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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Estimations of electron densities and temperatures in He-3 dominated plasmas

It is very useful to have a method of estimation for electron temperature and electron densities in nuclear pumped plasmas because measurements of such quantities are very difficult. This paper describes a method, based on rate equation analysis of the ionized species in the plasma and the electron energy balance. In addition to the ionized species, certain neutral species must also be calculated. Examples are given for pure helium and a mixture of helium and argon. In the HeAr case, He(+), He2(+), He/2 3S/, Ar(+), Ar2(+), and excited Ar are evaluated.

Depaola, B. D.↗
DOE OSTI2024

Shot-noise-induced lower temperature limit of the nonneutral plasma parallel temperature diagnostic

Abstract We develop a new algorithm to estimate the temperature of a nonneutral plasma in a Penning-Malmberg trap. The algorithm analyzes data obtained by slowly lowering a voltage that confines one end of the plasma and collecting escaping charges, and is a maximum likelihood estimator based on a physically-motivated model of the escape protocol presented in (Beck in Measurement of the magnetic and temperature dependence of the electron-electron anisotropic temperature relaxation rate. PhD thesis, 1990). Significantly, our algorithm may be used on single-count data, allowing for improved fits with low numbers of escaping electrons. This is important for low-temperature plasmas such as those used in antihydrogen trapping. We perform a Monte Carlo simulation of our algorithm, and assess its robustness to intrinsic shot noise and external noise. The assumptions in this paper allow for a lower bound for measurable plasma temperatures of approximately $3\,\mathrm{K}$ 3 K for plasmas of length $1\,\mathrm{cm}$ 1 cm , with approximately 100 particle counts needed for an accuracy of $\pm 10 \%$ ± 10 % .

Zhong, Adrianne (ORCID:0000000162618736)↗
NASA NTRS2011

Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

Shen, Suhung↗
DOE OSTI2025

A MOOSE-Based Model for Fission Product Transport and Source Term Estimation for High-Temperature Gas-Cooled Reactors

Thanks to fuel elements containing tristructural isotropic (TRISO) particles combined with a low core power density and passive feedback mechanisms leading to modest temperature rises in the event of accidental events, high-temperature gas-cooled reactors (HTGRs) offer a high degree of reliability in terms of fission product retention. While the anticipated source term for HTGRs is expected to be very low, it is important to provide a quantitative estimate of radiological releases during nominal and accidental conditions. Here, we propose a computationally efficient mechanistic source term methodology relying on the Multiphysics Object Oriented Simulation Environment (MOOSE) for tracking fission product transport from TRISO particles up to the coolant pressure boundary, as well as modeling the transport and potential deposition of these nuclides inside the reactor coolant loop. The proposed computational scheme is applied to estimate source term inventories for a representative 10-MW(thermal) prismatic high-temperature microreactor and is qualitatively compared against known release fractions. In addition to providing an alternate analysis tool, this MOOSE model can help reactor designers quantify the influence of key design parameters relevant for studies of radiological dose consequences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1982

Validation of Nimbus-7 temperature-humidity infrared radiometer estimates of cloud type and amount

Estimates of clear and low, middle and high cloud amount in fixed geographical regions approximately (160 km) squared are being made routinely from 11.5 micron radiance measurements of the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR). The purpose of validation is to determine the accuracy of the THIR cloud estimates. Validation requires that a comparison be made between the THIR estimates of cloudiness and the 'true' cloudiness. The validation results reported in this paper use human analysis of concurrent but independent satellite images with surface meteorological and radiosonde observations to approximate the 'true' cloudiness. Regression and error analyses are used to estimate the systematic and random errors of THIR derived clear amount.

Stowe, L. L.↗
NASA NTRS1986

The equilibrium structure of thin magnetic flux tubes. II

The thermal structure of the medium inside thin, vertical magnetic flux tubes embedded in a given external atmosphere is investigated, assuming cylindrical symmetry and a depth-independent plasma beta. The variation with tube radius of the temperature on the tube axis is computed and the temperature on the tube wall is estimated. The temperature variation across the flux tube is found to be due to the depth variation of the intensity and to the density stratification of the atmosphere. Since the temperature difference between the axis and the wall is small in thin flux tubes (of the order of 10 percent), the horizontal temperature gradient may often be neglected and the temperature in a tube of given radius may be described by a single function of depth. Thus, a more detailed numerical treatment of the radiative transfer within thin flux tubes can be substantially simplified by neglecting horizontal temperature differences within the flux tube proper.

