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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Methodology for Robust Load Reduction in Wind Turbine Blades Using Flow Control Devices

Decades of wind turbine research, development and installation have demonstrated reductions in levelized cost of energy (LCOE) resulting from turbines with larger rotor diameters and increased hub heights. Further reductions in LCOE by up-scaling turbine size can be challenged by practical limitations such as the square-cube law: where the power scales with the square of the blade length and the added mass scales with the volume (the cube). Active blade load control can disrupt this trend, allowing longer blades with less mass. This paper presents the details of the development of a robust load control system to reduce blade fatigue loads. The control system, which we coined sectional lift control or SLC, uses a lift actuator model to emulate an active flow control device. The main contributions of this paper are: (1) Methodology for SLC design to reduce dynamic blade root moments in a neighborhood of the rotor angular frequency (1P). (2) Analysis and numerical evidence supporting the use of a single robust SLC for all wind speeds, without the need for scheduling on wind speed or readily available measurements such as collective pitch or generator angular speed. (3) Intuition and numerical evidence to demonstrate that the SLC and the turbine controller do not interact. (4) Evaluation of the SLC using a full suite of fatigue and turbine performance metrics.

17 WIND ENERGY↗
NASA NTRS2015

Global Ocean Evaporation: How Well Can We Estimate Interannual to Decadal Variability?

Evaporation from the world's oceans constitutes the largest component of the global water balance. It is important not only as the ultimate source of moisture that is tied to the radiative processes determining Earth's energy balance but also to freshwater availability over land, governing habitability of the planet. Here we focus on variability of ocean evaporation on scales from interannual to decadal by appealing to three sources of data: the new MERRA-2 (Modern-Era Retrospective analysis for Research and Applications -2); climate models run with historical sea-surface temperatures, ice and atmospheric constituents (so-called AMIP experiments); and state-of-the-art satellite retrievals from the Seaflux and HOAPS (Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite) projects. Each of these sources has distinct advantages as well as drawbacks. MERRA-2, like other reanalyses, synthesizes evaporation estimates consistent with observationally constrained physical and dynamical models-but data stream discontinuities are a major problem for interpreting multi-decadal records. The climate models used in data assimilation can also be run with lesser constraints such as with SSTs and sea-ice (i.e. AMIPs) or with additional, minimal observations of surface pressure and marine observations that have longer and less fragmentary observational records. We use the new ERA-20C reanalysis produced by ECMWF embodying the latter methodology. Still, the model physics biases in climate models and the lack of a predicted surface energy balance are of concern. Satellite retrievals and comparisons to ship-based measurements offer the most observationally-based estimates, but sensor inter-calibration, algorithm retrieval assumptions, and short records are dominant issues. Our strategy depends on maximizing the advantages of these combined records. The primary diagnostic tool used here is an analysis of bulk aerodynamic computations produced by these sources and uses a first-order Taylor series analysis of wind speed, SST, near-surface stability and relative humidity variations around climatology to gauge the importance of these components. We find that the MERRA-2 evaporation record is strongly influenced by the availability of wind speed and humidity from passive microwave imagers beginning in the late 1980s as well as by the SST record. The trend over the period 1980 to present is nearly 10%. AMIP or the ERA-20C trends are much smaller. We find that ENSO-related signals involving both wind speed and thermodynamic variability remain the primary signal in the latter and are confirmed by satellite retrievals. We present uncertainty estimates based on the various data sources and discuss the implications for GEWEX water and energy budget science challenges.

Robertson, Franklin R.↗
DOE OSTI2025

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗
NASA NTRS1972

Mission 119 passive microwave results

Passive microwave measurements of the sea surface were made for determining surface wind speeds from the NP3A aircraft (NASA-927). Observations were made at frequencies of 1.4, 10.6, and 31.4 GHz during NASA mission 119, undertaken off Bermuda in the vicinity of Argus Island sea tower during January 1970. Passive microwave observations from Argus Island ocean showed that the surface roughness effect, dependent on wind speed, is also dependent on observational frequency, increasing with increasing frequency. The roughness effect appears to be dominant for wind speeds less than 30 to 40 knots (2).

