SEARCH · Engineering Papers
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.
This dataset includes 40km vertical wind profiles from late 2023 through 9/30/2024 for Oklahoma, Kansas, and the Northeastern US. The data are in text format. Key for interpreting data is included in this package. Additionally, a descriptor accompanies each data file.
The European Remote-sensing Satellite (ERS-1) was launched in July 1991 and contained several instruments for observing the Earth's ocean including a wind scatterometer. The scatterometer measurements were processed by the European Space Agency (ESA) and the Jet Propulsion Laboratory (JPL). JPL reprocessed (Freilich and Dunbar, 1992) the ERS-1 backscatter measurements to produced a 'value added' data set that contained the ESA wind vector as well as a set of up to four ambiguities. These ambiguities were further processed using a maximum-likelihood estimation (MLE) and a median filter to produce a 'selected vector.' This report describes a technique developed to produce time-averaged wind field estimates with their expected errors using only scatterometer wind vectors. The processing described in this report involved extracting regions of interest from the data tapes, checking the quality and creating the wind field estimate. This analysis also includes the derivation of biweekly average wind vectors over the North Pacific Ocean at a resolution of 0.50 x 0.50. This was done with an optimal average algorithm temporally and an over-determined biharmonic spline spatially. There have been other attempts at creating gridded wind files from ERS-1 winds, e.g., kriging techniques (Bentamy et al., 1996) and successive corrections schemes (Tang and Liu, 1996). There are several inherent problems with the ERS-1 scatterometer. Since this is a multidisciplinary mission, the satellite is flown in different orbits optimized for each phase of the mission. The scatterometer also shares several sub-systems with the Synthetic Aperture Radar (SAR) and cannot be operated while the SAR is in operation. The scatterometer is also a single-sided instrument and only measures backscatter along the right side of the satellite. The processing described here generates biweekly wind maps during the wktwo years analysis period regardless of the satellite orbit or missing data.
A method for generating high-resolution wind maps from scatterometer data was developed and tested on synthetic data for the northeast Pacific Ocean. It is shown that, unlike the wind fields generated by current GCMs, the wind maps constructed by this method retain the high spatial resolution of the scatterometer wherever adequate measurements exist. For the NASA scatterometer, this method would produce every 12 hours a wind map with spatial resolution that preserves the small-scale features of the original data over about half the mapped region. Over the rest of the region, maps with somewhat lower resolution and accuracy will be obtained.
The U.S. Department of Energy's Wind Powering America initiative provides high-resolution wind maps and estimates of the wind resource potential that would be possible from development of the available windy land areas after excluding areas unlikely to be developed. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to Wind Powering America's online wind energy resource maps.
Wind-Tunnel to Full-Scale Mapping of Winds and Loads for Launch-Vehicle Ground Wind Loads
A launch vehicle ground-wind-loads program was conducted at the NASA Langley Transonic Dynamics Tunnel. The objectives were to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces.Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. The study of ground-wind-loads presents unique challenges to quantify significant characteristics of the approaching wind and to relate the wind-tunnel acquired static, dynamic, and gravitational loads to full-scale vehicles. This paper will explain the correlation process between model-scale and full-scale wind characteristics and resulting structural loads. Characterization of the wind at a launch site requires knowledge of the vehicle dynamics and the anemometer performance. Vehicle dynamics dictate the frequency range of interest in characterization of the atmospheric turbulence, and in defining the required data window-length to model dynamic oscillation build-up during wind-gust analysis. Knowledge of the anemometer performance is required to infer peak wind magnitudes since most anemometers cannot directly measure instantaneous peak values. Following proper wind-speed correlation, static and dynamic wind-tunnel loads must be converted to full-scale equivalent values to derive design and operational guidance. In addition to the direct computation of full-scale equivalent loads using relevant scaling parameters, the corrections applied to dynamic loads accounting for differences in structural damping will also be discussed. Furthermore, a phenomenon that manifests in many slender and flexible launch vehicles is a load magnification due to gravity resulting from mass offset under deflection. A method for scaling this contribution from model-scale to full-scale is presented. Finally, a comparison of wind-tunnel derived loads using the described methodologies to launch vehicle measured loads is presented.
