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At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Assessing the Wind Energy Potential in Bangladesh: Enabling Wind Energy Development with Data Products

USAID Bangladesh and the U.S. Department of Energy’s National Renewable Energy Laboratory partnered with the Government of Bangladesh to develop a national wind resource assessment. The assessment used sophisticated resource modeling that was validated by a ground measurement campaign. Results from the project included a long-term, correlated wind data set; validated high-resolution wind resource maps; and publicly available data accessible through the RE Data Explorer (https://www.re-explorer.org/). The Renewable Energy (RE) Data Explorer allows users to access and download the Bangladesh wind resource assessment data and related geographic information system (GIS) data sets and perform customized technical potential analyses. Figure ES-1 is an example wind resource map for Bangladesh that can be created with the RE Data Explorer. This project improved upon existing global data sets by using best-in-class modeling techniques and analysis. Global models are good first steps in predicting wind resources in various parts of the world, but they do not generate the accuracy needed to reduce project risk and stimulate renewable investment. This project improved the quality of modeled wind resource data for Bangladesh. In addition to the modeling effort, the project team used a multi-year, local data-collection campaign to validate the model and further improve the accuracy of the data sets. The measurement campaign consisted of nine meteorological sites representing all geographical regions of the country. Seven meteorological towers and one remote-sensing, sonic detection and ranging unit (deployed at two sites) collected the data. Site-selection criteria focused on geographic diversity and proximity to existing transmission lines. Figure ES-1 shows measurement locations. The measurement campaign spanned June 2014 through December 2017. The results of the Bangladesh wind resource assessment will help Bangladesh overcome significant energy challenges. Its energy sector suffers from power shortages, increasing demand, decreasing domestic natural gas reserves, and inadequate transmission infrastructure. As part of a comprehensive plan to overcome these challenges, Bangladesh has committed that 10% of the total generation capacity will be renewable energy by 2021 (Power Division 2016). High-quality renewable energy resource data and other GIS data, such as those developed in this assessment, are important if Bangladesh wishes to reach its 10% renewable energy capacity target. These data support informed decision making, ranging from policy and investment decisions to reliable power sector planning. Specifically, the Bangladesh wind resource assessment will help reduce technical risk and encourage private-sector interest in the nascent wind market in Bangladesh. In addition, the Government of Bangladesh may use the results of the wind resource assessment to develop well-designed policies that could encourage investment in wind energy. This report provides a comprehensive description of the Bangladesh wind resource assessment, including details on the modeling approach and methods, instrumentation, data quality-control techniques, and resulting data sets.

17 WIND ENERGY↗

DOE OSTI2025

Remote Sensing and Fluxes Upscaling for Real-world Impact (Workshop Report)

The "Remote Sensing and Fluxes Upscaling for Real-world Impact" workshop, held on July 9-10, 2024, at Lawrence Berkeley National Lab, was a collaborative effort led by the AmeriFlux Management Project, NEON, and the Carbon Dew Community of Practice. The event brought together over 200 registrants and approximately 100 attendees each day, including leading experts, researchers, and practitioners. The primary focus was on bridging the gap between cutting-edge research and practical applications in environmental monitoring by integrating remote sensing and flux data. Key themes included the importance of site-level measurements for validating remote sensing products, providing nature-based climate solutions, and addressing challenges such as instrument costs and the need for standardized methods. At the regional scale, discussions centered on addressing spatial heterogeneity and using high-resolution remote sensing and machine learning methods to enhance data interpretation. Global scale challenges included data consistency, gap filling, and accurate emission source identification, with opportunities for international collaboration and standardized practices to improve global carbon budget assessments. The workshop emphasized the critical need for integrating data across local, regional, and global scales through explicit scale-matching and developed a workflow for scaling flux data using "straight shot" and "explicit nesting" approaches. The event highlighted the importance of connecting scientific research with real-world applications in carbon, energy, and water management, ensuring that advancements translate into tangible societal benefits. These insights will guide future research, technology transfer, and collaboration, maximizing the potential of environmental fluxes to address real-world challenges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Machine Learning-based False Data Injection Attack Detection and Localization in Power Grids

Cyberattacks on critical infrastructures can be catastrophic and bring nations to their knees. Therefore, detecting these attacks is crucial and challenging. This paper presents a novel approach for detecting and locating cyberattacks affecting an electrical power system. The adversary employs a man-in-the-middle technique to inject false data into the communication between distributed energy resources (DER) and Microgrid Controller (MGC) with the goal of disrupting power delivery. The approach for detection and localization is based on integrating multiple machine learning-based anomaly detection models that combine network traffic data and grid measurements. Experiments are performed to assess the method's performance using a hardware-in-the-loop real-time simulation testbed which includes Modbus TCP/IP communication. Power system topology and operating conditions are based on actual topology and real-world data provided by the Holy Cross Energy utility network. Results confirm that the method can be successfully employed for detecting and localizing cyberattacks.

