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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 343 records · Page 19

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NASA NTRS1991

Hourly wind profiler observations of the jet stream - Wind shear and pilot reports of turbulence

Hourly wind profiler observations of the jet stream are reported on the basis of over 400 hr of wind and temperature data taken during two prolonged jet stream passages over western and central Pennsylvania during mid-November 1986 and mid-January 1987. The mean wind speed profile with error bars for the 79 hr that the Crown radar was determined to be 'under' the jet stream is shown. A mean speed of 83 m/s for the period was found. A plot of wind shear for the hours of interest is given. Typically, the shear was at a maximum from 3 to 4 km below the level of maximum wind. Thus, an aircraft would have to fly through potentially rough air to reach the fuel savings and relative smoothness of flight at the jet stream level. A good correlation between pilot reports of turbulence and wind shear was found.

Syrett, William J.↗

NASA NTRS1995

Elemental composition in the slow solar wind measured with the MASS instrument on WIND

The MASS instrument on WIND contains the first isochronous time-offlight spectrometer to be flown in the solar wind. The first spectra obtained with this instrument has demonstrated its capability to measure the abundances of several high-and low-FIP elements in the solar wind. The derivation of these abundances requires a careful calibration of the charge exchange efficiencies of the relevant ions in carbon foils. These efficiencies and the corresponding instrument functions have been determined in extensive calibration campaigns at different institutions. We present first and preliminary results obtained in slow solar wind streams and we compare these results with those obtained from previous investigations of solar wind abundances and of coronal abundances as derived from Solar Energetic Particles. Recent models of the FIP related fractionation effect predict a depletion of a factor of typically 4 to 5 for high-FIP elements (He, N, O, Ne, Ar, etc.) relative to low-FIP elements (Mg, Fe, Si, etc.). We also compare our results with the detailed predictions of the different models and we discuss the resulting evidence to validate or to invalidate different physical scenarios explaining the feeding and the acceleration of slow stream solar wind.

Bochsler, P.↗

NASA NTRS1997

Altimeter Estimation of Sea Surface Wind Stress for Light to Moderate Winds

Aircraft altimeter and in situ measurements are used to examine relationships between altimeter backscatter and the magnitude of near-surface wind and friction velocities. Comparison of altimeter radar cross section with wind speed is made through the modified Chelton-Wentz algorithm. Improved agreement is found after correcting 10-m winds for both surface current and atmospheric stability. An altimeter friction velocity algorithm is derived based on the wind speed model and an open-ocean drag coefficient. Close agreement between altimeter- and in situ-derived friction velocities is found. For this dataset, quality of the altimeter inversion to surface friction velocity is comparable to that for adjusted winds and clearly better than the inversion to true 10-m wind speed.

Vandemark, Douglas↗

NASA NTRS2006

Physics-based Tests to Identify the Accuracy of Solar Wind Ion Measurements: A Case Study with the Wind Faraday Cups

We present techniques for comparing measurements of velocity, temperature, and density with constraints imposed by the plasma physics of magnetized bi-Maxwellian ions. Deviations from these physics-based constraints are interpreted as arising from measurement errors. Two million ion spectra from the Solar Wind Experiment Faraday Cup instruments on the Wind spacecraft are used as a case study. The accuracy of velocity measurements is determined by the fact that differential flow between hydrogen and helium should be aligned with the ambient magnetic field. Modeling the breakdown of field alignment suggests velocity uncertainties are less than 0.16% in magnitude and 3deg in direction. Temperature uncertainty is found by examining the distribution of observed temperature anisotropies in high-beta solar wind intervals where the firehose, mirror, and cyclotron microinstabilities should drive the distribution to isotropy. The presence of a finite anisotropy at high beta suggests overall temperature uncertainties of 8%. Hydrogen and helium number densities are compared with the electron density inferred from observations of the local electron plasma frequency as a function of solar wind speed and year. We find that after accounting for the contribution of minor ions, the results are consistent with a systematic offset between the two instruments of 34%. The temperature and density methods are sensitive to non-Maxwellian features such as heat flux and proton beams and as a result are more suited to slow solar wind where these features are rare. These procedures are of general use in identifying the accuracy of observations from any solar wind ion instrument.

