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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Observations of Offshore Low‐Level Jets Off the U.S. East Coast Reveal Systematic Biases in ERA5 and HRRR

Low-level jets (LLJs)—wind speed maxima typically occurring a few hundred meters above the surface—are common off the U.S. East Coast and influence many atmospheric processes with societal importance, including cloud formation, aviation safety, and search-and-rescue. However, their vertical structure and frequency remain poorly quantified due to limited offshore observations. This study presents new scanning Doppler LiDAR and infrared spectroradiometer data from the 2024 summer deployment of an offshore barge during the Wind Forecast Improvement Project 3. These coupled wind and temperature profiles provide unprecedented resolution to assess LLJ behavior and model performance. LLJs occurred in over 21% of observed profiles, with a weak diurnal preference for nighttime and early morning hours and maximum winds typically near 300 m. Both ERA5 and High-Resolution Rapid Refresh analysis underestimate jet wind speeds and misrepresent the boundary layer thermal structure. These results highlight persistent model biases and the critical need for high-resolution offshore observations.

17 WIND ENERGY↗
DOE OSTI2019

Development of a Ballon-Borne Barge-Mounted Wind Measurement Platform

Sandia National Laboratories (SNL) is developing a low-cost, environmentally safe, and weather-proof sensor system that can be deployed offshore for extended periods of time for wind resource monitoring. The system has clear economic benefits over meteorological (met) tower approaches and is easily relocated to multiple locations across a project site. The end development goal is a buoy or barge-based, balloon-borne atmospheric measurement platform that operates autonomously in all but the most severe weather conditions, provides data of comparable accuracy to a met tower, and provides more accurate wind data at higher altitudes than floating lidar at half the cost.

17 WIND ENERGY↗
NASA NTRS1980

Sea surface temperature of the coastal zones of France

The results of an investigation to map the various thermal gradients in the coastal zones of France are presented. Paricular emphasis is given to the natural phenomena and man made thermal effluents. It is shown that a close correlation exist between wind speed direction and the offshore width of the effluent.

Deschamps, P. Y.↗
NASA NTRS1994

Physical processes affecting availability of dissolved silicate for diatom production in the Arabian Sea

A passive tracer to represent dissolved silicate concentrations, with biologically realistic uptake kinetics, is successfully incorporated into a three-dimensional, eddy-resolving, ocean circulation model of the Indian Ocean. Hypotheses are tested to evaluate physical processes which potentially affect the availability of silicate for diatom production in the Arabian Sea. An alternative mechanism is offered to the idea that open ocean upwelling is primarily responsible for the high, vertical nutrient flux and consequent large-scale phytoplankton bloom in the northwestern Arabian Sea during the southwest monsoon. Model results show that dissolved silicate in surface waters available for uptake by diatoms is primarily influenced by the intensity of nearshore upwelling from soutwest monsoonal wind forcing and by the offshore advective transport of surface waters. The upwelling, which in the model occurs within 200 +/- 50 km of the coast, appears to be a result of a combination of coastal upwelling, Elkman pumping, and divergence of the coastal flow as it turns offshore. Localized intensifications of silicate concentrations appear to be hydrodynamically driven and geographically correlated to coastal topographic features. The absence of diatoms in sediments of the eastern Arabian Basin is consistent with modeled distributional patterns of dissolved silicate resulting from limited westward advection of upwelled coastal waters from the western continental margin of India and rapid uptake of available silicate by diatoms. Concentrations of modeled silicate become sufficiently low to become unavailable for diatom production in the eastern Arabian Sea, a region between 61 deg E and 70 deg E at 8 deg N on the south, with the east and west boundaries converging on the north at approximately 67 deg E, 20 deg N.

Young, David K.↗
NASA NTRS2014

Remotely Searching for Noctiluca Miliaris in the Arabian Sea

Reversing monsoonal winds in the Arabian Sea result in two seasons with elevated biological activity, namely the annual summer Southwest Monsoon (SWM; June to September) and winter Northeast Monsoon (NEM; November to March) [Wiggert et al., 2005]. Generally speaking, the SWM and NEM create two geographically distinct blooms [Banse and English, 2000; Levy et al., 2007]. In the summer, winds from the southwest drive offshore Ekman transport and coastal upwelling along the northwestern coast of Africa, which brings nutrient-rich water to the surface from below the permanent thermocline [Bauer et al., 1991]. In the winter, cooling of the northern Arabian Sea causes surface waters to sink, which generates convective mixing that injects nutrients throughout the upper mixed layer [Madhupratap et al., 1996]. This fertilization of otherwise nutrient-deplete surface waters produces one of the most substantial seasonal extremes of phytoplankton biomass and carbon flux anywhere in the world [Smith, 2005].