Leao, Bruno P.↗

DOE OSTI2016

Novel Data Reduction Based on Statistical Similarity

Applications such as scientific simulations and power grid monitoring are generating so much data quickly that compression is essential to reduce storage requirement or transmission capacity. To achieve better compression, one is often willing to discard some repeated information. These lossy compression methods are primarily designed to minimize the Euclidean distance between the original data and the compressed data. But this measure of distance severely limits either reconstruction quality or compression performance. In this paper, we propose a new class of compression method by redefining the distance measure with a statistical concept known as exchangeability. This approach reduces the storage requirement and captures essential features, while reducing the storage requirement. In this paper, we report our design and implementation of such a compression method named IDEALEM. To demonstrate its effectiveness, we apply it on a set of power grid monitoring data, and show that it can reduce the volume of data much more than the best known compression method while maintaining the quality of the compressed data. Finally, in these tests, IDEALEM captures extraordinary events in the data, while its compression ratios can far exceed 100.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2001

Hiding the Disk and Network Latency of Out-of-Core Visualization

This paper describes an algorithm that improves the performance of application-controlled demand paging for out-of-core visualization by hiding the latency of reading data from both local disks or disks on remote servers. The performance improvements come from better overlapping the computation with the page reading process, and by performing multiple page reads in parallel. The paper includes measurements that show that the new multithreaded paging algorithm decreases the time needed to compute visualizations by one third when using one processor and reading data from local disk. The time needed when using one processor and reading data from remote disk decreased by two thirds. Visualization runs using data from remote disk actually ran faster than ones using data from local disk because the remote runs were able to make use of the remote server's high performance disk array.

Ellsworth, David↗

NASA NTRS2011

Downscaling NASA Climatological Data to Produce Detailed Climate Zone Maps

The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of downscaling NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.

Chandler, William S.↗

DOE OSTI2018

Local Infrasound Variability Related to In Situ Atmospheric Observation

Abstract Local infrasound is widely used to constrain source parameters of near‐surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3‐D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere‐dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

58 GEOSCIENCES↗

NASA NTRS1968

Internal low Reynolds number turbulent heat transfer

The results of a semi-analytical and experimental study of adiabatic tube flow and an analytical and experimental investigation of the thermal entrance region for gas flowing through electrically heated circular tubes are presented. Emphasis is placed on the low Reynolds number turbulent flow regime--defined as fully turbulent flow at bulk Reynolds numbers from 3,000 to about 15,000. Adiabatic air velocity and friction data and localized heat transfer measurements for air and helium, at low heating rates, are presented for this range. The adiabatic data were obtained in a 1.61 inch 1D tube for flow at bulk Reynolds numbers from 3,000 to 15,000. A continuous, Reynolds number-dependent, profile is developed from the data by using a modification of Reichardts' wall and middle law eddy diffusivity expressions. The velocity profile satisfies continuity. It is valid for all Reynolds numbers in excess of 3,000 for which the flow is fully turbulent and the Blasius friction factor expression is valid. The thermal entrance problem for a fully developed velocity profile is solved analytically by the method of Sparrow, Hallman, and Siegel. The solution is based on the profile developed from the velocity study. Tabular values of the eigenvalues and normalized Nusselt numbers for gases are presented for it range of Reynolds numbers from 3,000 to 50,000. The axial variation of Nusselt number is found to be correlated by [Nu/Nu_(∞)] = 1 + 0.8 (1+ 70,000 Re^(-3/2)) ((x/D)^(-1)) to within ± 5 per cent for x/D ≥2. The fully developed value agrees with the Dittus - Boelter correlation, Nu_(∞) = 0.021 Re^(0.8) Pr^(0.4) For the eigenvalues, λ^(2)_(n), and the associated constants, A_(n), correlations of the form λ^(2)_(n) =A_(1,n) Re^(-b_(1,n) + C_(1,n) Re^(-d_(1,n)) A_(n) = -A_(2,n) Re^(-b_(2,n) + C_(2,n) Re^(-d_(2,n)) are obtained. The coefficients and powers are presented in tabular form. Heat transfer data are presented, primarily for helium, for the low Reynolds number turbulent range. A one-quarter inch, resistively heated, vertical, circular tube was used for the study. The data cover an axial range from 1.2 to 96 diameters; wall-to-bulk temperature ratios vary from 1 to 1.4. In the low Reynolds number turbulent regime, these data clearly support the present analytical solution rather than the prediction obtained by applying the eddy diffusivity distribution used by Sparrow, Hallman, and Siegel.

