Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “US”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Year-long buoy-based observations of the air–sea transition zone off the US west coast

Abstract. Two buoys equipped with Doppler lidars owned by the US Department of Energy (DOE) were deployed off the coast of California in autumn of 2020 by Pacific Northwest National Laboratory. The buoys collected data for an entire annual cycle at two offshore locations proposed for offshore wind development by the Bureau of Ocean Energy Management. One of the buoys was deployed approximately 50 km off the coast near Morro Bay in central California in 1100 m of water. The second buoy was deployed approximately 40 km off Humboldt County in northern California in 625 m of water. The buoys provided the first-ever continuous measurements of the air–sea transition zone off the coast of California. The atmospheric and oceanographic characteristics of the area and estimates of annual energy production at both the Morro Bay and Humboldt wind energy areas show that both locations have a high wind energy yield and are prime locations for future floating offshore wind turbines. This article provides a description and comprehensive analysis of the data collected by the buoys, and a final post-processed dataset is uploaded to a data archive maintained by the DOE. Additional analysis was conducted to show the value of the data collected by the DOE buoys. All post-processed data from this study are available on the Wind Data Hub website: https://a2e.energy.gov/data# (last access: 14 September 2023). Near-surface, wave, current, and cloud datasets for Humboldt and Morro Bay are provided at https://doi.org/10.21947/1783807 (Krishnamurthy and Sheridan, 2023b) and https://doi.org/10.21947/1959715 (Krishnamurthy and Sheridan, 2023a), respectively. Lidar datasets for Humboldt and Morro Bay are provided at https://doi.org/10.21947/1783809 (Krishnamurthy and Sheridan, 2023d) and https://doi.org/10.21947/1959721 (Krishnamurthy and Sheridan, 2023c), respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Transformation rate maps of dissolved organic carbon in the contiguous US

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (P r ), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution P r maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the P r values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of P r with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of P r based on the ML model. For evaluation, we compare the DOC concentration derived using the P r map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of P r to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two P r maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US

Abstract. Intensified extreme precipitation and corresponding floods are the most relevant consequences of climate change over the northeastern US (NEUS). To evaluate the impacts of climate change or certain climate perturbations on future extreme weather events which are dynamically similar to historic analogs, the pseudo-global warming (PGW) method has been frequently employed; however, this method lacks precise definition and guidelines, thus limiting its application. More specifically, three key questions related to the application of the PGW method remain unanswered: at what spatial scale should climate perturbations be applied? Among the different meteorological variables available, which ones should be perturbed? And will PGW projections vary significantly when different perturbations are applied? To address these questions, we examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments with varied perturbation spatial scales and choice of perturbed meteorological variables. The results show that the projections of precipitation and other essential variables at the regional mean scale are consistent across the PGW simulations, with a relative difference of much less than 10 %; however, different perturbation modifications can cause significant displacements of the storm events being simulated. Several previously assumed advantages of modifying only the temperature at regional mean scale, such as the preservation of geostrophic balance, do not appear to hold. Also, for these experiments, we find the regional mean perturbation produces a positive precipitation bias because it ignores the land–ocean warming contrast, which is a robust regional response to global warming. Overall, PGW experiments with perturbations from temperature or the combination of temperature and wind at the grid point scale are both recommended, depending on the research questions. The first approach can isolate the spatially dependent thermodynamic impact, and the latter incorporates both the thermodynamic and dynamic impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Observations of extreme wave runup events on the US Pacific Northwest coast

Extreme, tsunami-like wave runup events in the absence of earthquakes or landslides have been attributed to trapped waves over shallow bathymetry, long waves created by atmospheric disturbances, and long waves generated by abrupt breaking. These runup events are associated with inland excursions of hundreds of meters and periods of minutes. While the theory of radiation stress implies that nearshore energy transfer from the carrier waves to the infragravity waves can also lead to very large runup, there have not been observations of runup events induced by this process with magnitudes and periods comparable to the other three mechanisms. This work presents observations of several runup events in the US Pacific Northwest that are comparable to extreme runup events related to the other three mechanisms. It also discusses possible generation mechanisms and shows that energy transfer from carrier waves to bound infragravity waves is a plausible generation mechanism. In addition, a method to predict and forecast extreme runup events with similar characteristics is presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗
DOE OSTI2021