Arabian Sea↗
DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗
DOE OSTI2022

Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow

This work presents a new engineering analytical model that predicts the effect of both the turbine yaw misalignment and the inflow wind veer on the wake flow distribution downwind of a wind turbine. To consider the veered inflow, two methods were examined. In the first method, the curled shape of the wake due to the yaw offset is initially modelled. The wake shape is then laterally skewed at each height due to the wind veer based on the assumption that the turbine wake is transported downstream by the incoming flow. The second method is a more realistic approach that accounts for the effect of wind veer on the wind velocity direction and the yaw angle seen by the wind turbine. This models the wake region in a local coordinate system defined based on the wind direction at each height. A coordinate transformation is then performed to represent the wake flow distribution in the global coordinate system attached to the ground. The results show that while the two methods provide similar outputs for small variations in the wind direction across the rotor, the difference becomes more evident with an increase in wind veer. High-fidelity simulations for a turbine subject to a neutral atmospheric boundary layer were employed to validate model predictions for different operating conditions.

17 WIND ENERGY↗
DOE OSTI2023

The Diurnal Cycle of East Pacific Convection, Moisture, and CYGNSS Wind Speed and Fluxes

The far eastern tropical Pacific is one of the rainiest locations on Earth. This region is characterized by a robust diurnal cycle with precipitation initiating over the Andes mountains in Colombia in the late afternoon and moving offshore overnight while organizing into mesoscale convective systems (MCSs). As the MCSs move westward, they can seed tropical easterly waves that develop into tropical cyclones. Novel measurements of near-surface wind speeds and latent heat flux (LHFLX) from the Cyclone Global Navigation Satellite System (CYGNSS) mission and ERA5 reanalysis are used to evaluate changes to regional flow patterns, moisture, and LHFLX that favor a strong westward propagating diurnal cycle of precipitation in this region. Days with strongly versus weakly westward propagating diurnal precipitation are compared during the extended boreal summer of the CYGNSS era (May–October 2018–2021). Strongly propagating days have a more moist lower troposphere with stronger vertically integrated moisture flux convergence than days with weakly propagating precipitation. The enhanced low-level moisture is supported by increased wind-driven LHFLX from stronger regional flows including the Choco and Caribbean Low-Level Jets and Panama and Papagayo gap winds. Increased offshore convergence and vorticity also help sustain convection during the days with strongly propagating precipitation. Background variations in the physical environment, as opposed to diurnal variations, seem more important for supporting a robust diurnal cycle of precipitation in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Use of a Compliant Tether to Decouple Observation Buoy Motion for Auxiliary Wave Power

With the growth of the Blue Economy, the volume of data collection within the ocean environment has been rapidly increasing. Larger numbers of oceanographic, meteorological, and floating Light Detection And Ranging (LiDAR) buoys have been collecting high fidelity measurements while pushing against power budget limits. Power limitations lead to infrequent transmission of reduced data sets or recording data to local storage that must be physically collected when the buoy is serviced. Triton Systems, Inc. and its partners are developing a retrofittable wave energy converter (WEC) to provide auxiliary power to these observation buoys to increase mission duration and power budget, improve reliability, and reduce the need for service trips. One of the greatest challenges has been developing a method to interface Triton's WEC with these buoys without impacting measurement fidelity. This is especially critical for inertial wave and LiDAR wind measurements collected with sensors that could be adversely affected by additional buoy dynamics introduced by an integrated WEC. To address this, Triton and EOM Offshore developed a compliant tether to pair an observation buoy with a floating WEC while decoupling relative motion. Based on EOM's proven stretch hose technology, this compliant tether transmits power and data between the buoy-WEC system. In conclusion, modeling shows that the system has the potential to minimally adversely affect oceanographic, meteorological, wind resource characterization, and other measurements, with future testing scheduled to validate modeling efforts.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Large-Amplitude Motion Platform: A New Ocean Simulator Can Help Technologies Succeed

Offshore renewable energy technologies - like wave energy devices, wind turbines, floating solar panels, and hybrid systems - can help decarbonize our power grids as well as offshore activities like international shipping and seafood farming. But it's not always easy to build technologies hearty enough to operate in a powerful ocean environment. And subjecting promising prototypes to real ocean waves can be an expensive, time-consuming, and risky way to get these technologies ready for the high seas. Now, with the National Renewable Energy Laboratory's (NREL's) new testing platform, called the large-amplitude motion platform (or LAMP for short), our experts can replicate powerful ocean waves in a low-risk laboratory setting. The LAMP, coupled with NREL's diverse array of testing instrumentation, can help technology developers rapidly hone their prototypes before embarking on a potentially costly and time-consuming ocean trial.

