Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “WIND”

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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Study on Modeled Wind Speed Errors Using the U.S. Department of Energy Buoys

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies Office. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of wind energy in the U.S. waters. The first deployment for one buoy was off the coast of Virginia from December 2014 to May 2016, and the first deployment for the other buoy was off the coast of New Jersey from November 2015 until February 2017. This report describes recent analysis of data collected during these first two deployments. Specifically, we compare hub-height wind speed estimates using Monin-Obukhov Similarity Theory (MOST) to the lidar measurements, and examine how those errors are affected by wind direction, atmospheric stability, wind-wave direction differences, and various measures of the wave-state. The comparisons are done using standard similarity functions based on MOST; including the Businger - Dyer, the Beljaars & Holtslag and the Vickers & Mahrt similarity functions. All models produce large errors over the range of atmospheric stabilities that were observed, with the largest errors occurring for stable flows. The Vickers & Mahrt function resulted in the largest overall bias and standard deviation, while Beljaars & Holtslag function gave the smallest bias and standard deviation due to its better performance under stable conditions. The models perform best under unstable conditions, but even in this regime there is a consistent overestimation of the wind speed of between roughly 0 to 1 ms -1 compared to the lidar measurements. We identify specific metocean conditions (i.e. stability and wind and wave directions) at each of the deployment locations that lead to large errors in MOST predictions. Finally, a coupled ocean-atmosphere model framework was investigated to simulate large errors in weather research forecasting (WRF).

17 WIND ENERGY↗
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 OSTI2021

Deliverable D12 – Distributed Wind Data Catalog Development Guide and Instruction Manual

Pacific Northwest National Laboratory and Technical University of Denmark completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research (WP2) for the International Energy Agency Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future (IEA Wind Task 41). As the final deliverable for WP2, Deliverable D12 includes a data instruction guide for the IEA Wind Task 41 distributed wind data catalog. As such, this document includes: a step-by-step explanation of how the IEA Wind Task 41 data catalog was created, how it was populated, and how to use it; future options for the IEA Wind Task 41 data catalog, and a summary with recommendations for future work.

17 WIND ENERGY↗
DOE OSTI2025

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗
DOE OSTI2023

U.S. Offshore Wind Energy Noise Reduction Associated with Installation of Fixed-Bottom Foundations: Workshop Report

As offshore wind energy development grows in the United States, solutions are needed to reduce the underwater noise and substrate vibration generated during fixed-bottom turbine installation to help protect marine life. Monopiles are currently the main turbine foundation type installed globally and impact pile driving, the primary installation method, can be a major source of noise and vibration generation during wind farm construction. Opportunities exist to reduce the amount of noise and vibration produced during future offshore wind farm development. The use of alternative foundation types and installation methods, as well as innovative noise abatement technologies, would help reduce the potential detrimental effects on sensitive marine species. To explore these opportunities, the Department of Energy’s Wind Energy Technologies Office, in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, funded the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory to organize, host, and facilitate a virtual workshop in December 2022. The goal of the workshop was to gather input from the offshore wind energy community on noise reduction strategies for the installation of fixed-bottom offshore wind turbines in U.S. waters across multiple regions, including the U.S. Atlantic Coast, Gulf of Mexico, and Great Lakes to inform recommendations on future research. The joint lab team convened industry representatives, subject matter experts, and regulators to discuss potential pathways to reduce noise and vibration associated with fixed-bottom turbine installation, including the practicality of using alternative foundations and installation methods, the effectiveness of noise abatement technologies, as well as research and monitoring needs. In preparation for the workshop, the team invited experts to be part of a steering committee and worked with its members to help focus activities to meet the workshop goals. Additional pre-workshop activities included developing the invitee list and workshop agenda, reviewing existing Construction and Operations Plans (COP) for proposed offshore wind projects, distributing a brief questionnaire to industry representatives, and drafting the workshop discussion questions and Mural boards. In total, 128 workshop participants provided over 600 comments in response to the 17 group discussion questions used over two workshop sessions. Overarching recommendations highlighted across themes included future investments to provide data sharing, consistency, transparency, and opportunities for sharing best available science, knowledge, and expertise. The joint lab team synthesized the comments and identified four key research and development themes that could help advance the successful implementation of noise and vibration reduction strategies (see report). This report provides an overview of the workshop goals and scope, reviews the pre-workshop activities, presents brief summaries of participant feedback, and concludes with detailed research themes and recommendations for future investments. Appendix A includes the group discussion questions, Appendix B includes the results of the COP review, and Appendix C includes the results of the industry questionnaire. Overall, there was a high level of interest and engagement in the workshop. The sessions provided an opportunity for significant exchange of information between workshop participants from across sectors. Participants identified a variety of opportunities for next steps towards the noise reduction of offshore wind turbine installation in U.S. waters, including recommendations for future investments to provide certainty in the use of new technologies associated with alternative foundation types, noise abatement systems, and efficacy monitoring.