A launch vehicle ground-wind-loads program was conducted at the NASA Langley Transonic Dynamics Tunnel. The objectives were to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces. Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. The study of ground-wind-loads presents unique challenges to quantify significant characteristics of the approaching wind and to relate the wind-tunnel acquired static, dynamic, and gravitational loads to full-scale vehicles. This paper will explain the correlation process between model-scale and full-scale wind characteristics and resulting structural loads. Characterization of the wind at a launch site requires knowledge of the vehicle dynamics and the anemometer performance. Vehicle dynamics dictate the frequency range of interest in characterization of the atmospheric turbulence, and in defining the required data window-length to model dynamic oscillation build-up during wind-gust analysis. Knowledge of the anemometer performance is required to infer peak wind magnitudes since most anemometers cannot directly measure instantaneous peak values. Following proper wind-speed correlation, static and dynamic wind-tunnel loads must be converted to full-scale equivalent values to derive design and operational guidance. In addition to the direct computation of full-scale equivalent loads using relevant scaling parameters, the corrections applied to dynamic loads accounting for differences in structural damping will also be discussed. Furthermore, a phenomenon that manifests in many slender and flexible launch vehicles is a load magnification due to gravity resulting from mass offset under deflection. A method for scaling this contribution from model-scale to full-scale is presented. Finally, a comparison of wind-tunnel derived loads using the described methodologies to launch vehicle measured loads is presented.
This work uses journey maps to assess the deployment of distributed wind technologies through the perspective of installers. Journey mapping is a human-centered design method that chronologically traces processes from the perspective of those who participate in them. The journey map will be leveraged to identify deployment pain points (i.e., manifestations of generic deployment barriers) that the Strategize, Engage, Network and Deploy (SEND) Distributed Wind project team will seek to address in future work.
Aeolian features on Venus include dune fields, eroded hills (yardangs), wind streaks, (miniature dunes of 10 to 30 cm wavelength). Although and possibly microdunes (in repetitive imaging by Magellan did show changes in the appearance of the surface, these changes are attributed to radar artifacts as a consequence of look direction rather than to physical changes of the surface. Nonetheless, measurements of wind speeds near the surface of Venus and wind tunnel simulations suggest that aeolian processes could be currently active on Venus. Study of radar images of terrestrial analogs shows that radar wavelength, polarization, and viewing geometry, including look direction and incidence angle, all influence the detection of dunes, yardangs, and wind streaks. For best detection, dune crests and yardangs should be oriented perpendicular to look direction. Longer wavelength systems can penetrate sand sheets a meter or more thick, rendering them invisible, especially in arid regions. For wind streaks to be visible, there must be a contrast in surface properties between the streak and the background on which it occurs. Nonetheless, more than 6000 aeolian features have been found on Magellan images of Venus, the most common of which are various wind streaks. Mapping wind streak orientations enables near-surface wind patterns to be inferred for the time of their formation. Type P streaks are associated with parabolic ejecta crater deposits and are considered to have formed in association with the impact event. Most Type P streaks are oriented westward, indicative of the upper altitude superrotation winds of Venus. Non Type P streaks have occurrences and orientations consistent with Hadley circulation. Some streaks in the southern hemisphere are oriented to the northeast, suggesting a Coriolis effect.
This final report describes the comprehensive findings on a project to validate and improve atmospheric models for offshore wind resource mapping and prediction.