marine energy↗
DOE OSTI2021

Efficient and low-cost hydrogen production by wind power driven water electrolysis

The document describes and discusses the results of a techno-economic analysis for wind driven electrolysis systems. The costs obtained for different plants, including onshore and offshore locations and different plant sizes, are discussed. Large scale wind electrolysis plants show high potential to achieve the target of 2 $/kg. Initial results of experimental tests for a single cell electrolyzer, to be coupled directly with a wind turbine, are also presented and discussed.

08 HYDROGEN↗
DOE OSTI2020

Large-eddy simulations of the Northeastern US coastal marine boundary layer

In this study, large eddy simulations (LES) of offshore boundary layers near the Nantucket coast are performed using Nalu-Wind. The marine boundary layer conditions are chosen to match the predominantly unstable and neutral conditions measured by the Cape Wind platform. The appropriate domain, resolution, and boundary condition settings required for the LES are established through this work. Differences between stable and unstable cases are found in the wind speed profiles, averaged statistics, and wind spectra, and explained in terms of stratification effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Performance of reanalysis and mesoscale models off the coast of Hawai'i

The eastern Hawai'i coast in the United States is characterized by considerable wind resource fuelled by persistent trade winds, making it an important area for energy research. The need is strong for reanalyses and higher-resolution regional simulations where observations have been historically limited, such as Hawai'i's offshore environments. However, studies using offshore observations in other parts of the world have shown that significant errors can occur in reanalyses and wind datasets, which can lead to inaccurate estimates of wind energy generation, payback periods, and extreme weather risks at project locations. The degree of such errors is influenced by a number of factors, including spatial resolution and the handling of processes within the planetary boundary layer (PBL). In this work, we provide a wind resource characterization from year-long lidar buoy measurements off the eastern coast of O'ahu, Hawai'i, an environment previously unobserved at the rotor level, and use the characterization to evaluate the performance of two simulation datasets. The O'ahu deployment location is meteorologically unique and less complex than land-based wind resource characterizations, being strongly characterized by trade winds with minimal land–atmosphere interaction influences. Despite the unique and fairly consistent meteorological conditions, we hypothesize that distinct simulation datasets will exhibit diverse ranges of errors similar to those that have been seen for other offshore locations. We find the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) to strongly underestimate observed wind speeds at the O'ahu location (bias = −1.54 m s −1 at a height of 140 m above sea level), while a regional Weather Research and Forecasting Model (WRF) simulation produced by the University of Hawai'i (UH-WRF) provides a significantly smaller wind speed bias (−0.25 m s −1 ), highlighting the value of running regional, higher-resolution simulations. The large bias noted for ERA5 is driven by significant underestimation of fast wind speeds (>9 m s −1 ), which the study site is largely characterized by, along with discontinuities in the ERA5 diurnal cycle. We also speculate that the relative sparsity of observations for data assimilation in this remote part of the world could influence the performance of ERA5 and that challenges with characterizing island effects could impact the performance of both datasets.

17 WIND ENERGY↗
NASA NTRS2002

Satellite-Based Assessment of Sediment Transport, Distribution and Resuspension Associated with the Atchafalaya River Discharge Plume

Tbe Atchafalaya River discharges over 80 x 10(exp 6) tons of sediment annually onto the broad shallow continental shelf of central and western Louisiana. Satellite imagery from the NOAA AVHRR and Terra MODIS are used in this paper to quantify suspended sediment concentrations and to assess sediment transport processes along the Louisiana shelf under varying conditions of river discharge and wind forcing. The image data reveal the maim sources of sediment, direction of transport amd regional extent of wind-wave resuspension. The prevailing easterly winds transport much of the suspended sediments westward toward the Chernier Plain in a well-defined mud stream. Westerly flow rates of 25-50 cm/s (21-43 km per day) have been measured, yielding a transit time of about 1.5-2.5 days from the mouth of Atchafalaya Bay to the Chernier Plain. Progradation rates along the Chernier Plain coast reach 50 m per year. The westward-flowing Atchafalaya "mud stream" is rapidly disrupted by westerly winds and northerly winds, which accompany frequent winter storms and less frequent tropical storms or hurricanes. During these events, the coastal current reverses and sediments are rapidly transported out of Atchafalaya Bay and offshore where substantial sedimentary deposits can also be found. Offshore sediment fluxes during storm events, in combination with wind-wave resuspension, can result in surface sediment "plumes" extending 70 km offshore and 150 km alongshore. Field measurements of suspended sediment concentrations, current and wind velocities, and directions are used to assess sediment transport processes on the shelf. These combined processes are extending the pro-delta deposits of the Atchafalaya-Wax Lake delta complex far onto the continental shelf and supplying sediments for a renewal era of progradation along tbe downdrift Chernier Plain coast.