Hollinger, J. P.↗
DOE OSTI2021

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R 2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ocean Surface Flux Algorithm Effects on Earth System Model Energy and Water Cycles

Earth system models parameterize ocean surface fluxes of heat, moisture, and momentum with empirical bulk flux algorithms, which introduce biases and uncertainties into simulations. We investigate the atmosphere and ocean model sensitivity to algorithm choice in the Energy Exascale Earth System Model (E3SM). Flux differences between algorithms are larger in atmosphere simulations (where wind speeds can vary) than ocean simulations (where wind speeds are fixed by forcing data). Surface flux changes lead to global scale changes in the energy and water cycles, notably including ocean heat uptake and global mean precipitation rates. Compared to the control algorithm, both COARE and University of Arizona (UA) algorithms reduce global mean precipitation and top of atmosphere radiative biases. Further, UA may slightly reduce biases in ocean meridional heat transport. We speculate that changes seen here, especially in the ocean, could be even larger in coupled simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Analysis of the Bivariate Parameter Wind Differences Between Jimsphere and Windsonde

An analysis is presented for the bivariate parameter differences between the FPS-16 Radar/Jimsphere and the Meteorological Sounding System (MSS) Windsonde. The Jimsphere is used as the standard to measure the ascent wind during the Space Shuttle launches at Kennedy Space Center, Florida, and the Windsonde is the backup system. In addition, a discussion of the terrestrial environment (below 20 km) and a description of the Jimsphere and Windsonde wind sensors are given. Computation of the wind statistics from 64 paired Jimsphere and Windsonde balloon releases in support of 14 Space Shuttle launches shows a good agreement between the two wind sensors. From the analysis of buildup and back-off data for various scales of distance and the comparison of the cumulative percent frequency (CPF) versus wind speed change, it is shown that the wind speed change for various scales of distances for the Jimsphere and Windsonde compare favorably.

Susko, Michael↗
NASA NTRS1989

Acoustical effects of a large ridge on low-frequency sound propagation in stationary and moving atmospheres

The effects of a ridge on a low-frequency acoustic propagation in quiescent and windy atmospheres are investigated using a parabolic approximation. A logarithmic wind-speed profile, commonly employed to model atmospheric wind currents, is modified and used to model two-dimensional atmospheric flow over a triangularly-shaped hill. The parabolic equation is solved using an implicit finite-difference algorithm. Several examples are examined to determine the combined effects of source-ridge distance, ridge dimensions, wind-speed profile, and CW source frequency on the received acoustic field.

Robertson, J. S.↗
NASA NTRS1989

Correlation of N2O and ozone in the southern polar vortex during the Airborne Antarctic Ozone Experiment

The correlation of N2O and ozone in the Antarctic stratosphere during the late austral winter was investigated using measurements of N2O mixing ratios obtained by an airborne laser spectrometer and in situ measurements of ozone for latitudes between 53 and 72 deg S. In addition, airborne N2O and O3 measurements taken between 13 and 20 km in the mid-latitudes (37 deg N and 53 deg S) were correlated. It was found that, while the mid-latitude ozone-N2O corelation was negative, poleward of 53 deg S, the N2O and O3 mixing ratios often showed a strong positive correlation, which approximately coincided with the edge of the polar vortex as defined by the wind-speed maximum. Inside the vortex, in lower wind speed regions, the N2O-O3 correlation became negative again, with the lowest ozone mixing ratios usually found near the boundary with the positively correlated region.

Strahan, S. E.↗
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↗
DOE OSTI2025

Observations of Coastal Wind Momentum Flux: Dependence on Fetch and Waves with Comparisons to COARE

Here, using observations from the Martha’s Vineyard Coastal Observatory, this paper investigates how momentum flux in the marine atmospheric surface layer over the coastal ocean varies with fetch, wave age, and wave slope and assesses the performance of the COARE 3.5 bulk parameterization. Long-fetch (at least 300 km) and short-fetch (3–6 km away from land) conditions have very similar momentum flux, with the latter being just 15% higher. The COARE 3.5 wind speed–dependent formulation closely matches the observations. The sea state dependence of wave age and wave slope is analyzed by considering both peak frequency and mean frequency in a wave spectrum. The slope of regression lines between normalized roughness and wave age is sensitive to wind speed ranges and the scatter of momentum flux, potentially explaining why earlier studies did not find a universal formula to characterize the wave dependence. Although the observed momentum flux exhibits an obvious dependence on wave age, a robust quadratic fit between momentum flux and the 10-m neutral wind speed exists only for young waves. For the short-fetch conditions, the momentum flux does not increase as wave slope increases. This may be because waves generated by local wind are still weak and swell that propagates from other areas dominates the wave spectra. In other words, the wave slope computed by considering the spectra does not properly reflect the local wind–wave interaction.