The MIT group participated in seven publications in the 1999 issues of JGR with sections devoted in PEM-Tropics A, and had two papers which may be considered offshoots of these studies combined with commercial aircraft trace constituents data, one in Nature and one in EOS. In the meteorological overview we contributed a set of 1000 hPa divergent wind maps which we calculated from ECMWF data, meridional wind cross-sections, velocity potential and divergent wind maps, maps of stream function and rotational wind components, and vertical velocity profiles computed from mass balance, these all constituting part of the overall climatology. We also contributed material for the "stalactite" case observed from the DC-8 on September 3, 1996. This included a map of potential vorticity on 350 K, a cross-section of lidaro O3 a cross-section of potential vorticity along 140 deg W, and a map of specific humidity showing extreme dryness accompanying the high potential vorticity values and the high ozone values, all suggesting subsidence from the local stratosphere. In the paper on chemical characteristics we contributed 12 hour values of the 1000 hPa divergent wind component for the full period of PEM Tropics A; these were used by David Westberg to establish the air mass boundaries and in turn used by Gerry Gregory to set up a table of quantitative values of trace constituents and their ratios both sides of the boundaries.
In developing a national energy strategy, the United States has a number of objectives, including increasing economic growth, improving environmental quality, and enhancing national energy security. Wind power contributes to these objectives through the deployment of clean, affordable and reliable domestic energy. To achieve U.S. wind generation objectives, the Wind and Water Power Program within the Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE) instituted the U.S. Offshore Wind: Removing Market Barriers Program in FY 2011. Accurate and comprehensive information on offshore wind resource characteristics across a range of spatial and temporal scales is one market barrier that needs to be addressed through advanced research in remote sensing technologies. There is a pressing need for reliable offshore wind-speed measurements to assess the availability of the potential wind energy resource in terms of power production and to identify any frequently occurring spatial variability in the offshore wind resource that may impact the operational reliability and lifetime of wind turbines and their components and to provide a verification program to validate the “bankability” of the output of these alternative technologies for use by finance institutions for the financing of offshore wind farm construction. The application of emerging remote sensing technologies is viewed as a means to cost-effectively meet the data needs of the offshore wind industry. In particular, scanning and buoy mounted LIDAR have been proposed as a means to obtain accurate offshore wind data at multiple locations without the high cost and regulatory hurdles associated with the construction of offshore meteorological towers. However; before these remote sensing technologies can be accepted the validity of the measured data must be evaluated to ensure their accuracy. The proposed research will establish a unique coastal ocean test-bed in the Mid-Atlantic for the evaluation of LIDAR-based wind measurement systems to validate the accuracy of remotely measured wind data in marine applications. Specifically, the test-bed will be utilized to systematically evaluate the capability of emerging scanning LIDAR and buoy mounted vertically profiling LIDAR by: (1) Evaluating a fixed scanning LIDAR against land-based 50 and 60 meter high meteorological masts fitted with research quality cup-vane and/or sonic anemometers; (2) Evaluating a buoy mounted vertically profiling LIDAR fixed on land and floating in a sheltered bay against a co-located 60 meter high meteorological mast fitted with a research quality cup-vane and/or sonic anemometers and the fixed scanning LIDAR; and (3) Offshore field evaluation of both LIDAR platforms through a comparison of the fixed scanning LIDAR data and data obtained by the buoy mounted LIDAR located 10 miles offshore. The proposed research will systematically validate Light Detection and Ranging (LIDAR) based wind measurement systems and assess the temporal and spatial variability of the offshore wind resource in the Mid-Atlantic east of New Jersey. The goal of the proposed project is to address the technical and commercial challenges of the offshore wind energy industry by validating and assessing cost-effective, over ocean wind resource characterization technologies. The objective is to systematically evaluate the capability of both scanning and vertically profiling LIDARs to accurately measure 3D wind fields through comparison with fixed met masts and intercomparison among LIDAR platforms. Once validated, data collected by both buoy mounted vertically profiling LIDARs and shore-based, pulsed horizontally scanning LIDARs can be used to accurately assess offshore wind resources and to quantify the spatial and temporal variability in the offshore wind fields. One of the fundamental research questions to be addressed in phase 1 is the assessment of various measurement and data processing schemes to retrieve accurate wind vectors in the marine environment over large sampling ranges (10 to 12 km) and varying atmospheric aerosol levels. Atmospheric conditions and aerosol content within the coastal ocean region of the Mid-Atlantic seaboard of the US can vary significantly over short time periods in response to frontal passages and extratropical and tropical low pressure system passage offshore of the coast. Since aerosols provide the scattering medium for the determination of LIDAR Doppler shifts in the atmosphere the accuracy and range of LIDAR derived velocity measurements as a function