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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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33 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

How deep is your soil? Quantifying and spatially analyzing understudied deep soil in the United States

Deep soil is largely understudied and important in understanding biogeochemical processes in soil. Here, understudied soil is defined as the difference between soil studied to a known depth and the estimated bedrock depth. To understand more about deep soil, the understudied soil in the US was quantified and spatially analyzed using soil survey data and model estimates of bedrock depth. An equation was derived to find understudied soil using the dataset parameters “max lower depth studied”, “depth to bedrock”, and “likelihood of bedrock in the top 200 cm”. The survey data and bedrock model revealed that soil has been studied to an average depth of 1-2 meters, and the average depth to bedrock is 20 meters. Soil data density in the soil surveys was greatest in the West Coast, Midwest, and areas historically managed for agricultural, while the non-contiguous US and interior West were underrepresented. The soil had been studied deeper than the estimated soil depth in 455 out of 56,889 observation points concentrated in Alaska, California, Texas, Florida, Puerto Rico, and the US Virgin Islands. To understand the diversity and any taxonomic bias of the global soil data available, soil order was compared to US-based National Resource Conservation Service percentages and it was found that Oxisols, Alfisols, Ultisols, Andisols, and Histosols were overrepresented while Gelisols, Aridisols, Vertisols, Entisols, and Spodosols are underrepresented. Soil depth is important in exploring the complexity of biogeochemical processes that take place in soil.

Bedrock↗
DOE OSTI2020

The "Perfect Storm" for Distributed Wind Markets

Close to 1 GW of distributed wind has been installed across all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Yet the number of installations varies greatly by state, even when wind resources are similar. This article examines three key factors that over the past thirteen years have shown to be enablers of success for distributed wind installations in the United States: 1) favorable policy environments, including consistent incentives, administrative support for cutting through red tape, and favorable interconnection, net metering, and permitting policies; 2) high electricity prices that would be displaced by wind energy generation, and, 3) favorable wind resources, enabling steady production of energy. Not all conditions need to be met simultaneously, yet of the studied markets for distributed wind in Iowa, New York, Washington, and Oregon, the most successful ones exhibit at least two out of the three conditions mentioned. We describe steps that policymakers, regulators, and market players have taken in the past to increase distributed wind installations in the United States.

Foster, Nikolas AF↗
DOE OSTI2023

A scalable wave resource assessment methodology: Application to U.S. waters

Waves deliver large quantities of energy to populated coastlines around the world, and wave energy technology research and development has accelerated over the last two decades. Throughout this time national and regional resource assessments have utilized disparate methodologies, which can cause confusion and skepticism. Here, in this work, we describe a theoretical wave resource assessment methodology that addresses many of the major areas of inconsistency and debate. Applying this revised methodology to U.S. waters, we find the theoretical U.S. wave energy resource to be 3300 TWh/yr, with region totals of 2000 TWh/yr in Alaska, 510 TWh/yr along the U.S. west coast, 380 TWh/yr in Hawaii, 290 TWh/yr along the east coast, 69 TWh/yr in the Gulf of Mexico, and 17 TWh/yr in Puerto Rico and the U.S. Virgin Islands. We also find significant uncertainty in these estimates associated with the underlying model dataset, which emphasizes the importance of thorough model validation and calibration as well as quantifying uncertainty.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Concurrent colonization of rodent kidneys with multiple species and serogroups of pathogenic Leptospira