17 WIND ENERGY↗
DOE OSTI2025

5-minute Wind Power Data based on WFIP2 WRF Simulation

The second Wind Forecast Improvement Project (WFIP2) was a public-private partnership funded by the U.S. Department of Energy and NOAA, aimed at enhancing the forecast skill of numerical weather prediction models for turbine-height winds in regions with complex terrain. An 18-month Weather Research and Forecasting (WRF) model simulation was conducted over the Pacific Northwest, with model outputs validated against observational data collected during WFIP2. Simulated wind speeds were used to estimate wind power generation using reV (the Renewable Energy Potential Model developed by NREL) at ten wind project sites. Two sets of results were produced: one using wind speeds extracted from the model grid cell at the project centroid, and another using wind speeds from the actual turbine locations. For each dataset, power output was calculated using both actual turbine-specific power curves and nine generic power curves to convert wind speed into power.

17 WIND ENERGY↗
DOE OSTI2016

AXISYMMETRIC SIMULATIONS OF HOT JUPITER–STELLAR WIND HYDRODYNAMIC INTERACTION

Gas giant exoplanets orbiting at close distances to the parent star are subjected to large radiation and stellar wind fluxes. In this paper, hydrodynamic simulations of the planetary upper atmosphere and its interaction with the stellar wind are carried out to understand the possible flow regimes and how they affect the Lyα transmission spectrum. Following Tremblin and Chiang, charge exchange reactions are included to explore the role of energetic atoms as compared to thermal particles. In order to understand the role of the tail as compared to the leading edge of the planetary gas, the simulations were carried out under axisymmetry, and photoionization and stellar wind electron impact ionization reactions were included to limit the extent of the neutrals away from the planet. By varying the planetary gas temperature, two regimes are found. At high temperature, a supersonic planetary wind is found, which is turned around by the stellar wind and forms a tail behind the planet. At lower temperatures, the planetary wind is shut off when the stellar wind penetrates inside where the sonic point would have been. In this regime mass is lost by viscous interaction at the boundary between planetary and stellar wind gases. Absorption by cold hydrogen atoms is large near the planetary surface, and decreases away from the planet as expected. The hot hydrogen absorption is in an annulus and typically dominated by the tail, at large impact parameter, rather than by the thin leading edge of the mixing layer near the substellar point.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

AN INVESTIGATION OF THE SOURCES OF EARTH-DIRECTED SOLAR WIND DURING CARRINGTON ROTATION 2053

In this work we analyze multiple sources of solar wind through a full Carrington Rotation (CR 2053) by analyzing the solar data through spectroscopic observations of the plasma upflow regions and the in situ data of the wind itself. Following earlier authors, we link solar and in situ observations by a combination of ballistic backmapping and potential-field source-surface modeling. We find three sources of fast solar wind that are low-latitude coronal holes. The coronal holes do not produce a steady fast wind, but rather a wind with rapid fluctuations. The coronal spectroscopic data from Hinode ’s Extreme Ultraviolet Imaging Spectrometer show a mixture of upflow and downflow regions highlighting the complexity of the coronal hole, with the upflows being dominant. There is a mix of open and multi-scale closed magnetic fields in this region whose (interchange) reconnections are consistent with the up- and downflows they generate being viewed through an optically thin corona, and with the strahl directions and freeze-in temperatures found in in situ data. At the boundary of slow and fast wind streams there are three short periods of enhanced-velocity solar wind, which we term intermediate based on their in situ characteristics. These are related to active regions that are located beside coronal holes. The active regions have different magnetic configurations, from bipolar through tripolar to quadrupolar, and we discuss the mechanisms to produce this intermediate wind, and the important role that the open field of coronal holes adjacent to closed-field active regions plays in the process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