of variation in aerosol content in the marine environment is a key research question to be addressed. In phase 1, it is desired to capture as much variation in atmospheric conditions and aerosol content as possible. To this end, collocated measurements of LIDAR and standard anemometer wind fields will be captured by the project PIs over all four seasons and during specific events (e.g., coastal low pressure system passage) in year 1. Additionally, since the meteorological masts are permanent structures, additional events can be captured over the three year duration of the field research project. All research instruments are owned by Fishermen’s Energy and made available to the PIs though a lease agreement as part of the DOE grant. Energy Fishermen’s Energy will be responsible for the operation and maintenance of the scanning LIDAR and met mast anemometers. On a daily basis, environmental data and systems performance indicators will be transmitted from each measurement station to the Fishermen’s project team consisting of both in-house personnel and equipment manufacturer engineers. Data sets include compiled LIDAR files as well as data sets from ancillary sensors. Diagnostic parameters to be monitored include standard deviations of measured values, battery levels and charging systems output, and the operational status. Once data have been confirmed as complete and reliable, files will be transferred to the Garrad Hassan (a subcontractor to Fishermen’s Energy) for incorporation in to the validation database, which is accessible to other scientific team members. Data collection times and durations will be determined by the PI and Co-PIs in consultation with instrument engineers to ensure the capture of data representative of the expected range of mid-Atlantic atmospheric conditions (e.g., temperature, moisture, coastal low pressure systems, tropical systems, rain, snow, fog). The collection and processing of the data is a function of site specific measurement requirements (Kelley et.al. 2007; Hannon et.al. 2008). To determine the optimal profiles of wind speed and direction from the LIDAR radial velocities as a function of azimuth angle, rigorous estimates of the bias and random error of each radial velocity estimate are required. Lockheed Martin Coherent Technologies, Inc., under contract with Fishermen’s Energy, will provide analyses of raw and processed data using various scan patterns to determine optimal performance settings for the pulsed scanning LIDAR. Once optimized, appropriate processing and analyses techniques will be evaluated by Garrad Hassan for use in validating the accuracy of the LIDAR wind field measurements against the standard anemometer measurements from the meteorological masts. The most attractive capability of the scanning LIDAR is the ability to provide high spatial resolution observations in a three-dimensional volume which provides superior statistical accuracy due to the large number of samples obtained. Each radial scan provides measurements in 100 range gates over a distance of 10 to 12 km at an update rate of 5 to 10 Hz and rotation of 2.5° per second. Each rotation at a fixed azimuth requires 2.4 minutes. Depending on the number of azimuths desired a complete scan can take up to 10 minutes or longer to complete. Once collected the radial velocities are processed to produce vector wind velocity estimates based on a set of data distributed in angle and range around points of interest, typically a standard grid within the radial wind map. To calculate wind vectors over a limited spatial area of interest for the comparison of data with other measurement platforms a localized least-squares approach has been applied by Hannon et.al. (2008) and a Variation Assimilation (VAR) processing technique has been applied by Chan and al Assimilation (VAR) processing technique has been applied by Chan and Shao (2006). Additionally, Kelley et.al. (2007) applied a “stare” technique that fixed a scanning LIDAR in both azimuth and elevation angles to measure over collocated sampling volumes of the LIDAR and a 3D sonic anemometer mounted to a fixed mast. Although the stare technique is limited to wind directions aligned with the sampling radial of the LIDAR, it does provide a direct comparison of sampling volumes. Each of the processing techniques described above (and possibly others) will be evaluated to determine the validity of the LIDAR derived wind fields in the marine environment. Numerical methods such as linear regression and comparison of probability density functions of wind fields measured by each instrument platform will be used to assess the processing techniques. Linear regression has the advantage of directly evaluating corresponding pairs of wind data measured by each instrument and can lend insight into deviations and bias between instruments as a function of wind speed. Assessment of the coherency between the probability density function of the wind measured by each instrument provides insight into processes that may not be accurately resolved by each instrument at specific frequencies. Once processed and assessed the most appropriate technique will be utilized to provide valid wind measurements from the pulsed scanning LIDAR. A detailed analysis of the measurement data from the LIDAR and the three meteorological towers and comparison of the coastal wind characteristics from the different systems will be performed by the CO_PI at NREL. This analysis will evaluate how the WT LIDAR performance and measurement of the wind characteristics vary with distance from the LIDAR and by atmospheric conditions; using the tower measurements at different distances (4.8, 9.6, and 19 km) from the LIDAR as a reference. The comparative analysis will include, to the extent possible, evaluation of parameters such as wind speed and direction distributions, wind shear, turbulence intensity and their variations by atmospheric conditions, month or season, and time of day.
