SEARCH · Engineering Papers

Results for “Wind Direction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

NASA NTRS1988

Power spectral density analysis of wind-shear turbulence for related flight simulations

Meteorological phenomena known as microbursts can produce abrupt changes in wind direction and/or speed over a very short distance in the atmosphere. These changes in flow characteristics have been labelled wind shear. Because of its adverse effects on aerodynamic lift, wind shear poses its most immediate threat to flight operations at low altitudes. The number of recent commercial aircraft accidents attributed to wind shear has necessitated a better understanding of how energy is transferred to an aircraft from wind-shear turbulence. Isotropic turbulence here serves as the basis of comparison for the anisotropic turbulence which exists in the low-altitude wind shear. The related question of how isotropic turbulence scales in a wind shear is addressed from the perspective of power spectral density (psd). The role of the psd in related Monte Carlo simulations is also considered.

Laituri, Tony R.↗

NASA NTRS1990

The correction of infrasound signals for upper atmospheric winds

Infrasound waves propagate in the atmosphere by a well known mechanism produced by refraction of the waves, return to earth, and reflection at the surface into the atmosphere for subsequent bounces. A figure illustrates this phenomenon with results from a ray trace model. In this instance three rays are returned to earth from a region centered at about 50 kilometers in altitude and two from a region near 110 kilometers in altitude. The control of the wave refraction is largely dominated by the temperature-height profile and inversions; however, a major influence is also produced by the atmospheric wind profile. Another figure illustrates the considerable ray differences for rays moving in the wind direction (to the right) and in the counter direction (to the left). It obviously can be expected that infrasonic signal amplitudes will be greatly influenced by the winds in the atmosphere. The seasonal variation of the high altitude atmospheric winds is well documented. A third figure illustrates this with average statistics on the observed zonal wind in the region of 50 plus or minus 5 kilometers in altitude. The results are based upon a survey by Webb; Webb terms this parameterization the Stratospheric Circulation Index (SCI). The very strong seasonal variation has the ability to exert a major seasonal influence on infrasonic signals. The purpose here is to obtain a method for the correction of this effect.

Mutschlecner, J. Paul↗

NASA NTRS2004

Algorithm Determines Wind Speed and Direction from Venturi-Sensor Data

An algorithm computes the velocity of wind from the readings of an instrument like the one described in another Tech Brief. To recapitulate: The sensor has no moving parts and is a compact, rugged means of measuring wind vectors having magnitudes of as much as 300 mph (134 m/s). The sensor includes a Venturi gap bounded by a curved upper and a curved lower surface that are axisymmetric with respect to a vertical axis and mirror-symmetric with respect to a horizontal midplane. One of the curved surfaces is instrumented with multiple ports for measuring dynamic pressures. The sensor also incorporates auxiliary sensors for measuring temperature, relative humidity, and static atmospheric pressure. The design and operation of the sensor are based on the concepts of (1) using Bernoulli's equation (which expresses the relationship among variations of speed, density, and pressure along a streamline) to calculate the speed of the wind from differences among the pressure readings at the various ports; and (2) calculating the direction of the wind from the angular positions of ports selected according to comparisons among their pressure readings. The present algorithm performs these calculations.

Zysko, Jan A.↗

DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1974

Observation of a driver gas-tangential discontinuity

A complete analysis of an interplanetary disturbance of Nov. 19, 1970 using the Apollo 12-SIDE (Suprathermal Ion Detector Experiment) is presented. The SIDE detectors were pointing at 26.3 degrees from the normal solar-wind direction during the observations. The data were least-squares fitted (using a parabolic hypersurface approximation) to a convected Maxwell-Boltzmann distribution function. The results of the fit combined with two other experiments showed a drastic change in the wind speed (from an steady 352 km/sec down to 219 km/sec), direction, and temperature. Except for a delta-function increase at the onset, the density remained constant. There was a considerable enhancement in the abundance of He and probably of heavier elements. The interplanetary magnetic field exhibited a jump of 21 gamma with a change in latitude from -56 to -76 degrees in solar ecliptic coordinates. It is concluded that the disturbance was due to the driver gas-tangential discontinuity of a solar flare-induced shock wave. The characteristic of the tangential discontinuity fit well with theoretical prediction.

Medrano, R. A.↗

NASA NTRS2000

Microwave Sensing of Ocean Winds Including the Use of SAR Imagery

This paper presents aircraft measurements of near-surface atmospheric boundary layer wind roll signatures and radar-derived sea surface roughness. These data are completely coincident in space and time and this unique feature supports attempts to definitively link SAR backscatter signatures to boundary layer roll impacts. The open-ocean data were collected at an altitude of 20 m from NOAA's Long-EZ aircraft using its turbulence probe and down-looking Ka-band radar scatterometer. Several flight legs of 20-30 km were flown with a heading across the wind direction, which is also roughly perpendicular to the roll vortices. We find remarkable correlation between measured modulations in the along-wind component of wind speed and radar backscatter for the spatial scale of 1 to 1.5 km. Close agreement between normalized modulation amplitudes suggests the radar-inferred surface slope variance is changing linearly with wind speed. These data were collected within 30 minutes of a RADARSAT SAR overpass where apparent boundary layer impacts of the same orientation and spatial dimension are prevalent in the SAR backscatter image. Quantitative comparison between modulations in the aircraft and satellite radar data will be discussed.