Kalkofen, W.↗
DOE OSTI2024

Numerical thermalization in 2D PIC simulations: Practical estimates for low-temperature plasma simulations

The process of numerical thermalization in particle-in-cell (PIC) simulations has been studied extensively. It is analogous to Coulomb collisions in real plasmas, causing particle velocity distributions (VDFs) to evolve toward a Maxwellian as macroparticles experience polarization drag and resonantly interact with the fluctuation spectrum. This paper presents a practical tutorial on the effects of numerical thermalization in 2D PIC applications. Scenarios of interest include simulations, which must be run for many thousands of plasma periods and contain a population of cold electrons that leave the simulation space very slowly. This is particularly relevant to many low-temperature plasma discharges and materials processing applications. We present numerical drag and diffusion coefficients and their associated timescales for a variety of grid resolutions, discussing the circumstances under which the electron VDF is modified by numerical thermalization. Though the effects described here have been known for many decades, direct comparison of analytically derived, velocity-dependent numerical relaxation timescales to those of other relevant processes has not often been applied in practice due to complications that arise in calculating thermalization rates in 1D simulations. Using these comparisons, we estimate the impact of numerical thermalization in several examples of low-temperature plasma applications including capacitively coupled plasma discharges, inductively coupled plasma discharges, beam plasmas, and hollow cathode discharges. Finally, we discuss possible strategies for mitigating numerical relaxation effects in 2D PIC simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1980

Thermography for estimating near-surface soil moisture under developing crop canopies

Previous investigations of thermal infrared techniques using remote sensors (thermography) for estimating soil water content have been limited primarily to bare soil. Ground-based and aircraft investigations were conducted to evaluate the potential for extending the thermography approach to developing crop canopies. A significant exponential relationship was found between the volumetric soil water content in the 0-4 cm soil layer and the diurnal difference between surface soil temperature measured at 0230 and 1330 LST (satellite overpass times of NASA's Heat Capacity Mapping Mission - HCMM). Surface soil temperatures were estimated using minimum air temperature, percent cover of the canopy and remote measurements of canopy temperature. Results of the investigation demonstrated that thermography can potentially be used to estimate soil temperature and soil moisture throughout a complete growing season for a number of different crops and soils.

Heilman, J. L.↗
NASA NTRS1993

Estimation of the global average temperature with optimally weighted point gauges

This paper considers the minimum mean squared error (MSE) incurred in estimating an idealized Earth's global average temperature with a finite network of point gauges located over the globe. We follow the spectral MSE formalism given by North et al. (1992) and derive the optimal weights for N gauges in the problem of estimating the Earth's global average temperature. Our results suggest that for commonly used configurations the variance of the estimate due to sampling error can be reduced by as much as 50%.

Hardin, James W.↗
DOE OSTI2022

Out of Distribution Detection with Neural Network Anchoring

This is code to reproduce and build on OOD detection from the paper "Out of Distribution Detection with Neural Network Anchoring". Our goal here is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable this, we propose a new training strategy called anchoring that can estimate appropriate temperature values for each sample, leading to state-of-the-art OOD detection performance across several benchmarks. Using NTK theory, we show that this temperature function estimate is closely linked to the epistemic uncertainty of the classifier, which explains its behavior. In contrast to some of the best-performing OOD detection approaches, our method does not require exposure to additional outlier datasets, custom calibration objectives, or model ensembling. Through empirical studies with different OOD detection settings - far OOD, near OOD, and semantically coherent OOD - we establish a highly effective OOD detection approach.