Kasper, J. C.↗

NASA NTRS2013

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers. During launch operations, the payload/launch team sometimes asks the LWOs if they expect the upper-level winds to change during the countdown. The LWOs used numerical weather prediction model point forecasts to provide the information, but did not have the capability to quickly retrieve or adequately display the upper-level observations and compare them directly in the same display to the model point forecasts to help them determine which model performed the best. The LWOs requested the Applied Meteorology Unit (AMU) develop a graphical user interface (GUI) that will plot upper-level wind speed and direction observations from the Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Profiling System (AMPS) rawinsondes with point forecast wind profiles from the National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM), Rapid Refresh (RAP) and Global Forecast System (GFS) models to assess the performance of these models. The AMU suggested adding observations from the NASA 50 MHz wind profiler and one of the US Air Force 915 MHz wind profilers, both located near the Kennedy Space Center (KSC) Shuttle Landing Facility, to supplement the AMPS observations with more frequent upper-level profiles. Figure 1 shows a map of KSC/CCAFS with the locations of the observation sites and the model point forecasts.

Bauman, William H., III↗

NASA NTRS2012

Quality Control Algorithms for the Kennedy Space Center 50-Megahertz Doppler Radar Wind Profiler Winds Database

This paper presents the process used by the Marshall Space Flight Center Natural Environments Branch (EV44) to quality control (QC) data from the Kennedy Space Center's 50-MHz Doppler Radar Wind Profiler for use in vehicle wind loads and steering commands. The database has been built to mitigate limitations of using the currently archived databases from weather balloons. The DRWP database contains wind measurements from approximately 2.7-18.6 km altitude at roughly five minute intervals for the August 1997 to December 2009 period of record, and the extensive QC process was designed to remove spurious data from various forms of atmospheric and non-atmospheric artifacts. The QC process is largely based on DRWP literature, but two new algorithms have been developed to remove data contaminated by convection and excessive first guess propagations from the Median Filter First Guess Algorithm. In addition to describing the automated and manual QC process in detail, this paper describes the extent of the data retained. Roughly 58% of all possible wind observations exist in the database, with approximately 100 times as many complete profile sets existing relative to the EV44 balloon databases. This increased sample of near-continuous wind profile measurements may help increase launch availability by reducing the uncertainty of wind changes during launch countdown

Barbre, Robert E., Jr.↗

NASA NTRS2014

Three-Dimensional Wind Profiling of Offshore Wind Energy Areas With Airborne Doppler Lidar

A technique has been developed for imaging the wind field over offshore areas being considered for wind farming. This is accomplished with an eye-safe 2-micrometer wavelength coherent Doppler lidar installed in an aircraft. By raster scanning the aircraft over the wind energy area (WEA), a three-dimensional map of the wind vector can be made. This technique was evaluated in 11 flights over the Virginia and Maryland offshore WEAs. Heights above the ocean surface planned for wind turbines are shown to be within the marine boundary layer, and the wind vector is seen to show variation across the geographical area of interest at turbine heights.

Koch, Grady J.↗

NASA NTRS2015

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Upper-level wind profiles obtained from a 50-MHz Doppler Radar Wind Profiler (DRWP) instrument at Kennedy Space Center are incorporated in space launch vehicle design and day-of-launch operations to assess wind effects on the vehicle during ascent. Automated and manual quality control (QC) techniques are implemented to remove spurious data in the upper-level wind profiles caused from atmospheric and non-atmospheric artifacts over the 2010-2012 period of record (POR). By adding the new quality controlled profiles with older profiles from 1997-2009, a robust database will be constructed of upper-level wind characteristics. Statistical analysis will determine the maximum, minimum, and 95th percentile of the wind components from the DRWP profiles over recent POR and compare against the older database. Additionally, this study identifies specific QC flags triggered during the QC process to understand how much data is retained and removed from the profiles.

