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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 559 records · Page 31

An interdisciplinary analysis of ERTS data for Colorado mountain environments using ADP Techniques

Author identified significant preliminary results from the Ouachita portion of the Texoma frame of data indicate many potentials in the analysis and interpretation of ERTS data. It is believed that one of the more significant aspects of this analysis sequence has been the investigation of a technique to relate ERTS analysis and surface observation analysis. At present a sequence involving (1) preliminary analysis based solely upon the spectral characteristics of the data, followed by (2) a surface observation mission to obtain visual information and oblique photography to particular points of interest in the test site area, appears to provide an extremely efficient technique for obtaining particularly meaningful surface observation data. Following such a procedure permits concentration on particular points of interest in the entire ERTS frame and thereby makes the surface observation data obtained to be particularly significant and meaningful. The analysis of the Texoma frame has also been significant from the standpoint of demonstrating a fast turn around analysis capability. Additionally, the analysis has shown the potential accuracy and degree of complexity of features that can be identified and mapped using ERTS data.

Hoffer, R. M.↗

Trap‐Engineering the Persistent Luminescence of Ca 3 Ga 4 O 9 :Tb 3+ via Al 3+ Substitution for Optical Data Storage

Abstract Optically stimulated luminescence (OSL) materials hold great potential for optical data storage (ODS) and anticounterfeiting applications. Nevertheless, the scarcity of suitable luminescent materials with deep‐level traps remains a significant obstacle. Herein, a host substation strategy have been employed to tune the persistent luminescence (PersL) and OSL properties of Ca 3 Ga 4 O 9 :Tb 3+ by Al 3+ substitution through trap engineering and demonstrated their potential. Specifically, the photoluminescence of the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ of Tb 3+ is first investigated due to its different occupancies of Ca 2+ . The influence of host substitution on the crystal structure, trap depth, trap density, PersL, and OSL properties have further investigated. A series of strong PersL and OSL peaks from the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ with bluish‐green emissions have been observed. The Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ have shown controllable photon release upon thermal and optical stimuli, enhancing their performance for ODS. Thermally stimulated luminescence suggests that vacancy and defect concentrations inside the Ca 3‐x% (Ga 1‐y% Al y% ) 4 O 9 :x%Tb 3+ can be manipulated by Tb 3+ doping and Al 3+ substitution, which ultimately leads to the formation of deep traps and a broad distribution of traps with increased deep trap concentration. The work demonstrates that trap engineering through Al 3 ⁺ substitution is an effective method for tuning PersL and OSL properties of Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ for ODS.

Abeywickrama, Thulitha M. [Department of Chemistry↗

Deblurring

In most instances, traditional EEG methodology provides insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. This article describes a method called Deblurring for increasing the spatial detail of the EEG and for fusing neurophysiologic and neuroanatomic data. Deblurring estimates potentials near the outer convexity of the cortex using a realistic finite element model of the structure of a subject's head determined from their magnetic resonance images. Deblurring is not a source localization technique and thus makes no assumptions about the number or type of generator sources. The validity of Deblurring has been initially tested by comparing deblurred data with potentials measured with subdural grid recordings. Results suggest that deblurred topographic maps, registered with a subject's magnetic resonance imaging and rendered in three dimensions, provide better spatial detail than has heretofore been obtained with scalp EEG recordings. Example results are presented from research studies of somatosensory stimulation, movement, language, attention and working memory. Deblurred ictal EEG data are also presented, indicating that this technique may have future clinical application as an aid to seizure localization and surgical planning.

Non-NASA Center↗

Assessing overall building energy performance of a large population of residential single-family homes using limited field data

The U.S. Department of Energy (DOE), through the Building Energy Codes Program (BECP), supports building energy code development and implementation processes to achieve the maximum practicable, cost-effective improvements in energy efficiency while providing safe, healthy buildings for occupants. Currently, there is a lack of statistically representative data that shows how energy codes are implemented in the field and the energy savings opportunities that exist. To address this gap, DOE initiated a research study targeted at new residential single-family homes in 8 states starting in the fall of 2014. The study comprises of a baseline phase to determine current levels of compliance with the key energy provisions of the residential building energy code, identify issues, and calculate potential energy savings from improved compliance; a second phase implementing education, training and outreach activities designed to increase targeted code compliance; and a post-study phase to measure the impact of the training and outreach activities compared to the baseline phase. Initial analyses determined the code requirements with the largest energy impact and the minimum number of observations required to detect statistically significant differences in energy use. Data was collected in the field during a single site visit to avoid bias from repeat visits. However, the single site visit principle prevented energy simulation of individual homes due to the lack of all required model inputs. To address this, energy simulation was conducted using Pacific Northwest National Laboratory’s prototype building models and employing bootstrap random sampling on the data collected from all homes visited. The modeled energy consumption using the observed field data was evaluated relative to that associated with the minimum code requirements and potential savings associated with improved compliance of select items were assessed. This paper discusses the methodology developed for this field study, and presents the results and findings from the baseline phase.