ABSTRACT Rodents are important reservoir hosts of pathogenic leptospires in the US Virgin Islands. Our previous work determined that trapped rodents were colonized withLeptospira borgpeterseniiserogroup Ballum (n= 48) and/orLeptospira kirschneriserogroup Icterohaemorrhagiae (n= 3). In addition, nine rodents appeared to be colonized with a mixed population comprising more than one species/serogroup. The aim of this study was to validate this finding by characterizing clonal isolates derived from cultures of mixed species. Cultures of presumptive mixed species (designated LR1, LR5, LR37, LR57, LR60, LR61, LR68, LR70, and LR72) were propagated in different media including Hornsby-Alt-Nally (HAN) media, incubated at both 29℃ and 37℃, and T80/40/LH incubated at 29℃. Polyclonal reference antisera specific for serogroup Ballum and Icterohaemorrhagiae were used to enrich for different serogroups followed by subculture on agar plates. Individual colonies were then selected for genotyping and serotyping. Of the nine cultures of mixed species/serogroups, a single clonal isolate was separated in five of them:L. borgpeterseniiserogroup Ballum in LR1, LR5, and LR37, andL. kirschneriserogroup Icterohaemorrhagiae in LR60 and LR72. In four of the cultures with mixed species (LR57, LR61, LR68, and LR70), clonal isolates of bothL. borgpeterseniiserogroup Ballum andL. kirschneriserogroup Icterohaemorrhagiae were recovered. Our results definitively establish that rodents can be colonized with more than one species/serogroup ofLeptospiraconcurrently. The identification and characterization of multiple species/serogroups ofLeptospirafrom individual reservoir hosts of infection are essential to understand the epidemiology and transmission of disease to both human and domestic animal populations. IMPORTANCE PathogenicLeptospira, the causative agent of human and animal leptospirosis, comprise a diverse genus of species/serogroups which are inherently difficult to isolate from mammalian hosts due to fastidious growth requirements. Molecular evidence has indicated that reservoir hosts ofLeptospiramay shed multiple species concurrently. However, evidence of this phenomena by culture has been lacking. Culture is definitive and is essential for comprehensive characterization of recovered isolates by high-resolution genome sequencing and serotyping. In this work, a protocol using recently developed novel media formulations, in conjunction with reference antisera, was developed and validated to demonstrate the recovery of multiple species/serogroups of pathogenicLeptospirafrom the same host. The identification and characterization of multiple species/serogroups ofLeptospirafrom individual reservoir hosts of infection are essential to understand the epidemiology and transmission of disease to both human and domestic animal populations.

Biotechnology & Applied Microbiology↗
DOE OSTI2021

County Economic Impact Index: Measuring the ongoing economic effects of COVID-19

The County Economic Impact Index (CEII) estimates the change in overall county-level economic activity during the COVID-19 pandemic relative to January 2020. It shows which counties may be more susceptible to large reductions in economic activity compared to normal conditions by looking at which industries make up each county’s economy and then tracking monthly changes in industry employment at the national level. Economic activity in the CEII is measured by the total value added of all industries within the county. Counties with economic activities dominated by industries experiencing rising unemployment can expect larger direct impacts to their local economies, particularly if the industries account for a large portion of the economic output of that county. Results are available for all U.S. counties, as well as the District of Columbia, Puerto Rico municipios, and the U.S. Virgin Islands.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

SolSmart Technical Assistance Provider (Final Technical Report)

The SolSmart program was established in late 2015 to “establish a prominent national recognition and technical assistance program for local governments that will signal to installers and the public that a community is receptive to solar businesses and has established a supportive solar market environment. This, in turn, will reduce market barriers and lower soft costs, thus contributing to SunShot goals. The program will also assist communities who are just beginning to improve their solar markets.” By March 31, 2022 (the grant end date), the SolSmart Team designated 460 communities, more than 50% more than the initial program objective of 300 communities. The designated communities represent 42 states, the District of Columbia, the U.S. Virgin Islands, and Puerto Rico. The SolSmart team developed and revised criteria representing best practices for local governments; recruited, trained, evaluated, and mentored communities to incorporate these best practices; and disseminated resources about solar and solar-related technologies as well as the newest best practices on a regular basis. 98% of local government officials who participated in the program said that SolSmart increased their knowledge of solar energy. The SolSmart program had both real and perceived tangible impacts on barriers to solar adoption in designated communities. Significantly, the time to permit a solar installation decreased by 7.5 days on average. This reduced the soft costs for both the solar installer (and therefore the customer) and the local government. The result is that solar installations in SolSmart communities increased by 17% per month compared with similar non-SolSmart communities. Larger and wealthier communities were more likely to pursue SolSmart designation and earn more points within SolSmart. As a result, IREC/TSF developed strategies to reach underserved communities and created new resources to help them more easily achieve designation, as described below. In the last year of the Award, 44% of designated communities were underserved, compared with 31% in the earlier years of the program. DOE issued two awards for SolSmart: the SolSmart Technical Assistance Provider (TAP), led by The Solar Foundation (TSF) which has since merged with the Interstate Renewable Energy Council (IREC), and the Designation Program Administrator (DPA), led by the International City/County Management Association (ICMA). IREC was lead for the TAP project and, until the time of TSF/IREC merger, was a subrecipient on the DPA project. These two projects were interdependent; one could not exist without the other. While this report will focus on the work performed by the TAP, it will be impossible to speak of this without talking about the successes, impacts, and benefits of the overall SolSmart program.