Vacek, Austin D.↗

NASA NTRS2015

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Vacek, Austin↗

NASA NTRS2016

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Vacek, Austin↗

NASA NTRSDate not supplied

Novel Mars In-situ Wind & Wind-Blown Particle Measurement Instruments

Mars Sonic Anemometer We have developed the Mars Sonic Anemometer: an in-situ wind measuring instrument. It uses transducers to transmit ‘chirps’ through a volume of atmosphere and measures wind direction, speed, and temperature based on the chirp travel times when received by a paired transducer (fig 1). This method can rapidly take multiple samples of wind (~20 Hz) and can measure gentler wind speeds (~0.05 m/s) than current planetary weather stations (~1Hz and ~2m/s) and is more durable than recent Mars wind sensors. The Sonic Anemometer opens new avenues of research into Mars surface-to-atmosphere exchange (e.g., of heat, momentum or trace gases). It also can be recast as a hydrogen ortho-para sensor for a giant planet descent probe or as an infrasound detector for Earth or Venus. The performance of the sensor at Mars-like conditions of 6mbar of CO2 was validated at the Danish Mars Wind Tunnel.

Donald J Banfield↗

DOE OSTI2017

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators

Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power time series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.

17 WIND ENERGY↗

DOE OSTI2019

Validation of the first LiDAR wind resource assessment buoy system offshore the Northeast United States

The US offshore wind industry is maturing with several projects in various stages of development. These projects require site wind and environmental data before and during operation. Conventional techniques such as fixed-bottom meteorological towers present economical and permitting challenges for the US. Floating Light Detection and Ranging (LiDAR) buoys offer significant advantages including reduced costs, less permitting, and reusability. This paper presents the validation of the first floating LiDAR buoy in Northeast US waters. The buoy, named DeepCLiDAR, includes a LiDAR, ecological monitoring sensors, and metocean sensors. A three-phase LiDAR validation plan was executed, and its results are presented. The objective of the validation plan was to verify the accuracy of measurements made by the LiDAR buoy in wave environments against an unmoving reference wind measurement. Due to a lack of reference met masts, the use of a LiDAR on land as a baseline reference was implemented for validation. Comparison to a reference LiDAR instead of a traditional meteorological tower was a unique approach required in the Northeast US waters due to the absence of a reference fixed-bottom meteorological tower in the region at the time of this study. The testing included a comparison of wind speed measurements made by the buoy deployed 15 km offshore from the mainland and a land-based reference LiDAR located on a nearby island. This paper presents the methodology and results of this program, which indicate favorable agreement. This was the first such validation program in the Northeast USA which is now seeing rapid development of offshore wind.

17 WIND ENERGY↗

DOE OSTI2020

Assessing the blockage effect of wind turbines and wind farms using an analytical vortex model

Wind farm blockage effects are currently neglected in the prediction of wind farm energy yield, typically leading to an overestimation of the production. This work presents a novel method to assess wind farm production, while accounting for blockage effects. We apply a vortex model, based on a cylindrical wake, to assess induction effects. We present variations of the model to account for finite wake length, finite tip-speed ratios, and the proximity to the ground. The results are applied to single rotors in aligned and yawed conditions and to different wind farm layouts. We provide far-field approximations for faster estimates of the velocity field. Further, this article includes a new methodology to couple the induction model to engineering wake models, such as the ones present in the FLOw Redirection and Induction in Steady State (FLORIS). We compare the results to actuator disk simulations for various operating conditions of a single turbine and different wind farm layouts. We found that the mean relative error of the model in the induction zone is typically around 0.2% compared with actuator disk simulations. The computational time of the velocity field using the analytical vortex model is three orders of magnitude less than the one obtained with the actuator disk simulation.

