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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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The VOWCRIS project is an integrated systems approach to the feasibility-level design, performance, and cost-of-energy estimate for a notional 600-megawatt offshore wind project using site characteristics that apply to the Wind Energy Areas of Virginia, Maryland and North Carolina.
The fiscal year 2015 U.S. Department of Energy (DOE) Hydrogen and Fuel Cells Program Annual Merit Review and Peer Evaluation Meeting (AMR), in conjunction with DOE's Vehicle Technologies Office AMR, was held from June 8-12, 2015, in Arlington, Virginia. This report is a summary of comments by AMR peer reviewers about the hydrogen and fuel cell projects funded by DOE's Office of Energy Efficiency and Renewable Energy.
This fact sheet provides information about the Parkersburg, West Virginia, Disposal Site
Energy used by Virginia single-family homes that can be saved through cost-effective improvements. Prepared by Eric Wilson and Noel Merket, NREL, and Erin Boyd, U.S. Department of Energy Office of Energy Policy and Systems Analysis.
Energy used by West Virginia single-family homes that can be saved through cost-effective improvements. Prepared by Eric Wilson and Noel Merket, NREL, and Erin Boyd, U.S. Department of Energy Office of Energy Policy and Systems Analysis.
Fact sheet details public-private partnership efficiency impacts and local project examples in Virginia.
The fiscal year 2019 U.S. Department of Energy (DOE) Hydrogen and Fuel Cells Program Annual Merit Review and Peer Evaluation Meeting (AMR) was held from April 29 to May 1, 2019, in Arlington, Virginia. This report is a summary of comments by AMR peer reviewers about the hydrogen and fuel cell projects funded by DOE's Office of Energy Efficiency and Renewable Energy.
The Middle Devonian Marcellus shale play has emerged as a major world-class hydrocarbon accumulation and represents one of the largest and most prolific shale plays in the world. According to many outcrop studies in the region, natural fractures are well developed in the Marcellus Shale. However, evaluating fractures in the subsurface is often a significant challenge due to a lack of sufficient data. Therefore, in the Marcellus Shale Energy and Environment Laboratory (MSEEL) consortium project, significant efforts have been made to acquire high-quality image logs in the Marcellus laterals. The project provided tremendous opportunities to characterize the natural fractures and sub-seismic faults and to evaluate their impact on well stimulation. In this study, about 70,000 ft of acquired high-resolution logging while drilling (LWD) acoustic images from five long laterals located in Monongalia County, West Virginia, were processed and interpreted. In addition, the study used high-quality micro-resistivity images from a pilot well, allowing the evaluation of natural fractures in the entire Marcellus vertical sequence. Based on the available acoustic images, the natural fractures were classified into three basic categories: high-amplitude fractures, low-amplitude fractures, and faults. Further, larger open fractures can also be determined when a low-amplitude fracture is evident on caliper images. The fractures in the Marcellus usually have a medium to high angle dip; however, multiple fracture sets in terms of strike orientation were clearly observed in all the laterals. The fracture set with a strike at NE-SW (or 60-240 deg) seems to be the predominant one in all the wells. A few other sets, including those with N-S, NWW-SEE, and E-W strikes, were also observed. Several sub-seismic faults, with mostly a low dip angle and a NE-SW strike, have also been seen in two of the laterals. The fracture density is variable across all the laterals, ranging from very low (or none) to very high (up to 5 fractures per ft). The average fracture density for all the laterals is about 1 fracture per 10 ft. In the vertical sequence, the natural fracture development showed a clear preference for shale or shaly facies over carbonate-rich or thin limestone layers. The interpreted fracture and fault data were used as input data for the stimulation design with the purpose of better understanding the fractures’ impact on well stimulation. Production data from the laterals were also used to evaluate the natural fractures’ influence on well performance. The quality image database and the consistent interpretation results for the entire project enabled a systematic approach to characterizing fractures and, more importantly, to evaluating the impact of fractures on well stimulation and production.
Gamma-ray spectral data were collected from sensors mounted to traffic signals around Northern Virginia. The data were collected over a span of approximately fifteen months. A subset of the data were analyzed manually and subsequently used to train machine-learning models to facilitate the evaluation of the remaining 50k anomalous events identified in the dataset. We describe the analysis approach used here and discuss the results in terms of radioisotope classes and frequency patterns over day-of-week and time-of-day spans. Data from this work has been archived and is available for future and ongoing research applications.
According to the U.S. Census Bureau, Virginia had 5,629,718 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.
According to the U.S. Census Bureau, West Virginia had 1,129,785 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.
