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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Electrical properties of n-type GaSb substrates and p-type GaSb buffer layers for InAs/InGaSb superlattice infrared detectors

Lightly doped n-type GaSb substrates with p-type GaSb buffer layers are the preferred templates for growth of InAs/InGaSb superlattices used in infrared detector applications because of relatively high infrared transmission and a close lattice match to the superlattices. We report here temperature dependent resistivity and Hall effect measurements of bare substrates and substrate-p-type buffer layer structures grown by molecular beam epitaxy. Multicarrier analysis of the resistivity and Hall coefficient data demonstrate that high temperature transport in the substrates is due to conduction in both the high mobility zone center Γ band and the low mobility off-center L band. High overall mobility values indicate the absence of close compensation and that improved infrared and transport properties were achieved by a reduction in intrinsic acceptor concentration. Standard transport measurements of the undoped buffer layers show p-type conduction up to 300 K indicating electrical isolation of the buffer layer from the lightly n-type GaSb substrate. However, the highest temperature data indicate the early stages of the expected p to n type conversion which leads to apparent anomalously high carrier concentrations and lower than expected mobilities. Data at 77 K indicate very high quality buffer layers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management. Without accessibility to other data sources, the onsite observed temperatures or the airport temperatures are used in forecast models. In this paper, we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations (PWS) to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework. The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs. Our approach is distinguished from existing literature in various aspects. First, we leverage the crowdsourcing weather data from PWS in addition to public data sources. In this way, the data is at much finer time resolution (e.g., at 5-minute frequency) and spatial resolution (e.g., arbitrary location vs grid). Second, our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance. Here, we demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio, Texas, USA. In general, the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50% compares with persistent model and has 90% chance to outperform airport forecast in short-term forecasting. In a real-time setting, the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon. Moreover, we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance. Finally, we implement our model in other cities such as Syracuse and Chicago to test the model's performance in different landforms and climate types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data Needs for Modeling Low-Temperature Non-Equilibrium Plasmas: The LXCat Project, History, Perspectives and a Tutorial

Technologies based on non-equilibrium, low-temperature plasmas are ubiquitous in today’s society. Plasma modeling plays an essential role in their understanding, development and optimization. An accurate description of electron and ion collisions with neutrals and their transport is required to correctly describe plasma properties as a function of external parameters. LXCat is an open-access, web-based platform for storing, exchanging and manipulating data needed for modeling the electron and ion components of non-equilibrium, low-temperature plasmas. The data types supported by LXCat are electron- and ion-scattering cross-sections with neutrals (total and differential), interaction potentials, oscillator strengths, and electron- and ion-swarm/transport parameters. Online tools allow users to identify and compare the data through plotting routines, and use the data to generate swarm parameters and reaction rates with the integrated electron Boltzmann solver. In this review, the historical evolution of the project and some perspectives on its future are discussed together with a tutorial review for using data from LXCat.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Independent confirmation of global land warming without the use of station temperatures

Confidence in estimates of anthropogenic climate change is limited by known issues with air temperature observations from land stations. Station siting, instrument changes, changing observing practices, urban effects, land cover, land use variations, and statistical processing have all been hypothesized as affecting the trends presented by the Intergovernmental Panel on Climate Change and others. Any artifacts in the observed decadal and centennial variations associated with these issues could have important consequences for scientific understanding and climate policy. We use a completely different approach to investigate global land warming over the 20th century. We have ignored all air temperature observations and instead inferred them from observations of barometric pressure, sea surface temperature, and sea-ice concentration using a physically based data assimilation system called the 20th Century Reanalysis. This independent data set reproduces both annual variations and centennial trends in the temperature data sets, demonstrating the robustness of previous conclusions regarding global warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Thermochemical characterization of polymers for improved fire safety

Apparatus has been constructed for studying the thermal decomposition of polymers as a function of temperature. Such data is needed to evaluate the toxic threat presented by polymeric materials under fire conditions such as the smoldering fire of the type that occurs in closed areas such as coat closets in which anaerobic decomposition of polymers occurs. The apparatus allows the products of thermal decomposition to be collected and analyzed by infrared spectrometry and mass spectrometry. Data obtained from dog hair, an aromatic polyamide, polyphenylene sulfide, and polybenzimidazole are presented. It was found that significant amounts of toxic gas were evolved from dog hair at temperatures as low as 250 C, while temperatures in excess of 500 C were necessary in order for the evolution of toxic gas from the aromatic polymers to become significant.