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. Such understanding has been hindered by a lack of publicly available wind profile observations in offshore wind energy areas. However, the New York State Energy Research and Development Authority recently funded the deployment of two floating lidars within two current lease areas off the coast of New Jersey. These floating lidars provide publicly available wind speed data from 20 to 200 m height with a 20 m vertical resolution. In this study, we leverage a year of these lidar data to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. In designing a detection algorithm for these events, we find that the typical, non-dimensional power-law-based wind shear exponent is insufficient to identify many of these extreme, high-wind-speed events. Rather, we find that the simple vertical gradient of wind speed better captures the events. Based on this detection method, we find that almost 100 independent events occur throughout the year with mean wind speed at 100 m height and wind speed gradient of 16 m s -1 and 0.05 s -1 , respectively. The events have strong seasonal variability, with the highest number of events in summer and the lowest in winter. A detailed analysis reveals that these events are enabled by an induced stable stratification when warmer air from the south flows over the colder mid-Atlantic waters, leading to a positive air–sea temperature difference.

17 WIND ENERGY↗
DOE OSTI2023

Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast

Uncertainty quantification of long-term modeled wind speed is essential to ensure stakeholders can best leverage wind resource numerical data sets. Offshore, this need is even stronger given the limited availability of observations of wind speed at heights relevant for wind energy purposes and the resulting heavier relative weight of numerical data sets for wind energy planning and operational projects. In this analysis, we consider the National Renewable Energy Laboratory's 21-year updated numerical offshore data set for the US East Coast and provide a methodological framework to leverage both floating lidar and near-surface buoy observations in the region to quantify uncertainty in the modeled hub-height wind resource. We first show how using a numerical ensemble to quantify the uncertainty in modeled wind speed is insufficient to fully capture the model deviation from real-world observations. Next, we train and validate a random forest to vertically extrapolate near-surface wind speed to hub height using the available short-term lidar data sets in the region. We then apply this model to vertically extrapolate the long-term near-surface buoy wind speed observations to hub height so that they can be directly compared to the long-term numerical data set. We find that the mean 21-year uncertainty in 140 m hourly average wind speed is slightly lower than 3 m s -1 (roughly 30m% of the mean observed wind speed) across the considered region. Atmospheric stability is strictly connected to the modeled wind speed uncertainty, with stable conditions associated with an uncertainty which is, on average, about 20 % larger than the overall mean uncertainty.

17 WIND ENERGY↗
DOE OSTI2024

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

17 WIND ENERGY↗
DOE OSTI2025

Code associated with "Assessing the Effect of a Deep-Rooted Grass on Belowground Carbon Storage in Cultivated Land: Insights from a Multi-Site US Study"

R code associated with "Assessing the Effect of a Deep-Rooted Grass on Belowground Carbon Storage in Cultivated Land: Insights from a Multi-Site US Study" These scripts can be used to analyze the accompanying dataset: https://doi.org/10.5281/zenodo.16620529. (1) resampling_functions.R : Creates functions for resampling data for nonparametric bootstrapping (2) bootstrap_depth_profiles.R : Applies resampling functions to the dataset (3) gapfill_masscalcs.R : Prepares data for equivalent mass calculations (4) get_14C_EM.R : Applies soilR to obtain the 14C end member for mixing model calculations (5) mass_aggregate.R : Performs equivalent mass and mass weighted averaging calculations.