Harold C. Reynolds, Jr.↗

NASA NTRS2004

Kernel PLS Estimation of Single-trial Event-related Potentials

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Rosipal, Roman↗

NASA NTRS2005

Comparing Goldstone Solar System Radar Earth-based Observations of Mars with Orbital Datasets

The Goldstone Solar System Radar (GSSR) has collected a self-consistent set of delay-Doppler near-nadir radar echo data from Mars since 1988. Prior to the Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) global topography for Mars, these radar data provided local elevation information, along with radar scattering information with global coverage. Two kinds of GSSR Mars delay-Doppler data exist: low 5 km x 150 km resolution and, more recently, high (5 to 10 km) spatial resolution. Radar data, and non-imaging delay-Doppler data in particular, requires significant data processing to extract elevation, reflectivity and roughness of the reflecting surface. Interpretation of these parameters, while limited by the complexities of electromagnetic scattering, provide information directly relevant to geophysical and geomorphic analyses of Mars. In this presentation we want to demonstrate how to compare GSSR delay-Doppler data to other Mars datasets, including some idiosyncracies of the radar data. Additional information is included in the original extended abstract.

Haldemann, A. F. C.↗

DOE OSTI2018

City Energy: From Data to Decisions. Rochester, New York: Reducing Energy Costs for Low-Income Households

The City of Rochester partnered with the Energy Department and the National Renewable Energy Laboratory (NREL) to demonstrate how data and analysis can inform more strategic energy decisions. NREL based its analysis in part on the State and Local Energy Data (SLED) website's City Energy Profiles (eere.energy.gov/sled). The profiles contain data compiled by SLED and the Cities Leading through Energy Analysis and Planning (Cities-LEAP) program. Cities across the country can follow the same approach and use data-driven analysis in their own energy planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1983

Large-scale, near-Earth, magnetic fields from external sources and the corresponding induced internal field

Data from MAGSAT analyzed as a function of the Dst index to determine the first degree/order spherical harmonic description of the near-Earth external field and its corresponding induced field. The analysis was done separately for data from dawn and dusk. The MAGSAT data was compared with POGO data. A local time variation of the external field persists even during very quiet magnetic conditions; both a diurnal and 8-hour period are present. A crude estimate of Sq current in the 45 deg geomagnetic latitude range is obtained for 1966 to 1970. The current strength, located in the ionosphere and induced in the Earth, is typical of earlier determinations from surface data, although its maximum is displaced in local time from previous results.

Langel, R. A.↗

NASA NTRS1985

Large-scale, near-field magnetic fields from external sources and the corresponding induced internal field

Data from Magsat analyzed as a function of the Dst index to determine the first degree/order spherical harmonic description of the near-earth external field and its corresponding induced field. The analysis was done separately for data from dawn and dusk. The Magsat data was compared with POGO data. A local time variation of the external field persists even during very quiet magnetic conditions; both a diurnal and 8-hour period are present. A crude estimate of Sq current in the 45 deg geomagnetic latitude range is obtained for 1966 to 1970. The current strength, located in the ionosphere and induced in the earth, is typical of earlier determinations from surface data, although its maximum is displaced in local time from previous results.

Langel, R. A.↗

DOE OSTI2016

America Saves! Energizing Main Street's Small Businesses

The America Saves! Energizing Main Street Small Businesses project engaged the 1,200-member National Main Street Center (NMSC) network of downtown organizations and other local, regional, and national partners to test a methodology for sharing customized energy efficiency information with owners of commercial buildings smaller than 50,000 square feet. Led by the National Trust for Historic Preservation’s Preservation Green Lab, the project marshalled local staff and volunteers to gather voluntarily-disclosed energy use information from participating businesses. This information was analyzed using a remote auditing tool (validated by the National Renewable Energy Lab) to assess energy savings opportunities and design retrofit strategies targeting seven building types (food service and sales, attached mixed-use, strip mall, retail, office, lodging, and schools). The original project design contemplated extensive leveraging of the Green Button protocol for sharing annualized utility data at a district scale. Due the lack of adoption of Green Button, the project partners developed customized approaches to data collection in each of twelve pilot communities. The project team encountered considerable challenges in gathering standardized annual utility data from local partners. After overcoming these issues, the data was uploaded to a data storehouse. Over 450 properties were benchmarked and the remote auditing tool was tested using full building profiles and utility records for more than 100 commercial properties in three of the pilot communities. The audit tool demonstrated potential for quickly capturing, analyzing, and communicating energy efficiency opportunities in small commercial buildings. However, the project team found that the unique physical characteristics and use patterns (partial vacancy, periodic intensive uses) of small commercial buildings required more trouble-shooting and data correction than was anticipated. In addition, the project revealed that remote technology alone (such as audits) is not sufficient to convince most owners of commercial buildings or businesses to invest in energy efficiency. Additional, one-on-one personal communication is critical. A combination of technology and well-planned direct contact is likely to produce the highest rate of energy efficiency implementation in the small commercial building market sector. Note that only two of the three planned phases of this project were completed. As a result, research and testing were not fully implemented and thus all results and conclusions from the America Saves! Energizing Main Street Small Businesses project should be considered preliminary. In addition to the National Main Street Center, local organizations, and regional utilities, the America Saves! project partners included the National Renewable Energy Laboratory, Energy Center of Wisconsin (Seventh Wave), Lend Lease, Building Energy, and Energy RM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1977