PLASMA-FIELD COUPLING AT SMALL LENGTH SCALES IN SOLAR WIND NEAR 1 au

In collisionless plasmas such as the solar wind, the coupling between plasma constituents and the embedded magnetic field occurs on various temporal and spatial scales, and is primarily responsible for the transfer of energy between waves and particles. Recently, it was shown that the transfer of energy between solar wind plasma particles and waves is governed by a new and unique relationship: the ratio between the magnetosonic energy and the plasma frequency is constant, E {sub ms}/ ω {sub pl} ∼ ℏ{sub *}. This paper examines the variability and substantial departure of this ratio from ℏ{sub *} observed at ∼1 au, which is caused by a dispersion of fast magnetosonic (FMS) waves. In contrast to the efficiently transferred energy in the fast solar wind, the lower efficiency of the slow solar wind can be caused by this dispersion, whose relation and characteristics are derived and studied. In summary, we show that (i) the ratio E {sub ms}/ ω {sub pl} transitions continuously from the slow to the fast solar wind, tending toward the constant ℏ{sub *}; (ii) the transition is more efficient for larger thermal, Alfvén, or FMS speeds; (iii) the fast solar wind is almost dispersionless, characterized by quasi-constant values of the FMS speed, while the slow wind is subject to dispersion that is less effective for larger wind or magnetosonic speeds; and (iv) the constant ℏ{sub *} is estimated with the best known precision, ℏ{sub *} ≈ (1.160 ± 0.083) × 10{sup −22} Js.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Turbulent Transport in a Three-dimensional Solar Wind

Turbulence in the solar wind can play essential roles in the heating of coronal and solar wind plasma and the acceleration of the solar wind and energetic particles. Turbulence sources are not well understood and thought to be partly enhanced by interaction with the large-scale inhomogeneity of the solar wind and the interplanetary magnetic field and/or transported from the solar corona. To investigate the interaction with background inhomogeneity and the turbulence sources, we have developed a new 3D MHD model that includes the transport and dissipation of turbulence using the theoretical model of Zank et al. We solve for the temporal and spatial evolution of three moments or variables, the energy in the forward and backward fluctuating modes and the residual energy and their three corresponding correlation lengths. The transport model is coupled to our 3D model of the inhomogeneous solar wind. We present results of the coupled solar wind-turbulence model assuming a simple tilted dipole magnetic configuration that mimics solar minimum conditions, together with several comparative intermediate cases. By considering eight possible solar wind and turbulence source configurations, we show that the large-scale solar wind and IMF inhomogeneity and the strength of the turbulence sources significantly affect the distribution of turbulence in the heliosphere within 6 au. We compare the predicted turbulence distribution results from a complete solar minimum model with in situ measurements made by the Helios and Ulysses spacecraft, finding that the synthetic profiles of the turbulence intensities show reasonable agreement with observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Computational examination of utility scale wind turbine wake interactions

We performed numerical simulations of small, utility scale wind turbine groupings to determine how wakes generated by upstream turbines affect the performance of the small turbine group as a whole. Specifically, various wind turbine arrangements were simulated to better understand how turbine location influences small group wake interactions. The minimization of power losses due to wake interactions certainly plays a significant role in the optimization of wind farms. Since wind turbines extract kinetic energy from the wind, the air passing through a wind turbine decreases in velocity, and turbines downstream of the initial turbine experience flows of lower energy, resulting in reduced power output. Our study proposes two arrangements of turbines that could generate more power by exploiting the momentum of the wind to increase velocity at downstream turbines, while maintaining low wake interactions at the same time. Furthermore, simulations using Computational Fluid Dynamics are used to obtain results much more quickly than methods requiring wind tunnel models or a large scale experimental test.

17 WIND ENERGY↗
DOE OSTI2017

Atmospheric turbulence affects wind turbine nacelle transfer functions

Despite their potential as a valuable source of individual turbine power performance and turbine array energy production optimization information, nacelle-mounted anemometers have often been neglected because complex flows around the blades and nacelle interfere with their measurements. This work quantitatively explores the accuracy of and potential corrections to nacelle anemometer measurements to determine the degree to which they may be useful when corrected for these complex flows, particularly for calculating annual energy production (AEP) in the absence of other meteorological data. Using upwind meteorological tower measurements along with nacelle-based measurements from a General Electric (GE) 1.5sle model, we calculate empirical nacelle transfer functions (NTFs) and explore how they are impacted by different atmospheric and turbulence parameters. This work provides guidelines for the use of NTFs for deriving useful wind measurements from nacelle-mounted anemometers. Corrections to the nacelle anemometer wind speed measurements can be made with NTFs and used to calculate an AEP that comes within 1% of an AEP calculated with upwind measurements. We also calculate unique NTFs for different atmospheric conditions defined by temperature stratification as well as turbulence intensity, turbulence kinetic energy, and wind shear. During periods of low stability as defined by the Bulk Richardson number ( R B ), the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of high stability at some wind speed bins below rated speed, leading to a steeper NTF during periods of low stability. Similarly, during periods of high turbulence, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of low turbulence at most wind bins between cut-in and rated wind speed. Based on these results, we suggest different NTFs be calculated for different regimes of atmospheric stability and turbulence for power performance validation purposes.