Thiagarajan, Jayaraman↗
NASA NTRS2004

Electrical Conductivity of HgTe at High Temperatures

The electrical conductivity of HgTe was measured using a rotating magnetic field method from 300 K to the melting point (943 K). A microscopic theory for electrical conduction was used to calculate the expected temperature dependence of the HgTe conductivity. A comparison between the measured and calculated conductivities was used to obtain the estimates of the temperature dependence of Gamma(sub 6)-Gamma(sub 8) energy gap from 300 K to 943 K. The estimated temperature coefficient for the energy gap was comparable to the previous results at lower temperatures (less than or equal to 300 K). A rapid increase in the conductivity just above 300 K and a subsequent decrease at 500 K is attributed to band crossover effects. This paper describes the experimental approach and some of the theoretical calculation details.

Li, C.↗
NASA NTRS1999

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

Morris, A. Terry↗
DOE OSTI2021

Fluid temperature predictions of geothermal borefields using load estimations via state observers

Fluid temperature predictions of geothermal borefields usually involves temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modeled as a linear state space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised when the borefield is already operating and its load history is not registered or there are gaps in the data. This paper assesses the performance of state observers to estimate the borefield load history and obtain accurate fluid predictions. Results show that both Time-Varying Kalman Filter (TVKF) and Moving Horizon Estimator (MHE) provide predictions with average and maximum errors below 0.1 $^\circ C$ and 1 $^\circ C$ respectively. MHE outperforms TVKF in terms of n-step ahead output predictions and load history profile at the expenses of about 5 times more computational time.

Figueroa, Iago C.↗
NASA NTRS1976

Estimation of daily mean air temperature from satellite derived radiometric data

The Screwworm Eradication Data System (SEDS) at JSC utilizes satellite derived estimates of daily mean air temperature (DMAT) to monitor the effect of temperature on screwworm populations. The performance of the SEDS screwworm growth potential predictions depends in large part upon the accuracy of the DMAT estimates.

Phinney, D.↗
DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

2-D Surface Temperature Simulation Data and Matlab Scripts

SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sjoberg, Carl Magnus↗
NASA NTRS1979

Thermal infrared properties of the Martian atmosphere. I - Global behavior at 7, 9, 11, and 20 microns

Infrared observations of Mars by the Viking infrared thermal mapper (IRTM) are presented for conditions of both a relatively clear and a dust-laden atmosphere. The 7-, 9-, 11-, and 20-micron bands of the IRTM respond differently to radiation emitted through and by a dusty atmosphere, permitting characterization of the global atmospheric state, monitoring of secular changes, and derivation of optical depth information. Surface temperature behavior is found to be greatly modified by the diminution of insolation and thermal blanketing resulting from global dust storms. Brightness temperature at 7 microns is employed to estimate surface temperatures in the presence of dust absorption. The difference (T7) is indicative of airborne dust when thermal contrast exists between the surface and atmosphere. The diurnal behavior of T7-T9 reveals changes in the contrast; the sign of the differential reverses as the surface, warmer than the atmosphere in daytime, becomes cooler than the atmosphere at night. IRTM observations of local areas at varying emission angle yield optical depths indicative of global trends. Two global dust storms in 1977 produced large optical depth changes: at 9 microns the optical depth became as large as 2.0.

Martin, T. Z.↗
NASA NTRS1994

Statistical uncertainties in temperature diagnostics for hot coronal plasma using the ASCA SIS

Statistical uncertainties in determining the temperatures of hot (0.5-10 keV) coronal plasmas are investigated. The statistical presicion of various spectral temperature diagnostics is established by analyzing synthetic ASCA solid-state imaging spectrometer (SIS) CCD spectra. The diagnostics considered are the ratio of hydrogen-like to helium-like line complexes of Z greater than or = 14 elements, line-free portions of the continuum, and the entire spectrum. While fits to the entire spectrum yield the highest statistical precision, it is argued that fits to the line-free continuum are less susceptible to atomic data uncertainties but lead to a modest increase in statistical uncertainty over full spectral fits. Temperatures deduced from line ratios can have similar accuracy, but only over a narrow range of temperatures. Convenient estimates of statistical accuracies for the various temperature diagnostics are provided which may be used in planning ASCA SIS observations.

Swartz, Douglas A.↗