Walker, Nan↗
DOE OSTI2020

Outcomes of the DOE Workshop on Atmospheric Challenges for the Wind Energy Industry

The U.S. Department of Energy-funded Mesoscale-to-Microscale Coupling (MMC) project team planned and conducted a virtual Workshop on Atmospheric Challenges for the Wind Energy Industry on October 19 and 20, 2020. The goal of the workshop was to forge a dialog with the community, including industry representatives, on how modeling tools are currently being used, the present active atmospheric modeling research in support of wind energy, and required advancements in capabilities and technology to continue to advance wind energy deployment. The workshop was planned in collaboration with an industry advisory panel that included representatives from wind power plant developers, turbine manufacturers, and companies that provide resource assessment and forecasting services. The format of the workshop included panels from government research sponsors, visionaries from industry, and mixed panels of researchers discussing research status and needs. A shared keynote presentation from the Technical University of Denmark experts anchored the second day of the workshop. An emphasis was placed on understanding the research needs in the offshore environment. In addition, breakout opportunities were provided each day. On the first day, the breakout discussions addressed predesigned questions configured to elicit participants’ thoughts on needed research directions. The second-day breakouts treated three important technical topics through a combination of presentations and group conversations. Each workshop participant chose their breakout preference from among downscaling details, modeling for turbines, and using artificial intelligence for atmospheric modeling. The discussions were robust and productive. The outcomes of the workshop include archiving a series of recommendations from industry and the research community on research directions required to further advance wind energy deployment. Discussions confirmed the need for high-fidelity modeling but that there are specific areas of applicability and other areas where the time and cost of computation is prohibitive. In those cases, the high-fidelity models can inform low-order models that are more practical for real-time or widely deployed applications. Industry must consider the financial cost of performing more expensive modeling approaches, but industry engineers and researchers are using these approaches where there appears to be a return on investment. An emerging type of low-order model is based on machine learning (ML). Participants confirmed that there are many atmospheric phenomena that need to be modeled better, including low-level jets, cold air outbreaks, land-sea induced circulations, diurnal variability, thin stable boundary layers, dynamic changes such as from frontal passage, interaction of wakes and blockage, and more. For the offshore environment, there is wide agreement that some level of ocean-wave-atmospheric coupling is necessary to capture variations in rotor-level winds needed to plan and operate offshore wind plants. Another recurring recommendation is that more observations are needed, particularly for the offshore environment. Those observations should consider the needs for model improvement, both for physically based models and for ML models. Observations must capture atmospheric profiles of variables that are important to understanding and modeling atmospheric and oceanic phenomena that impact boundary layer winds. Models must be validated with data and the uncertainty quantified, particularly those that are sensitive to initial and boundary conditions. Finally, a repeated request was to consider the holistic needs of hybrid plants of wind, solar, and storage resources because those types of plants are likely to be the wave of the future. In addition, industry wishes to understand impacts of the resource under a changing climate for long-term planning.

17 WIND ENERGY↗
NASA NTRS2011

Peak Wind Forecasts for the Launch-Critical Wind Towers on Kennedy Space Center/Cape Canaveral Air Force Station, Phase IV

This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds arc an important forecast clement for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to update the statistics in the current peak-wind forecast tool to assist in forecasting LCC violations. The tool includes onshore and offshore flow climatologies of the 5-minute mean and peak winds and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗
DOE OSTI2025

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Cape Cod (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles that integrate a scanning Doppler lidar, a profiling Doppler lidar, and two sonic anemometers across Northeast U.S. coastal and offshore sites during the WFIP3 campaign. Variables include wind speed, wind direction, vertical velocity, turbulence intensity, and turbulent kinetic energy, each with per-instrument quality control and inter-instrument agreement validation. Profiles are mapped to a standardized height grid – dedicated near-surface levels at the sonic measurement heights (4 m and 10 m AGL), 20 m spacing to 100 m, and 30 m spacing above – and carry component and derived uncertainty estimates. Heights are reported above ground level; the site's ground elevation is stored separately. The Cape Cod dataset covers 1 February 2024 – 6 September 2025.

17 WIND ENERGY↗