17 WIND ENERGY↗
DOE OSTI2020

An Overview of Wind Energy Production Prediction Bias, Losses, and Uncertainties

The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the industry is recording near-zero average energy prediction bias. Herein, we present an overview of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including the improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight the opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty, and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary on how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the manuscript.

literature review↗
NASA NTRS2002

Detecting ocean surface wind using the TRMM precipitation radar

Although designed specifically for the measurement of precipitation in the atmosphere, the Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite alsomeasures the normalized radar cross-section at the Earth's surface. As such, this instrument providesan interesting opportunity to explore an alternative radar configuration in the satellite remote sensingnf ocean winds. In particular, it can measure the strength of the ocean winds in relatively higherspatial resolution as compared to the conventional scatterometer systems presently in use. The addition of wind sensing capability to precipitation radar also complements its rain profiling capabilitynicely and allows coincident wind and rain measurements. In this paper, we discuss the new ocean wind algorithm developed specifically for TRMM PR using maximum likelihood estimation. A uniquefeature of this wind algorithm is its capability to incorporate measurement sensitivity and noiseinformation consistently in both the along-track and cross-track directions. This PR wind algorithm hasbeen tested using data from the TRMM Microwave Imager (TMI) and NASA QuikSCAT scatterometer.Excellent agreement on the retrieved wind strengths is achieved among three sensors.

precipitation radar TRMM GPM CAMEX-4 ocean surface↗
NASA NTRS2006

Combined Active and Passive Remote Sensing of Hurricane Ocean Winds

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

sea surface winds↗
NASA NTRS2020

Instrument Offset Optimization Technique for Airborne Doppler Wind Lidar Profiling Algorithm

This paper presents the instrument offset optimization technique for the Doppler Aerosol Wind Lidar (DAWN) profiling algorithm at NASA Langley Research Center (LaRC). The 2 um Doppler wind Lidar system at LaRC has a long history of research development and airborne campaigns. The core of the wind Lidar data processing is Airborne Wind Profiling Algorithm for Doppler Wind Lidar (APOLO), which was developed at LaRC. The extraction of wind parameters from the airborne Doppler wind Lidar data is challenging due to many factors such as the speed of aircraft, and the errors in instrument installation and calibration. It is unavoidable to prevent the adverse impact of calibration error and instrument installation offset on the performance of wind parameter estimation in the algorithm. Due to the unsteady environment where the data are collected, even a small offset will result in nonsensical results in the parameter estimation process. A brief introduction of APOLO and the overview of the optimization techniques are presented in this paper.

Wind profile↗
NASA NTRSDate not supplied

Wind-Optimal Trajectories for Multirotor eVTOL Aircraft on UAM Missions

Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. Low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, from the safety and efficiency perspective, planning and flying minimum energy trajectories are important.The primary motivation for this paper is to determine if there is an operational benefit to flying wind-optimal trajectories for short flights (less than 60 miles) in the urban environment. This study employs wind-optimal trajectories for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The optimal control model presented includes a wind model for quantifying the effect of wind on the trajectory. The optimal control problem is numerically solved using the direct method. Energy consumption and flight duration flying wind-optimal trajectories between origins and destinations in a metropolitan area are compared with energy consumption and flight duration flying on the great-circle paths between the same origin and destination pairs to determine the operational benefit of wind-optimal routing for short flights.The flight duration results for different scenarios are validated using a simulation tool designed and developed by NASA for exploring advanced air traffic management concepts. In summary,this research study suggests that for short flights in an urban environment, the wind-optimal trajectories have a very slight (insignificant) operational advantage over the great-circle trajectories in terms of energy consumption and flight duration. As expected, headwinds and tailwinds along the route of flight have a significant impact on energy consumption and flight duration.

Urban Air Mobility↗
DOE OSTI2013

National Skills Assessment of the U.S. Wind Industry in 2012

A robust workforce is essential to developing domestic wind power projects, including manufacturing, siting, operations, maintenance, and research capabilities. The purpose of our research is to better understand today's domestic wind workforce, projected workforce needs as the industry grows, and how existing and new programs can meet the wind industry's future education and training needs. Results presented in this report provide the first published investigation into the detailed makeup of the wind energy workforce, educational infrastructure and training needs of the wind industry. Insights from this research into the domestic wind workforce will allow the private sector, educational institutions, and federal and state governmental organizations to make workforce-related decisions based on the current employment and training data and future projections in this report.

17 WIND ENERGY↗