Carbon↗
DOE OSTI2021

Material flows and GHG emissions from housing stock evolution in US counties, 2020–60

The evolution of housing stocks determines demand for construction materials and energy, and associated emissions of greenhouse gasses (GHGs). The contribution of construction to building life-cycle emissions is growing as buildings become more energy efficient and the energy supply decarbonizes. A housing stock model is developed for counties in the United States using dynamic vacancy rates which endogenously influence stock out- and inflows. Stocks of three house types and 10 construction cohorts are projected for all contiguous US counties for the period 2020–60. Inflows and outflows of construction materials are then estimated along with GHG emissions associated with material production and construction activities in scenarios defined by stock turnover rates, population share by house type, and floor area characteristics of new houses. The results provide new insights into the drivers of construction-related emissions at local and national levels, and identify opportunities for their reduction. Demolition material flows grow in relation to construction material flows over the analysis period. Increasing the stock turnover rate increases future floor area per person, material requirements, and emissions from construction. Scenarios with reduced floor area and more multifamily homes in new construction have lower floor area growth, material requirements, and emissions from construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Power Density Waterfalls Plots for AGR-1, AGR-2 US UCO, and AGR-5/6/7 Experiments

Task: Generate plots of the distribution of power per particle per power bin over time. Kairos needs these for licensing purposes. Basically, they need to know which power/particle was sustained by which fraction of the fuel and for how long. The idea is to leverage AGR results. However, Kairos wants to operate at relatively high power/particle and, therefore, they need to check how much of their range is covered by AGR. These plots are made for AGR-1, AGR-2 US UCO, and what is predicted for AGR-5/6 and AGR-7 (for which there are no daily as-run values but projected values for every cycle). The predicted AGR-5/6/7 data was provided by the attached Excel file in an Email by Blaise Collin to Cam Binh Pham on May 21, 2018.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Future Collider Options for the US

The United States has a rich history in high energy particle accelerators and colliders -- both lepton and hadron machines, which have enabled several major discoveries in elementary particle physics. To ensure continued progress in the field, U.S. leadership as a key partner in building next generation collider facilities abroad is essential; also critically important is the exploring of options to host a future collider in the U.S. The "Snowmass" study and the subsequent Particle Physics Project Prioritization Panel (P5) process provide the timely opportunity to develop strategies for both. What we do now will shape the future of our field and whether the U.S. will remain a world leader in these areas. In this white paper, we briefly discuss the US engagement in proposed collider projects abroad and describe future collider options for the U.S. We also call for initiating an integrated R&D program for future colliders.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Concentration and Recovery of Rare Earth Elements from Eastern US Coal Refuse

Recent studies funded by the US Department of energy have shown that coal and coal byproducts contain elevated contents of Rare Earth Elements (REEs), making them a potential resource for these critical materials. The approach employed in this research focused on the concentration and extraction of REEs from fine coal refuse derived from various preparation plants in the Appalachian coal basin of the United States. Initial efforts in this research focused on the identification and characterization of REEs in various fine coal refuse streams from nine distinct industrial preparation plants in Appalachia. The average REE content in these materials was determined to be approximately 200 ppm, but the REE content showed a strong correlation to the aluminum content, suggesting that the REEs are closely associated with the clay minerals present in the refuse. Given the relatively low REE concentrations, initial efforts sought to concentrate the REEs through decarbonization and dispersive liberation steps. In these tests, high-shear agitation in the presence of a polyelectrolyte, followed by sedimentation was able to isolate the REE-enriched fine clay particles from siliceous gangue minerals. Following the dispersive liberation step, all samples were found to have an REE content greater than 300 ppm, a benchmark used for many initial exploratory studies. In one case, the REE content was increased by more than 125%. Subsequent extraction tests initially utilized a direct ion-exchange leaching approach with ammonium sulfate as lixiviant. In all cases, the simple ion-exchange leaching process failed to recover significant quantities of rare earth elements, ultimately suggesting that the REEs in fine coal waste may be passivated or bound in a colloidal phase. To access this colloidal phase, several alternative approaches were evaluated, including leaching with alternative ion-exchange lixiviants, reductive leaching, gas-purged leaching, and others. The approach that showed the most promise was strong alkaline pretreatment, followed by ion-exchange leaching with ammonium sulfate at pH 4. A combination of strong alkali and high-temperatures treatment successfully liberated the REEs, converting them to a form amenable to ion-exchange leaching. The highest REE recovery achieved with this method was determined to be 39%. Lastly, bench-scale solvent extraction tests were used to further concentrate REEs in the leach solution and demonstrate that mixed rare earth concentrates can be successfully produced from fine coal refuse.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Understanding Low Level Jets in the US Atlantic Offshore