Air-sea interaction↗
DOE OSTI2026

A Multiscale Simulation Study of the Effects of Nantucket Island on Atmospheric Boundary Layer Flow

Multiscale atmospheric simulations were conducted to investigate how Nantucket Island modifies the marine atmospheric boundary layer (ABL) flow, how the mechanisms responsible are represented in mesoscale versus large-eddy simulation (LES) domains, and potential impacts on wind energy production downstream, in moderate and high wind speed cases. Here, to isolate the effects of the island, each case study was simulated (i) with and without island topography included and (ii) with observed versus spatially uniform sea surface temperature (SST) values, the latter removing the influence of spatial variability in SST, while also enabling the examination of how the island effects vary with near-surface thermodynamic stability over the surrounding ocean. Island effects were found to be strongest during daytime heating, which generates convective rolls that redistribute momentum vertically over the island and downstream. Colder SSTs and weaker winds strengthen these rolls and extend their influence. Flow statistics within a representative wind turbine rotor-swept area downstream show that while vertical momentum redistribution enhances near-surface wind speeds, those aloft decrease, resulting in minimal net change to rotor-equivalent wind speed and slightly reduced vertical shear. Comparisons of mesoscale and LES domains reveal that both capture the roughness-driven near-surface slowdown, but mesoscale models underestimate vertical momentum transport compared to LES, which explicitly resolves convective rolls. Increasing LES resolution beyond the grid spacing required to begin capturing the largest convective roll structures ∼ O(100) m yields minimal additional momentum transport but increases resolved turbulence kinetic energy, relevant for stress loading.

Atmosphere-land interaction↗
DOE OSTI2021

Wind Energy Forecasting with the Weather Research and Forecasting Model

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Siemens Energy, Inc. (Siemens) to develop a wind resource forecasting tool. LLNL was to develop an independent high-resolution mesoscale modeling capability forecasting tool that could be implemented in conjunction with existing wind farm control and monitoring software to provide forecasting of wind resources using local observations of winds and temperature. Research with LLNL’s state-of-the-art large-eddy simulation meteorological prediction model, based on the community WRF model and innovative turbulence parameterizations, would improve that model’s applicability to large wind farms offshore and in complex terrain. The modeling capability would include uncertainty quantification. Finally, the application of the modeling tool and existing global climate change predictions would enable the delineation of the likely effects of climate change on wind resources. Siemens was to provide high time resolution hub-height wind speed and other meteorological data streams, including temperature profiles from wind farms, for LLNL to incorporate into the modeling system, to validate and tune this forecasting model for their locations of interest. These data streams would also be used for longer-term studies of correlations of wind resources to climate oscillations to indicate how long-term climate change trends may affect the available wind resource. Siemens would also provide information and observations of turbine wakes for incorporation into the modeling tool. By implementing state-of-the-art turbulence parameterizations into a simulation model and/or ensembles of simulation models, and by integrating real-time hub height wind speed and other meteorological datastreams from wind farms into that model or ensemble of models, LLNL would develop a forecasting tool that could be implemented by Siemens as an add-on to existing wind farm control and monitoring software to provide owners with useful resource forecasting. The desired outcome was that the accuracy level of the output would be sufficient to substantiate power output commitments. The final deliverable for this work would consist of a document outlining the algorithms and software tools that could be integrated into Siemens Wind Park Supervisor.

17 WIND ENERGY↗
NASA NTRS1995

Morphology of solar wind fluctuations and structure in the vicinity of the Sun from radio propagation measurements

Radio propagation measurements represent a powerful means for remote probing of electron density and solar wind speed in the acceleration region of the solar wind not yet explored by in situ measurements. Recent investigations based on radio propagation measurements have led to considerable progress in our knowledge of the general morphology of solar wind fluctuations and structure, especially in terms of their relationship to solar wind properties that have been observed directly by fields and particles measurements, and to coronal features observed in white-light measurements. The purpose of this paper is to present an overview of the latest results on quasi-stationary structure covering the large scale variation of solar wind speed over the streamer belt and coronal hole regions, coronal streamers (source of slow solar wind) and their associated small-scale electron density structure, plumes, density and fractional or relative density fluctuations, and the spectral characteristics of the electron density fluctuations. The radio propagation measurements not only reveal new information on the structure near the Sun, but also show that the structure appears to undergo substantial evolution on its way to 0.3 AU, the closest radial distance for which direct in situ spacecraft measurements are available.

