth and hourly average temperature data, but can be improved through the addition of site-specific factors, when available. We validate this model to quantify its ability to more accurately predict snow albedo and compare the model’s performance against satellite imagery-based methods for obtaining historical albedo data. In addition, we perform modeling using the System Advisor Model (SAM) to show the impact of changes in albedo on energy modeling for PV systems. Overall, our albedo model has a significantly improved ability to predict the solar insolation on PV modules in real time, especially on bifacial PV modules where reflected irradiance plays a larger role in energy production.

Pike, Christopher (ORCID:0000000155888033)↗