14 SOLAR ENERGY↗
DOE OSTI2022

High-Resolution Wind Resource Data Set of the Greater Puerto Rico Region

In February 2022, the U.S. Department of Energy and six national laboratories launched the Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100). PR100 aims to provide a comprehensive analysis of possible pathways for Puerto Rico's energy future, with a goal of 100% renewable energy by 2050. As a part of the renewable energy potential assessment in this project, we developed 20 years (2001-2020) of data using a numerical weather prediction (NWP) model for onshore and offshore wind resource assessment for the Puerto Rico. The research steps in developing the long-term wind resource data sets based on the NWP model were: 1. Model wind resource based on the Weather Research and Forecasting (WRF) model. 2. Develop WRF model configurations for Puerto Rico. 3. Test WRF with 11 different physics parameterizations for planetary boundary layer (PBL). 4. Assess WRF output from the different PBL schemes against observations. 5. Select a final model configuration which can produce the modeled wind speed with sufficient accuracy. 6. Produce 20 years wind resource data sets for Puerto Rico region. In the first stage of our framework for developing wind resource data, we developed a WRF model configuration using two nested domains (9 km and 3 km) to cover Puerto Rico and U.S. Virgin Islands and downscale the ERA5 reanalysis data (0.25 degrees x 0.25 degrees; hourly interval) to a 3-km domain. For the second stage, we implemented one-year simulations focused on using 11 different PBL physics parameterizations to find a combination of WRF physics parameterizations that could provide accurately modeled wind speed for Puerto Rico. We also analyzed the sensitivity of the modeled wind speed to PBL schemes for onshore and offshore locations. The WRF output resulting from the 11 WRF experiments using different PBL parameterizations were evaluated against observations obtained from the National Data Buoy Center (NDBC) as well as at hub height for a location for which measurements were available. A final model setup selected through the validation with observational data was used to produce 20 years of data with 3-km spatial and 5-minute temporal resolution. The WRF model output was post-processed to include wind profiles and basic atmospheric variables in a format that can be easily used for downstream modeling. The 20 years of wind resource data will be made available through NREL and support the estimation of wind energy development costs for the PR100 study.

17 WIND ENERGY↗
DOE OSTI2023

Toward Solar Photovoltaic Storm Resilience: Learning from Hurricane Loss and Rebuilding Better

The General Service Administration (GSA) suffered extensive damage to its solar arrays located throughout the Caribbean from Hurricanes Irma and Maria in 2017. While the damage that occurred was unfortunate, there are excellent lessons learned that can be gained and utilized on new systems. A site on St. Croix provides a particularly high-value opportunity for lessons learned due to the innovative rebuilding process utilized by GSA managers and the in-depth analysis performed by the project engineers. This case study focuses on the rebuild of a 469-kW ground array located at the Almeric L. Christian Federal Building in Christiansted, St. Croix in the U.S. Virgin Islands. This array was destroyed by Hurricane Maria. The entire process of planning and subsequent rebuilding that the GSA managers undertook was highly successful. Notably, GSA managers conducting the rebuild effort obtained an independent assessment of failure modes from U.S. Department of Energy (DOE) national labs and then retained a consulting engineering firm to develop design and construction guidance for the rebuild effort. This design and construction guidance was then provided to the engineering, procurement, and constructing firm to implement while rebuilding the site.

14 SOLAR ENERGY↗
DOE OSTI2023

Toward Solar Photovoltaic Storm Resilience: Learning from Hurricane Loss and Rebuilding Better

This case study report focuses on the rebuild of a 469 kW ground array located at the Almeric L. Christian Federal Building in Christiansted, St. Croix, in the U.S. Virgin Islands. The General Service Administration (GSA) suffered extensive damage to its solar arrays located throughout the Caribbean from Hurricanes Irma and Maria in 2017. While the damage that occurred was unfortunate, there are excellent lessons learned that can be gained and utilized on new systems. The St. Croix site provides a particularly high-value opportunity for lessons learned due to the innovative rebuilding process utilized by GSA managers and the in-depth analysis performed by the project engineers.