Xie, YuLong↗

Imputation for multisource data with comparison and assessment techniques

Missing data are prevalent issue in analyses involving data collection. The problem of missing data is exacerbated for multisource analysis, where data from multiple sensors are combined to arrive at a single conclusion. In this scenario, it is more likely to occur and can lead to discarding a large amount of data collected; however, the information from observed sensors can be leveraged to estimate those values not observed. We propose two methods for imputation of multisource data, both of which take advantage of potential correlation between data from different sensors, through ridge regression and a state-space model. These methods, as well as the common median imputation, are applied to data collected from a variety of sensors monitoring an experimental facility. Performance of imputation methods is compared with the mean absolute deviation; however, rather than using this metric to solely rank themethods,we also propose an approach to identify significant differences. Imputation techniqueswill also be assessed by their ability to produce appropriate confidence intervals, through coverage and length, around the imputed values. Finally, performance of imputed datasets is compared with a marginalized dataset through a weighted k-means clustering. In general, we found that imputation through a dynamic linearmodel tended to be the most accurate and to produce the most precise confidence intervals, and that imputing the missing values and down weighting them with respect to observed values in the analysis led to the most accurate performance.

97 MATHEMATICS AND COMPUTING↗

Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Big data has a potential to unlock novel groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry are discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.

13 HYDRO ENERGY↗

Overview of a Methodology for Calculating the A Priori Scan Minimum Detectable Concentration for Post-Processed Radiological Surveys (Final Report) (Rev.1)

Increased continuous data collection using automated data loggers and autonomous radiological survey devices or vehicles has introduced a need for corresponding guidance and statistical techniques for data that are collected without surveyor vigilance. This report presents a method for calculating the a priori scan minimum detectable concentrations (MDCs) for surveys performed without vigilance similar to methods described in the Multi-Agency Radiation Survey and Site Investigation Manual, NUREG-1507, and NUREG/CR-6364. A priori scan MDCs are calculated during survey planning to ensure that survey parameters (e.g., scanning speed, scanning altitude, detector geometry) will lead to collecting data in which potentially contaminated areas can be detected when data are processed after the survey, within acceptable statistical error probabilities.

54 ENVIRONMENTAL SCIENCES↗

Comparative evaluations of the geodetic accuracy and cartographic potential of Landsat-4 and Landsat-5 Thematic Mapper image data

A Landsat Image Data Quality Analysis (LIDQA) Program is conducted by NASA. One part of this program forms studies which are being performed with the objective to evaluate the geometric fidelity of Landsat-4 and Landsat-5 Thematic Mapper (TM) data in computer tape (CCT-pt) formats. It is pointed out that the Landsat-4 and Landsat-5 systems provide image data of significantly better geometric fidelity than were obtained from the earlier Landsat missions. Attention is given to the factors which influence the geometric fidelity of the Landsat TM data, the study areas and data sets, the rectification procedures, the rectification of Landsat-4 TM data and comparisons of the Scrounge and the TM Image Processing System (TIPS), the rectification of system and scene corrected Landsat-5 data processed on TIPS, and the cartographic potential of TM data.

Welch, R.↗

Space Network mission support in the Space Station era

The Mission Model for user support and NASA's plans to provide the necessary support resources are discussed. Particular attention is given to considerations which imply operation of up to two additional Tracking and Data Relay Satellites (TDRS), as well as potential interoperability with data relay satellite systems planned for launch in the mid-1990s by the ESA and by the NASDA of Japan. NASA activities related to the development of an Advanced TDRS system for the support of missions flying in the 21st century are also discussed.

Harris, David W.↗

Investigating the Impact of UV Radiation on High-Altitude Shallow Lake Habitats, Life Diversity, and Life Survival Strategies: Clues for Mars' Past Habitability Potential?