17 WIND ENERGY↗

DOE OSTI2017

A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

Not Available

Feng, Cong↗

DOE OSTI2025

Winds of fortune? Understanding the geographic, sociodemographic, and temporal distribution of benefit mechanisms from land-based wind projects in the United States

Despite decades of research on factors shaping local responses to wind development, there is relatively little known about benefit mechanisms (e.g., agreements, funds, donations) used by developers in the U.S. land-based wind sector. To address this gap, we collected benefit mechanism data across all current utility-scale land-based wind projects installed between 1982 and 2024 (n = 1047), finding that just under one-third of projects had a benefit mechanism attached to them. We find the use of benefit mechanisms has become more common over time, is associated with larger projects, and varies by region. In terms of host community characteristics, the use of benefit mechanisms is associated with characteristics like higher education level, higher percent white, higher percent Republican, higher decision-making capacity, lower unemployment rate, and higher poverty rate. Building on a theoretical framework of purposes, we discuss what these findings could suggest about the motivations driving developers' use of these mechanisms, such as increasing local acceptance of a wind project or supporting distributive fairness. This first-of-its-kind study builds a comprehensive understanding of how benefit mechanisms have been used in the U.S. wind industry throughout its history, which can inform future approaches to benefit-sharing across sectors.

17 WIND ENERGY↗

DOE OSTI2019

Assessing wind power operating costs in the United States: Results from a survey of wind industry experts

This paper draws on a survey of wind industry professionals to clarify trends in the operational expenditures (OpEx) of U.S. land-based wind power plants. We find that average all-in lifetime OpEx has declined from approximately $80/kW-yr (~$35/MWh) for projects built in the late 1990s to a level approaching $40/kW-yr (~$11/MWh) for projects built in 2018. Turbine operations and maintenance costs represent the single largest component of overall OpEx and the primary source of cost reductions. We observe wide ranges of OpEx over time; respondents cite a range in average expected costs for recently commissioned projects from $33/kW-yr to $59/kW-yr. We also use historical OpEx learning rates, showing a 9% OpEx reduction for each doubling of global wind capacity, to project a further $5-$8/kW-yr reduction from 2018 to 2040. These findings suggest that continued OpEx reductions may contribute 10% or more of the expected reductions in land-based wind's levelized cost of energy. Moreover, these estimates understate the importance of OpEx owing to the multiplicative effects through which operational advancements influence not only operations and maintenance costs but also component reliability, performance, and plant-level availability - thereby also affecting levelized costs by enhancing annual energy production and plant lifetimes. Given the limited quantity and comparability of previously available OpEx data, the trends reported here may inform OpEx assumptions used by electric planners, analysts, and modelers. The results may also provide useful benchmarks to the wind industry, helping developers and asset owners compare their expectations with historical experience and other industry projections.

17 WIND ENERGY↗

DOE OSTI2022

Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework

Building on the verification and validation work developed under the Second Wind Forecast Improvement Project, this work exhibits the value of a consistent procedure to evaluate wind power forecasts. We established an open-source Python code base tailored for wind speed and wind power forecast validation, WE-Validate. The code base can evaluate model forecasts with observations in a coherent manner. To demonstrate the systematic validation framework of WE-Validate, we designed and hosted a forecast evaluation benchmark exercise. We invited forecast providers in industry and academia to participate and submit forecasts for two case studies. We then evaluated the submissions with WE-Validate. Our findings suggest that ensemble means have reasonable skills in time series forecasting, whereas they are often inferior to single ensemble members in wind ramp forecasting. Adopting a voting scheme in ramp forecasting that allows ensemble members to detect ramps independently leads to satisfactory skill scores. Throughout this document, we also emphasize the importance of using statistically robust and resistant metrics as well as equitable skill scores in forecast evaluation.

17 WIND ENERGY↗