14 SOLAR ENERGY↗
DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) - Deliverable Task 7: Risk Assessment

The “Optimizing Alabama’s CO 2 Storage in Shelby County: Project OASIS” CarbonSAFE Phase II Project seeks to build on regional data sets that demonstrate that the subsurface within Shelby County, Alabama has the potential to store commercial volumes of CO 2 safely, permanently, and economically. The primary target CO 2 Storage Complex is the deep Ketona Dolomite located within a 140 square mile area of the Valley and Ridge Region of Alabama. This deep saline reservoir is beneath a confining system encompassing at least 6,500 ft of shales and other low permeability sediments. Project OASIS drilled a deep stratigraphic test well to confirm the geological properties of the confining system and storage reservoir(s) within the Storage Complex. The geological data was incorporated into numerical models to establish the areal extent of the CO 2 plume and help design the storage site and its monitoring system. The project is managed by the Southern States Energy Board (SSEB), an interstate compact organization consisting of governors and state legislative leaders from sixteen southern states, Puerto Rico, and the U.S. Virgin Islands, as well as an appointee by the President of the United States. The organizational compact provides it with access to state government organizations and legislatures. The Board also maintains an Associate Members program comprised of energy resource companies, utilities, trade groups, academic R&D science and technology experts and energy consultants. Further, the SSEB staff is experienced in managing and coordinating complex energy and environmental programs, from research programs to full-scale design and demonstrations of new and innovative technologies. Project OASIS is a public-private partnership of six entities with multiple principal investigators (PIs). SSEB’s Lead PI and Co-PI are responsible for all aspects of project performance in accordance with the DOE-NETL Cooperative Agreement. SSEB has issued subgrants to Advanced Resources International, Inc., Alabama A&M University, Auburn University, Crescent Resource Innovation, and Oklahoma State University. Advanced Resources International, Inc., issued subgrants to Baker Hughes and Loudon Technical Services for field services

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Satellite Imagery of PV Site Storm Damage

"This repository contains multiple data sets focused on visible damage to photovoltaic (PV) installations following extreme weather events such as hailstorms and hurricanes. Data sets are split into two categories: the first category, the ‘manually labeled’ data, was compiled by researchers manually, and contains manually identified PV sites exposed to storms. The second data set, the ‘aggregated’ data, is a compilation of the manually labeled PV sites and deep learning-identified PV sites. The hail damage data set focuses on post-storm PV damage following a September 24, 2023 hailstorm in Austin, TX, which caused over $600 million in damages in the Austin metro area. The hurricane damage data set focuses on post-storm PV damage following Hurricanes Irma and Maria in Puerto Rico and the US Virgin Islands. Hurricanes Irma and Maria were back-to-back category 5 hurricanes, which pummeled the Caribbean and southeastern United States in September 2017, causing an estimated $115.2 billion in damages."

14 SOLAR ENERGY↗
DOE OSTI2020

Energy Snapshot – Puerto Rico

This profile provides a snapshot of the energy landscape of the Commonwealth of Puerto Rico - a U.S. territory located about 60 miles east of the Dominican Republic and directly west of the U.S. Virgin Islands.

44 EE - Strategic Programs, Energy Transition Init↗
DOE OSTI2021

Territorial Government Revenue Vulnerability Index (TGRVI): Measuring Financial Impacts to Territorial Governments during the COVID-19 Pandemic

The Territorial Government Revenue Vulnerability Index (TGRVI) measures the vulnerability of U.S. territorial government revenues by estimating monthly changes relative to a January 2020 baseline. Revenues accounted for in the index include: taxes on products and sales, transportation and housing revenues, individual income taxes, severance taxes and royalties, and property taxes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

A framework for feasibility-level validation of high-resolution wave hindcast models

The value of long-term wave hindcasts for investigating wave climates, wave energy resources, and extreme wave conditions has motivated research developing, calibrating and validating wave hindcast models. Past hindcast model validation studies examined the accuracy in modeling bulk wave parameters of overall sea states without considering the dependency of the model's skill within different sea states. In the present study, a framework for wave hindcast model validation is developed by examining the model accuracy for the most frequently occurring sea states, sea states contributing the most energy to total wave power, sea states associated with hurricane events, and those with the largest model error. Here, validations using bulk wave parameters and frequency-directional spectra at these key sea states and extreme wave conditions based on univariate and bivariate-contour methods provide insights to improve model accuracy, identifying the model's strong and weak points, and pathways for improvement, e.g., modeling wave-current interactions and adjusting wind data. This study adds to a growing body of research demonstrating that a carefully calibrated and verified spectral wave hindcast model can be used to estimate key wave energy parameters over a wide range of wave energy climates, as well as their spatial, temporal, frequency, directional, and probabilistic distributions.

54 ENVIRONMENTAL SCIENCES↗