The National Energy Technology Laboratory (NETL) and West Virginia University Research Corporation (Participant) will collaborate on the testing of a 3D printed sparger in a temperature and pressure chamber, for the purpose of supporting the “American-Made Geothermal Prize” competition, designed to catalyze manufacturing innovation in the American geothermal industry by harnessing the rapid advances additive manufacturing can provide in improving design, fabrication, and functionality, which is accomplished through a series of prize competitions and the development of a diverse and powerful support network that leverages national laboratories, energy incubators, and other resources from across the United States. The intent is to connect competitor teams with national laboratories that can help accelerate the development of innovative solutions and products. Teams who have won the Set!, Go!, Make! Contests are eligible to utilize vouchers at national laboratories to advance their ideas.
Everyday citizens, emergency responders, and critical infrastructure can be dramatically affected by street flooding caused by the increasing tidal levels and major storm events magnified by climate change. Low-level flooding, such as nuisance flooding, continues to increase in frequency, especially in cities like Norfolk, Virginia, which can expect nearly 200 flooding events by 2050 [1]. Recently, machine learning (ML) models have been leveraged to produce real-time predictions based on local weather and geographic conditions. However, ML models are known to produce unusual results when presented with data that varies from their training set. For decision-makers to determine the trustworthiness of the model's predictions, ML models need to quantify their prediction uncertainty. This study applies Deep Quantile Regression (DQR) to a previously published, LSTM-based model for hourly water depth predictions [2], and analyzes its out-of-distribution (OOD) performance.
Recently hadron spectroscopy has seen a lot of success. There has been a large number of baryon and meson resonances discovered over the last two decades. There have also been several tetra and pentaquark candidates with experimental evidence but not confirmed. The first serious candidate was the X(3872), a potential tetraquark, leading to this rise in success for exotic hadron physics. This has brought about improvements in Quantum Chromo Dynamics (QCD), our current best description of interactions between quarks and gluons. QCD predicts the existence of hexaquark states, and then the d*(2380) was discovered. This thesis explores the rest of the d* Jp =3+ anti-decuplet by searching for experimental evidence of the ds hexaquark. This is the first analysis of the e'd ¿e'K+d0 s ¿e'K+¿n channel using the Py' measurements of the ¿ as a lens to perform this search. This observable was extracted from ¿ electroproduction events off a liquid deuterium target. From this an upper limit of the Breit-Wigner peak strength was extracted. This was done with the use of the CLAS12 detector system housed at Thomas Jefferson Laboratory in Virginia, USA. These polarization measurements are the first to be made on this data, and this is the first time the ds has been searched for in such a way.
Coal refuse disposal across Appalachia has resulted in widespread environmental degradation, including stream burial, landscape destabilization, and long-term hydrologic impacts. This study provides a GIS-based spatial characterization of 623 coal refuse sites in West Virginia, evaluating their potential for ecological and economic restoration. Stream loss was quantified through digitization of historic topographic maps, revealing over 194,500 meters of historically present streams lost, with 105,000 meters directly buried beneath refuse piles. Volume estimation using empirical Bayesian kriging and modern LiDAR surfaces indicated approximately 1.96 billion cubic meters of deposited refuse. Land cover analysis based on NAIP-derived classification showed that 48% of the total site area was forested, while 15% remained barren. These results highlight not only the environmental footprint of legacy refuse deposits but also their potential for restoration through stream daylighting and beneficial reuse. Emerging opportunities, including rare earth element recovery and mitigation banking, may offer economic incentives to facilitate reclamation. This work establishes a spatial framework to prioritize refuse sites for restoration, balancing ecological uplift with feasible material management strategies.
The Historically Black Colleges and Universities (HBCU) Solar Radiation Monitoring Network operated from July 1985 through December 1996. Funded by DOE, the six-station network provided 5-minute averaged measurements of direct normal, global, and diffuse horizontal solar irradiance. The data were processed at NREL to improve the assessment of the solar radiation resources in the southeastern United States. Historical HBCU data available online include quality assessed 5-min data, monthly reports, and plots. In January 1997 the HBCU sites became part of the CONFRRM solar monitoring network and data from the two remaining active stations, Bluefield State College and Elizabeth City State University, are collected by the NREL Measurement & Instrumentation Data Center (MIDC).
Since 1976, Industrial Assessment Centers (IACs) administered by the U.S. Department of Energy have supported small and medium-sized American manufacturers to reduce their energy use and improve their productivity and competitiveness. DOE is now offering up to 50 assessments per year at no cost to industrial or municipal water and wastewater plants.