We present data and results from an ongoing project of astrobiological high-altitude expeditions investigating the highest and least explored perennial lakes on Earth in the Bolivian and Chilean Andes, including several volcanic crater lakes nearing and beyond 6,000 m in elevation. In the next five years, they will provide the first integrated long-term astrobiological characterization and monitoring of lacustrine environments and their biology for such altitude. These extreme lakes are natural laboratories. They provide the field data missing beyond 4,000 m to complete our understanding of terrestrial lakes and biota. Research on the effects of UV has been performed in lower altitude lakes and models of UV flux over time are being developed. Lakes showing a high content of dissolved organic material (DOM) shield organisms from UV. DOM acts as a natural sunscreen as it influences the water transparency, therefore is a determinant of photic zone depth. In sparsely vegetated alpine areas, lakes are clearer and offer less protection from UV to organisms living in the water. Transparent water and high UV irradiance may maximize the penetration and effect of UV radiation. Shallow-water communities in these lakes are particularly sensitive to UV radiation. The periphyton can live on various susbtrates. While on rocks, it includes immobile species that cannot seek low UV refuges unlike sediment-dwelling periphyton or alpine phytoflagellates which undergo vertical migration. Inhibition of algal photosynthesis by UV radiation has been documented in laboratory and showed that phytoplankton production is reduced by formation of nucleic acid lesions or production of peroxides and free oxygen radicals. of peroxides and free oxygen radicals. Our project is providing the field data that is missing from natural laboratories beyond 4,000 m and will complement the vision of the effects of UV on life and its adaptation modes (or lack thereof).

Cabrol, A.↗

Ka-Band Link Study and Analysis for a Mars Hybrid RF/Optical Software Defined Radio

The integrated radio and optical communications (iROC) project at the NASA Glenn Research Center (GRC) is investigating the feasibility of a hybrid RF and optical communication subsystem for future deep space missions. The hybrid communications subsystem enables the advancement of optical communications while simultaneously mitigating the risk of infusion by combining an experimental optical transmitter and telescope with a reliable Ka-band RF transmitter and antenna. The iROC communications subsystem seeks to maximize the total data return over the course of a potential 2-year mission in Mars orbit beginning in 2021. Although optical communication by itself offers potential for greater data return over RF, the reliable Ka-band link is also being designed for high data return capability in this hybrid system. A daily analysis of the RF link budget over the 2-year span is performed to optimize and provide detailed estimates of the RF data return. In particular, the bandwidth dependence of these data return estimates is analyzed for candidate waveforms. In this effort, a data return modeling tool was created to analyze candidate RF modulation and coding schemes with respect to their spectral efficiency, amplifier output power back-off, required digital to analog conversion (DAC) sampling rates, and support by ground receivers. A set of RF waveforms is recommended for use on the iROC platform.

communication↗

New ORNL Method Could Unleash Solar Power Potential

Measurement and data analysis techniques developed at the Department of Energy’s Oak Ridge National Laboratory could provide new insight into performance-robbing flaws in crystalline structures, ultimately improving the performance of solar cells.

14 SOLAR ENERGY↗

Working Group on Virtual Data Integration

This report is the outcome of a workshop commissioned by the U.S. Department of Energy’s (DOE) Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements foundational for achieving CESD scientific mission goals in advancing a robust, predictive understanding of Earth’s climate and environmental systems. Over the past several years, data volumes in CESD disciplines have risen sharply to unprecedented levels (tens of petabytes). Moreover, the complexity and diversity of this research data— including simulations, observations, and reanalysis— have grown significantly, posing new challenges for data capture, storage, verification, analysis, and integration. With the trends of increased data volume (in the hundreds of petabytes), more complex analysis processes, and growing cross-disciplinary collaborations, it is timely to investigate whether the CESD community has the computational and data support needed to fully realize the scientific potential of its data collections. In recognition of the challenges, a partnership is forming across CESD and among national and international agencies to examine the viability of creating an integrated, collaborative data infrastructure: a Virtual Laboratory. The overarching goal of this report is to identify the community’s key data technology requirements and high-priority development needs for sustaining and growing its scientific discovery potential. The report also aims to map these requirements to existing solutions and to identify gaps in current services, tools, and infrastructure that will need to be addressed in the short, medium, and long term to advance scientific progress.