Woo, R.↗
NASA NTRS1977

Aircraft measurements of the microwave scattering signature of the ocean

Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to 55 deg) and radar azimuth angle (0 to 360 deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.

Jones, W. L.↗
DOE OSTI2026

Slow Wake Recovery and Low Turbulence Behind Wind Farms Parameterized in Mesoscale Simulations

Numerical weather prediction (NWP) and climate models equipped with wind-farm parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates wake recovery behind a wind farm represented by the NWP-WFP approach in the Weather Research and Forecasting (WRF) model using either the Fitch et al. (2012) or Ma et al. (2022a, b) WFPs. Results are benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm with aligned and staggered layouts under neutral atmospheric stability. Near-farm wake recovery is underestimated in NWP-WFP simulations due to its representation on a coarse mesoscale grid. This limitation leads to slow wake recovery through two interconnected mechanisms: (i) spatial gradients in the wind velocity field are weaker compared to LES and (ii) turbulence kinetic energy (TKE) remains low not because of excessive dissipation but due to insufficient shear production caused by these weakened gradients. For the scenario considered here, a wind-speed bias develops in the near-farm wake and persists into the far wake. Differences between the NWP-WFP simulations and LES emerge within a short distance downstream of the farm exit, where the mesoscale simulations recover too slowly. This reduced recovery contributes approximately 0.15-0.50 m s-1 to the near-farm wind-speed bias. The bias established in this region is not subsequently compensated for downstream but instead propagates into the far wake, where wind-speed differences of approximately 0.4-0.6 m s-1 remain up to 50 km downstream. Higher-resolution mesoscale simulations partially reduce this bias. Increasing turbine-added TKE or including subgrid wake effects provides additional improvement, but neither fully addresses the underlying cause. The slow wake recovery is not caused by limitations of the WFPs themselves, as it also occurs outside their region of influence, and adding subgrid wake effects does not significantly impact recovery. Rather, the slow wake recovery is a consequence of mesoscale flow representation. This behavior is not limited to regions downstream of the wind farm but is less visible within the farm, where wake recovery occurs simultaneously with turbine-induced momentum extraction. These results highlight the need for improved representations of wake recovery both within and downstream of wind farms. While enhanced subgrid modeling, shear-driven TKE production, and refined WFP formulations may improve intra-farm dynamics, accurately capturing near-farm wake recovery downstream remains challenging, as WFPs do not act in this region.

17 WIND ENERGY↗
NASA NTRS1986

Low-speed wind-tunnel investigation of the effect of strakes and nose machines on lateral-directional stability of a fighter configuration

A series of low-speed static wind-tunnel force tests were conducted on a 0.15-scale model of a modern high-performance fighter aircraft. The tests identified the use of nose chines to enhance stability at high angles of attack. Results of this investigation showed that the strake was the major contributor to directional instability. The destabilizing forces were created by two mechanisms: (1) adverse flow in the region of the vertical tail, and (2) forces generated on the fuselage ahead of the center of gravity. Properly designed nose chines effectively negated the adverse flow near the vertical tail and created stabilizing forces on the forebody in the range of the stall angle of attack.

Brandon, J. M.↗
NASA NTRS2008

Changing Characteristics of Jupiter's Little Red Spot

The Little Red Spot (LRS) in Jupiter's atmosphere was investigated in unprecedented detail by the New Horizons spacecraft together with the Hubble Space Telescope (HST) and the Very Large Telescope (VLT). The LRS and the larger Great Red Spot (GRS) of Jupiter are the largest known atmospheric storms in the solar system. Originally a white oval, the LRS formed from the mergers of three smaller storms in 1998 and 2000 and became as red as the GRS between 2005 and 2006. Here we show that circulation and wind speeds in the LRS have increased substantially since the Voyager and Galileo eras when the oval was white. The maximum tangential velocity of the LRS is now 172 +/- 18 m/s, close to the highest values ever seen in the GRS, which has also evolved both in size and maximum wind speed. The cloud top altitudes of the GRS and LRS are similar, both storms extending much higher in the atmosphere than other Jovian anticyclonic systems. The similarities in wind speeds, cloud morphology, and coloring suggest a common dynamical mechanism explains the reddening of the two largest anticyclonic systems on Jupiter. These storms will not be observed again from close range until at least 2016.

Cheng, A. F.↗