Lerner, N. R.↗
NASA NTRS1978

Effect of silicone oil on nozzle heat transfer in solid propellant rockets

The feasibility of reducing heat transfer rates to inert nozzle walls in solid rockets by addition of silicone oil as a propellant ingredient is explored experimentally. A metallized control propellant and its counterpart with 1% silicone oil are fired in a 2 1/2-in. diameter end burning all-metal burner. Pressure-time histories are obtained; temperature-time data at the nozzle throat are obtained in some of the runs. The heat loss by the product gases to the cold inert walls of the nozzle lower the temperature of the gases leading to the condensation of aluminum oxide on the walls. This condensation is used as an index of the heat transfer rate to the nozzle. On a statistical basis it is found that the silicone propellant gives practically no condensation in 70% of the firings contrasted with 21% for its counterpart with no silicone oil in it. The gas temperature at the nozzle throat is experimentally seen to be generally higher with the silicone propellant than with its counterpart; this higher temperature is consistent with a preliminary analysis that is used here to relate the nozzle surface temperature to the heat transfer from the product gases.

Ramohalli, K.↗
NASA NTRS1990

An investigation into the flow behavior of a single phase gas system and a two phase gas/liquid system in normal gravity with nonuniform heating from above

The fluid behavior in normal gravity of a single phase gas system and a two phase gas/liquid system in an enclosed circular cylinder heated suddenly and nonuniformly from above was investigated. Flow visualization was used to obtain qualitative data on both systems. The use of thermochromatic liquid crystal particles as liquid phase flow tracers was evaluated as a possible means of simultaneously gathering both flow pattern and temperature gradient data for the two phase system. The results of the flow visualization experiments performed on both systems can be used to gain a better understanding of the behavior of such systems in a reduced gravity environment and aid in the verification of a numerical model of the system.

Disimile, Peter J.↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
NASA NTRS1980

Radiation damage annealing mechanisms and possible low temperature annealing in silicon solar cells

The defect responsible for reverse annealing in 2 ohm/cm n(+)/p silicon solar cells was identified. This defect, with energy level at e sub v + 0.30 eV was tentatively identified as a boron oxygen-vacancy complex. Results indicate that its removal could result in significant annealing for 2 ohm/cm and lower resistivity cells at temperatures as low as 200 C. These results were obtained by use of an expression derived from the Shockley-Read-Hall recombination theory which relates measured diffusion length ratios to relative defect concentrations and electron capture cross sections. The relative defect concentrations and one of the required capture cross sections are obtained from Deep Level Transient Spectroscopy. Four additional capture cross sections are obtained using diffusion length data and data from temperature dependent lifetime studied. These calculated results are in reasonable agreement with experimental data.

Weinberg, I.↗
NASA NTRS1990

Wave number spectra from temperature-humidity infrared radiometer 6.7-micron water vapor data

Wave number spectra from Nimbus 7 temperature-humidity infrared radiometer 6.7-micron water vapor data are analyzed using series 4800 km long, in regions free of high clouds and frontal zones. In these regions, the brightness temperatures approximate temperatures on a water vapor isosteric (constant density) surface, rather than averages over a broad vertical layer. Power above the noise can be extracted down to wavelengths of about 60 km. Fitting the power spectrum versus horizontal wave number k to a k to the -nth power law for wavelengths from 60 to a few hundred kilometers gives slopes of n = 2.7 to 3.0, depending on the exact wave numbers that are fitted. Thunderstorms and convective cloud systems may constitute an energy source for the reverse energy cascade which produces a -5/3 spectral slope. The results suggest that when these features are not present, the enstrophy-cascading process that gives a -3 slope may govern the motion at scales smaller than it has heretofore been observed.

Manney, Gloria L.↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microscopic Mechanisms of Glasslike Lattice Thermal Transport in Cubic Cu 12 Sb 4 S 13 Tetrahedrites

Materials based on cubic tetrahedrites (Cu 12 Sb 4 S 13 ) are useful thermoelectrics with unusual thermal and electrical transport properties, such as very low and nearly temperature-independent lattice thermal conductivity (κ L ). We explain the microscopic origin of the glasslike κ L in Cu 12 Sb 4 S 13 by explicitly treating anharmonicity up to quartic terms for both phonon energies and phonon scattering rates. We show that the strongly unstable phonon modes associated with trigonally coordinated Cu atoms are anharmonically stabilized above approximately 100 K and continue hardening with increasing temperature in accord with experimental data. This temperature-induced hardening effect reduces scattering of heat carrying acoustic modes by reducing the available phase space for three-phonon processes, thereby balancing the conventional ∝ T increase in scattering due to phonon population and yielding nearly temperature independent κ L . Furthermore, we find that very strong phonon broadening leads to a qualitative breakdown of the conventional phonon-gas model and modify the dominant heat transport mechanism from the particlelike phonon wave packet propagation to incoherent contributions described by the off-diagonal terms in the heat-flux operator, which are typically prevailing in glasses and disordered crystals. Furthermore, our work paves the way to a deeper understanding of glasslike thermal conductivity in complex crystals with strong anharmonicity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Screening of Additional Candidate Low-Temperature Glasses for Technetium Recovered from Hanford Effluent Management Facility Evaporator Bottoms