54 ENVIRONMENTAL SCIENCES↗

Representation of the Geosynchronous Plasma Environment in Spacecraft Charging Calculations

Historically, our ability to predict and postdict spacecraft surface charging has been limited by the characterization of the plasma environment. One difficulty lies in the common practice of fitting the plasma data to a Maxwellian or Double Maxwellian distribution function, which may not represent the data well for charging purposes. We use electron and ion flux spectra measured by the Los Alamos National Laboratory (LANL) Magnetospheric Plasma Analyzer (MPA) to examine how the use of different spectral representations of the charged particle environment in computations of spacecraft potentials during magnetospheric substorms affects the accuracy of the results. We calculate the spacecraft potential using both the measured fluxes and several different fits to these fluxes. These measured fluxes have been corrected for the difference between the measured and calculated potential. The potential computed using the measured fluxes and the best available material properties of graphite carbon, with a secondary electron escape fraction of 81%, is within a factor of three of the measured potential for 87% of the data. Potentials calculated using a Kappa function fit to the incident electron flux distribution function and a Maxwellian function fit to the incident ion flux distribution function agree with measured potentials nearly as well as do potentials calculated using the measured fluxes. Alternative spectral representations gave less accurate estimates of potential. The use of all the components of the net flux, along with spacecraft specific average material properties, gives a better estimate of the spacecraft potential than the high energy flux alone.

Davis, V. A.↗

Estimating the National Carbon Abatement Potential of City Policies: A Data-Driven Approach

Cities are increasingly taking actions such as building code enforcement, urban planning, and public transit expansion to reduce emissions of carbon dioxide in their communities and municipal operations. However, many cities lack the quantitative information needed to estimate policy impacts and prioritize city actions in terms of carbon abatement potential and cost effectiveness. This report fills this research gap by providing methodologies to assess the carbon abatement potential of a variety of city actions. The methodologies are applied to an energy use data set of 23,458 cities compiled for the U.S. Department of Energy City Energy Profile tool. The analysis develops a national estimate of the carbon abatement potential of realizable city actions in six specific policy areas encompassing the most commonly implemented city actions. The results of this analysis suggest that, in aggregate, cities could reduce nationwide carbon emissions by about 210 million metric tons of carbon dioxide (MMT CO2) per year in a 'moderate abatement scenario' by 2035 and 480 MMT CO2/year in a 'high abatement scenario' by 2035 through these common actions typically within a city's control in the six policy areas. The aggregate carbon abatement potential of these specific areas equates to a reduction of 3%-7% relative to 2013 U.S. emissions. At the city level, the results suggest the average city could reduce carbon emissions by 7% (moderate) to 19% (high) relative to current city-level emissions. In the context of U.S. climate commitments under the 21st session of the Conference of the Parties (COP21), the estimated national abatement potential of the city actions analyzed in this report equates to about 15%-35% of the remaining carbon abatement necessary to achieve the U.S. COP21 target. Additional city actions outside the scope of this report, such as community choice aggregation (city-level purchasing of renewable energy), zero energy districts, and multi-level governance strategies, could significantly augment the carbon abatement contributions of city actions toward national climate targets. The results suggest that cities may play a pivotal role in progress toward national climate targets. In addition to providing carbon and emissions estimates, this report estimates the national net economic impacts of policies for which cost and benefit data are available. Impact metrics include employment, worker earnings, and gross domestic product (GDP). For the policy areas studied, the economic analysis demonstrates that city carbon abatement may be achieved with only minimal and generally slightly positive economic impacts. Employment impacts range from 0.04% to 0.13% of U.S, employment during implementation and zero to 0.1% thereafter. GDP estimates show net impacts of 0.02% to 0.07% of GDP during implementation and impacts from -0.02% to zero thereafter. This report quantitatively demonstrates the material impact of a limited set of local policy areas on national carbon abatement potential. The magnitude of estimated carbon reductions from city policies, 3%-7% of national emissions by 2035, suggests an important role for city-led actions in reaching U.S. climate goals. Multi-level governance at the city, state, and national levels could augment the carbon abatement potential of city actions and make cities a key component of long-term U.S. climate strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Resonance charge transfer, transport cross sections, and collision integrals for N(+)(3P)-N(4S0) and O(+)(4S0)-O(3P) interactions

N2(+) and O2(+) potential energy curves have been constructed by combining measured data with the results from electronic structure calculations. These potential curves have been employed to determine accurate charge exchange cross sections, transport cross sections, and collision integrals for ground state N(+)-N and O(+)-O interactions. The cross sections have been calculated from a semiclassical approximation to the scattering using a computer code that fits a spline curve through the discrete potential data and incorporates the proper long-range behavior of the interactions forces. The collision integrals are tabulated for a broad range of temperatures 250-100,000 K and are intended to reduce the uncertainty in the values of the transport properties of nonequilibrium air, particularly at high temperatures.