An operational, multistate, earth observation data management system

The purpose of this paper is to investigate a group of potential users of satellite remotely sensed data - state, local, and regional agencies involved in natural resources management. We assess this group's needs in five states and outline alternative data management systems to serve some of those needs. We conclude that an operational Earth Observation Data Management System (EODMS) will be of most use to these user agencies if it provides a full range of information services - from raw data acquisition to interpretation and dissemination of final information products.

Eastwood, L. F., Jr.↗

DOE OSTI2014

The R35 residue of the influenza A virus NS1 protein has minimal effects on nuclear localization but alters virus replication through disrupting protein dimerization

The influenza A virus NS1 protein has a nuclear localization sequence (NLS) in the amino terminal region. This NLS overlaps sequences that are important for RNA binding as well as protein dimerization. To assess the significance of the NS1 NLS on influenza virus replication, the NLS amino acids were individually mutated to alanines and recombinant viruses encoding these mutations were rescued. Viruses containing NS1 proteins with mutations at R37, R38 and K41 displayed minimal changes in replication or NS1 protein nuclear localization. Recombinant viruses encoding NS1 R35A were not recovered but viruses containing second site mutations at position D39 in addition to the R35A mutation were isolated. The mutations at position 39 were shown to partially restore NS1 protein dimerization but had minimal effects on nuclear localization. These data indicate that the amino acids in the NS1 NLS region play a more important role in protein dimerization compared to nuclear localization. - Highlights: • Mutations were introduced into influenza NS1 NLS1. • NS1 R37A, R38A, K41A viruses had minimal changes in replication and NS1 localization. • Viruses from NS1 R35A rescue all contained additional mutations at D39. • NS1 R35A D39X mutations recover dimerization lost in NS1 R35A mutations. • These results reaffirm the importance of dimerization for NS1 protein function.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

DFAT: A web-based toolkit for estimating demand flexibility in building-to-grid integration

Demand Flexibility Assessment Tool (DFAT) is an open source web-based tool that estimates the demand flexibility potential of common control strategies in commercial buildings. The toolkit features a demand flexibility estimation tool that contains two calculators, basic and advanced, based on the level of input of customer data. The basic version calculates demand shed metrics for the control strategy “global temperature adjustment” and “cycle on/off compressors” using customer building information, local weather data, and electrical meter data. The advanced version, which uses detailed HVAC equipment data, calculates demand flexibility metrics for control strategies such as static pressure reset, global temperature adjustment, and cycle on/off compressors. In addition to the demand flexibility estimation tool, this toolkit offers a benchmarking tool that helps facility operators, aggregators, and utility resource managers assess demand flexibility opportunities, quantify/verify performance, and compare their performance against that of their peers.

Leong, Michael↗

NASA NTRS1995

Finding the forest in the trees: The challenge of combining diverse environmental data

It has become increasingly important to conduct interdisciplinary environmental research assessments, both nationally and internationally. For this reason, the Committee for a Pilot Study on Database Interfaces was charged to review and advise on data interfacing activities. The committee used six case studies (1) to identify and understand the most important problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a very wide range of temporal scales; and (2) to elaborate the common barriers to interfacing data of disparate sources and types. Consistent with the committee's charge, the primary focus was the interfacing of geophysical and ecological data. The case studies used by the committee were: The Impact Assessment Project for Drought Early Warning in the Sahel, The National Acid Precipitation Assessment Program, The H.J. Andrew Experimental Forest Long-Term Ecological Research Site, The Carbon Dioxide Information Analysis Center, The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment, and The California Cooperative Oceanic Fisheries Investigation. The committee derived a number of lessons from the case studies, and these lessons are summarized at the end of each case study and analyzed in the last chapter. Some are generic in nature; others are more specific to a discipline or project. The conclusions and recommendations are based on the committee's analysis of the case studies and additional research. They are organized according to four major areas of barriers or challenges to the effective interfacing of diverse environmental data. In the final section the committee offers a set of broadly applicable principles (Ten Keys to Success) that can be used by scientists and data managers in planning and conducting interfacing activities.

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