In this annex to a previously reported study, a series of laboratory screening tests was conducted to identify low-temperature glasses that have significant potential for use in disposition of technetium from a Hanford Tank Waste Treatment & Immobilization Plant (WTP) secondary liquid waste stream. Specifically, a glass waste form is sought that would be suitable for on-site disposition of technetium, salts, and other species in a Tc-rich stream recovered by ion exchange from the future Effluent Management Facility (EMF) evaporator concentrate. In the current study, several additional candidate glasses were identified, and testing of previous candidates was extended to include the Toxicity Characteristic Leaching Procedure (TCLP). In non-radioactive testing with rhenium surrogate, new formulations incorporated a simulated ion exchange eluate at temperatures below 750 °C to produce an amorphous, or mixed crystalline-amorphous, product. Incorporation of technetium (NaTcO 4 )-containing simulated eluate was evaluated for two of these glasses. Technetium was not retained well in these glasses, confounding the previous conclusion that Tc volatilization during vitrification can be reduced by appropriate selection of low-temperature glasses. Preliminary data for additional low-temperature glass compositions and recommendations for future work are provided. This report is a deliverable associated with requisition 55068-004-03 NFE-17-0020 "Candidate Low-T Glass Waste Forms for EMF Bottoms On-Site Disposition Alternative."

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

National Renewable Energy Laboratory, South Table Mountain Campus, Golden, Colorado

The National Renewable Energy Laboratory (NREL) South Table Mountain campus, located in Golden, Colorado, has multiyear datasets from buildings with approximately 1,100,000 sq ft of floor area. These 16 buildings include a large office, nine laboratories, and other education or public assembly facilities such as an education center, a warehouse, quick service restaurants, two site entrance security buildings, and a parking garage—all constructed and improved from 1982 to 2014. These datasets are also available from the NREL data storage and management platform SkySparks. The datasets contain electricity meter data (poser, voltage, and current) with 1-minute resolution and building automation system (BAS) data with resolutions of 5 or 15 minutes. Some subsystems (e.g., lighting) or equipment electricity data have the same intervals as above. Some mechanical equipment state or condition data, such as flow and temperature, are captured with 5- to 15-minute intervals. The types of measurement points (i.e., electrical meter power and zone temperature) and associated data quality across the campus are typical, which helps reduce the unreliability of data quality.

STM, Systems and equipment operational, Energy use↗
DOE OSTI2018

Planck 2015 Constraints on the Non-flat XCDM Inflation Model

We examine the Planck 2015 cosmic microwave background (CMB) anisotropy data by using a physically consistent energy density inhomogeneity power spectrum generated by quantum-mechanical fluctuations during an early epoch of inflation in the non-flat XCDM model. Here dark energy is parameterized using a fluid with a negative equation of state parameter but with the speed of fluid acoustic inhomogeneities set to the speed of light. We find that the Planck 2015 data in conjunction with baryon acoustic oscillation distance measurements are reasonably well fit by a closed-XCDM model in which spatial curvature contributes a percent of the current cosmological energy density budget. In this model, the measured non-relativistic matter density parameter and Hubble constant are in good agreement with values determined using most other data. Depending on cosmological parameter values, the closed-XCDM model has reduced power, relative to the tilted, spatially flat ΛCDM case, and can partially alleviate the low multipole CMB temperature anisotropy deficit and can help partially reconcile the CMB anisotropy and weak lensing σ 8 constraints, at the expense of somewhat worsening the fit to higher multipole CMB temperature anisotropy data. Furthemore, the closed-XCDM inflation model does not seem to improve the agreement much, if at all, compared to the closed ΛCDM inflation case, even though it has one additional free parameter.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

A study of remote sensing as applied to regional and small watersheds. Volume 2: Supporting technical details

The Stanford Watershed Model, the Kentucky Watershed Model and OPSET program, and the NASA-IBM system for simulation and analysis of watersheds are described in terms of their applications to the study of remote sensing of water resources. Specific calibration processes and input and output parameters that are instrumental in the simulations are explained for the following kinds of data: (1) hourly precipitation data; (2) daily discharge data; (3) flood hydrographs; (4) temperature and evaporation data; and (5) snowmelt data arrays. The Sensitivity Analysis Task, which provides a method for evaluation of any of the separate simulation runs in the form of performance indices, is also reported. The method is defined and a summary of results is given which indicates the values obtained in the simulation runs performed for Town Creek, Alabama; Alamosa Creek, Colorado; and Pearl River, Louisiana. The results are shown in tabular and plot graph form. For Vol. 1, see N74-27813.

Source record↗
NASA NTRS1973

An equation of state for oxygen and nitrogen

Recent measurements of the thermodynamic properties of oxygen and nitrogen have been used to develop a single equation of state for both fluids; with appropriate coefficients, the equation describes the pressure-density-temperature surface for each fluid within the estimated experimental uncertainty of the data. The formulation uses least squares curve fitting of the equation of state to the available experimental data (including pressure-density-temperature data, saturation data, and measured isochoric heat capacities). New vapor pressure equations and equations for the ideal gas heat capacities of oxygen and nitrogen are included for use in calculation of derived thermodynamic properties.

Jacobsen, R. T.↗