Stallcop, James R.↗

Front-of-Meter Model Results

These files contains aggregations of key variables from the NREL Distributed Wind Futures Study using full parcel level data. These variables describe total technical and economic potential for distributed wind turbine deployment. Aggregations are available at the (1) county, (2) zipcode (zip code tabulation area or zcta), and (3) US Census block group level. Each scenario is coded with the scenario name (e.g., baseline) and year (e.g., 2022). Those files postfixed with 'econpot' contain results for only those parcels that are economically viable while the files postfixed with 'techpot' include results for all parcels that are technically feasible. Hence these correspond to technoeconomic and technical potential respectively. The data are available as CSV or Geopackage. Columns in the files are as follows: * geoid: geographic identifier (FIPS code or similar) * min_techpot_sum_kw: technical potential for all parcels in kW using turbines downsized to demand when appropriate * max_techpot_sum_kw: technical potential for all parcels in kW without downsizing turbines * aep_sum_kwh: annual energy production estimate in kWh * cf_mean_ratio: mean capacity factor * lcoe_mean_cents_per_kwh: mean levelized cost of energy for parcels in geography in cents per kWh * lcoe_std_cents_per_kwh: standard deviation of the above * parcel_area_sum_acres: total area of viable parcels in acres * n_turbines: number of cited turbines (one per viable parcel currently) Note: These are preliminary results from the full-parcel 2024 update of the Distributed Wind Energy Futures study. Please take care when making use of the data, and feel free to contact the team with any questions. Full documentation in support of these data is in progress and will follow.

17 WIND ENERGY↗

Thermosyphon Cooler Hybrid System for Water Savings in an Energy-Efficient HPC Data Center: Results from 24 Months and the Impact on Water Usage Effectiveness

In August 2016, the National Renewable Energy Laboratory (NREL) installed a thermosyphon hybrid cooling system to reduce water usage in its already extremely energy-efficient High-Performance Computing (HPC) Data Center. In its first year of use, the system saved 4,400 m3 (1.16 million gal) of water, and 7,950 m3 (2.10 million gal) during a 2-year period, cutting the use of water in the data center by about one-half. NREL's 930-m2 (10,000-ft2) HPC Data Center is often called the most energy-efficient data center in the world: it has achieved a trailing 12-month average power usage effectiveness of 1.034, and it features a chiller-less design, component-level warm-water liquid cooling, and waste heat capture and reuse. NREL considered the amount of water used by the cooling towers to be counter to the laboratory's sustainability mission, so a team of researchers from NREL, Sandia National Laboratories (Sandia), and Johnson Controls integrated the BlueStream thermosyphon cooler (TSC) - an advanced dry cooler that uses refrigerant in a passive cycle to dissipate heat - on the roof of NREL's Energy Systems Integration Facility, the building that houses the HPC Data Center. In combination with the existing cooling towers, the TSC forms an extremely water- and cost-efficient cooling system. In its first year of operation, on-site water usage effectiveness (WUE) was 0.70 L/kWh. In comparison, the WUE would be 1.27 L/kWh if NREL had continued using only heat-recovery and cooling towers. This on-site water savings was accomplished without negatively impacting the energy-efficient operation of the HPC Data Center. The TSC system technology has the potential for application in data centers around the world, and it is currently being implemented by Sandia. center by about one-half. NREL's 930-m2 (10,000-ft2) HPC Data Center is often called the most energy-efficient data center in the world: it has achieved a trailing 12-month average power usage effectiveness of 1.034, and it features a chiller-less design, component-level warm-water liquid cooling, and waste heat capture and reuse. NREL considered the amount of water used by the cooling towers to be counter to the laboratory's sustainability mission, so a team of researchers from NREL, Sandia National Laboratories (Sandia), and Johnson Controls integrated the BlueStream thermosyphon cooler (TSC) - an advanced dry cooler that uses refrigerant in a passive cycle to dissipate heat - on the roof of NREL's Energy Systems Integration Facility, the building that houses the HPC Data Center. In combination with the existing cooling towers, the TSC forms an extremely water- and cost-efficient cooling system. In its first year of operation, on-site water usage effectiveness (WUE) was 0.70 L/kWh. In comparison, the WUE would be 1.27 L/kWh if NREL had continued using only heat-recovery and cooling towers. This on-site water savings was accomplished without negatively impacting the energy-efficient operation of the HPC Data Center. The TSC system technology has the potential for application in data centers around the world, and it is currently being implemented by Sandia.

97 MATHEMATICS AND COMPUTING↗