Low level jets (LLJs) in the atmosphere exhibit a local windspeed maximum in the boundary layer, with positive shear beneath the jet and negative shear above the jet. Wind turbines tend to experience increased loads with varying wake recovery characteristics in the presence of an LLJ, therefore understanding the mechanism and impact of LLJs is crucial to wind energy development. The US Mid-Atlantic offshore region is a huge potential wind energy resource, yet LLJs in this area are poorly understood. In particular, the coastal offshore environment does not exhibit the same diurnal cycle that leads to strong LLJs in the well-characterized Great Plains region. In this study, we use the Weather Research and Forecasting model (WRF) plus lidar buoy data to identify case studies for LLJ events in 2020 in the New York Bight. A reduced order model is presented to explain the onset of these events based on the competing effects of baroclinicity and eddy diffusivity. Finally, using the macro-scale WRF, we drive a micro-scale large eddy simulation (LES) to generate a more detailed characterization of the Marine Boundary Layer during an LLJ. Gaining a better understanding of LLJs and their impacts on offshore wind in the mid-Atlantic is crucial for a transition toward renewable energy.

atmospheric boundary layer↗
DOE OSTI2022

Contentious narratives and disinformation about nuclear weapons in strategic deterrence and competition: A SOCOM perspective. Part of Section: United States Special Operations Command (USSOCOM) in Emerging Strategic & Geopolitical Challenges: Operational Implications for US Combatant Commands

Russia’s “special military operation” in Ukraine demonstrates the challenge for strategic deterrence and competition of countering contentious narratives and disinformation about weapons of mass destruction (WMD) during conventional regional wars against a nucleararmed adversary. Moscow uses both tailored, contentious narratives and targeted disinformation about WMD in Ukraine to influence and disrupt local and global perceptions in support of its deterrence and competition objectives vis-à-vis the United States and NATO. Since December 2021, Moscow has made a focal point of chemical, biological, radiological, and nuclear weapons in its efforts to establish a permissive environment for its military buildup on the border with Ukraine and then its military intervention. These information tactics also demonstrate an opportunity for US Special Operations Forces (SOF). They are a case study for considering how SOF can contribute to strategic deterrence and competition objectives, specifically countering adversary gray-zone information efforts to alter regional security orders.1 Such a role is in line with the 2022 Special Operations Forces Vision and Strategy, which provides a framework for the evolution of SOF into “a force capable of creating strategic, asymmetric advantages for the nation as a key contributor of integrated deterrence” (United States Special Operations Command, 2022). This paper briefly examines this strategic challenge and SOF opportunity, focusing narrowly on the distinction between contentious narratives and disinformation about nuclear weapons and the role of SOF in countering these gray-zone information tactics. The nuclear dimension of Moscow’s contentious narratives and disinformation in the “special military operation” is of particular interest because it demonstrates the distinction between strategic efforts to influence and disrupt local and global perceptions in Moscow’s favor. This distinction between influence and disruption is less clear with Russia’s contentious narratives and disinformation about chemical and biological weapons in Ukraine, as disinformation about these two types of WMD appears to overwhelm contentious narratives. We believe this distinction is useful for policymakers and warfighters responsible for countering gray-zone information tactics because it provides a framework for crafting tailored responses to contentious narratives and disinformation about nuclear weapons and other WMD. The chapter concludes with a discussion of efforts that could be undertaken by SOF in cooperation with other relevant stakeholders to address this aspect of adversary gray-zone information tactics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