Information about ocean weather is extracted from radar returns with aid of special algorithm. Algorithm determines wind-speeds and wind directions at ocean surface, and from this information can locate low- and high-pressure centers, convergence regions, and zones of strong winds and wind shear associated with ocean weather system fronts.
The application of the Laser Atmospheric Wind Sounder to the EOS and Space Station is proposed. The use of pulsed, CO2 Doppler lidar to measure wind is described. The design requirements for a Doppler lidar operating in space, and the need to study the global distribution of naturally occurring atmospheric aerosols are discussed. The space-based Doppler lidar wind data will be useful for improving the skill of numerical weather predictions, for studying large-scale atmospheric circulation and climate dynamics, and for analyzing global biogeochemical and hydrological cycles.
Detailed maps of wind streaks in Tharsis and Elysium have been compiled from Viking Orbiter observations spanning one complete Martian year. The streak pattern is controlled by slope winds on the central volcanoes and on the flanks of the Tharsis bulge, while the global circulation dominates in Elysium. Dust erosion by downslope winds occurs over much of Tharsis and in the vicinity of Elysium Mons; this process is effective even at the low atmospheric pressures found near the summits of the large volcanoes. Erosional streaks are largely absent in Elysium Planitia; net deposition of dust might have occurred during the period of the observations. Surface properties such as slope, thermal inertia, and roughness may influence the efficiency of slope wind production sufficiently to account for the pronounced differences in streak types and patterns present in these two regions.
The National Renewable Energy Laboratory (NREL) recently released new estimates of the U.S. potential for wind-generated electricity, using advanced wind mapping and validation techniques to triple previous estimates of the size of the nation's wind resources. The new study, conducted by NREL and AWS TruePower, finds that the contiguous 48 states have the potential to generate up to 37 milliongigawatt-hours annually. In comparison, the total U.S. electricity generation from all sources was roughly 4 million gigawatt-hours in 2009.
The Hurricane Imaging Radiometer (HIRAD) is a synthetic thinned array passive microwave radiometer designed to allow retrieval of surface wind speed in hurricanes, up through category five intensity. The retrieval technology follows the Stepped Frequency Microwave Radiometer (SFMR), which measures surface wind speed in hurricanes along a narrow strip beneath the aircraft. HIRAD maps wind speeds in a swath below the aircraft, about 50-60 km wide when flown in the lower stratosphere. HIRAD has flown in the NASA Genesis and Rapid Intensification Processes (GRIP) experiment in 2010 on a WB-57 aircraft, and on a Global Hawk unmanned aircraft system (UAS) in 2012 and 2013 as part of NASA's Hurricane and Severe Storms Sentinel (HS3) program. The GRIP program included flights over Hurricanes Earl and Karl (2010). The 2012 HS3 deployment did not include any hurricane flights for the UAS carrying HIRAD. The 2013 HS3 flights included one flight over the predecessor to TS Gabrielle, and one flight over Hurricane Ingrid. This presentation will describe the HIRAD instrument, its results from the 2010 and 2013 flights, and potential future developments.
This dataset contains statistics (mean and standard deviation) calculated from quality-control lidar radial wind speed data through the LiSBOA method. This is an intermediate product for the synthesis of dual-Doppler wind maps.