Vandemark, Douglas↗

NASA NTRS2000

Measured Correlation Between Roll-Vortex Signatures and Radar-Inferred Sea Surface Roughness

This paper presents aircraft measurements of near-surface atmospheric boundary layer roll signatures and radar-derived sea surface roughness. These data are completely coincident in space and time and this unique feature supports attempts to definitively link SAR backscatter signatures to boundary layer roll impacts. The open-ocean data were collected at an altitude of 20 in from NOAA's Long-EZ aircraft using its turbulence probe and down-looking Ka-band radar scatterometer, Several flight legs of 20-30 km were flown with a heading across the wind direction, which is also roughly perpendicular to the roll vortices. We find remarkable correlation between measured modulations in the along-wind component of wind speed and radar backscatter for the spatial scale of I to 1.5 kin. Close agreement between normalized modulation amplitudes suggests the radar-inferred surface slope variance is changing linearly with wind speed. These data were collected within 30 minutes of a RADARSAT SAR overpass where apparent boundary layer impacts of the same orientation and spatial dimension are prevalent in the SAR backscatter image. Quantitative comparison between modulations in the aircraft and satellite radar data will be discussed.

Vandemark, Douglas↗

NASA NTRS2013

Observations of C-Band Brightness Temperatures and Ocean Surface Wind Speed and Rain Rate from the Hurricane Imaging Radiometer (HIRAD) during GRIP and HS3

HIRAD is a new technology developed by NASA/MSFC, in partnership with NOAA and the Universities of Central Florida, Michigan, and Alabama-Huntsville. HIRAD is designed to measure wind speed and rain rate over a wide swath in heavy-rain, strong-wind conditions. HIRAD is expected to eventually fly routinely on unmanned aerial vehicles (UAVs) such as Global Hawk over hurricanes threatening the U.S. coast and other Atlantic basin areas, and possibly in the Western Pacific as well. HIRAD first flew on GRIP in 2010 and is part of the 2012-14 NASA Hurricane and Severe Storm Sentinel (HS3) mission on the Global Hawk, a high-altitude UAV. The next-generation HIRAD will include wind direction observations, and the technology can eventually be used on a satellite platform to extend the dynamical range of Ocean Surface Wind (OSV) observations from space.

Miller, Timothy L.↗

NASA NTRS1982

Mapping Ocean Winds by Radar

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.

Overland, J. E.↗

NASA NTRS2014

Comparison of Marine Boundary Layer Cloud Properties from CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km×30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R(sup 2) = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km× 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 micrometers is 1.3 micrometers larger than that from the ARM retrievals (12.8 micrometers), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm( exp -2) less than its ARM counterpart (114.2 gm( exp-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 micrometers channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from 13.7 to 2.1 gm2. The 10% differences between the ARM and CERES-MODIS LWP and r(sub e) retrievals are within the uncertainties of the ARM LWP (approximately 20gm( exp -2)) and r(sub e) (approximately 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when τ is approximately 10 and topography. The τ differences vary with wind direction and are consistent with the island orography.Much better agreement in τ is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Xi, Baike↗

NASA NTRS1983

Effects of wind on turbofan engines in outdoor static test stands

Wind can affect measured thrust and can cause turbofan engine speed to fluctuate during outdoor testing. Techniques used at an outdoor test stand at NASA Lewis Research Center to make testing easier and faster and to improve data repeatability include using an inflow control device (ICD) to make fan speed steadier, taking many raw data samples for better averaging, and correcting thrust for wind direction and speed. Data from engine tests are presented to show that the techniques improve repeatability of thrust and airflow measurements under various wind conditions.

Mcardle, J. G.↗

NASA NTRS1983

Effects of wind on turbofan engines in outdoor static test stands

Mcardle, J. G.↗

NASA NTRS2010

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

NASA NTRS1985

Observed Changes at Viking Lander 1

A local dust storm raged in Chryse Planitia, Mars, in June 1981. The changes wrought in the vicinity of the lander (Mutch Memorial Station) by this storm sometime near Sol 1742 were partly described previously. Here, changes related to the storm are itemized, evidence for wind directions during the peak of the storm are cited, and two observations unrelated to the storm are noted. The observations suggest that the eroding winds of the Sol 1742 storm were more easterly (N. 35 deg to 90 deg E.) than those (N. 5 deg to 11 deg E.) that formed the large wind tails; and fragments in erosional residues are 0.7 cm and larger, but smaller ones may be present. Some fragments 0.4 to 0.5 cm and smaller were somehow removed, at least locally; wind speeds of the 1742 local storm were probably greater than those of a previous local dust storm (25 to 30 m/s) that occurred during the same season on Sol 423 because the earlier storm did not alter the surface; the major, if not entire, amount of erosion by the storm occurred between Sols 1728 and 1757; and erosion chiefly occurred where the surface configuration and material properties were altered by the lander and its sampler.

Moore, H. J.↗

NASA NTRS1993

Low Wind Speed Radar Backscatter Measurements at C- and Ku-Band Obtained During the Surface Wave Dynamics Experiment

Radar backscatter measurements collected at both C- and Ku-Band during the recent SurfaceWaves Dynamics Experiment (SWADE) on 1 March 1991 show dramatic variabilities of thenormalized radar cross section (sigma degree) of the ocean surface at low wind speed. Additionally,measurements of the sigma degree in the cross wind direction fluctuated much more than the sigmadegree in the upwind direction. The C- and Ku-band data are quite similar, both exhibiting a morepronounced roll off of sigma degree with decreasing neutral stability wind than indicated bypreviously published empirical model functions. The data show extremely large azimuthalmodulations, in some cases greater than 20 dB, and show good qualitative agreement with theazimuthal modulation predicted.

Carson, S. C.↗

NASA NTRS2005

Contour Error Map Algorithm

The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.

Merceret, Francis↗

NASA NTRS1983

Highlights of the SEASAT-SASS program - A review

Some important concepts of the SEASAT-SASS program are described and some of the decisions made during the program as to methods for relating wind to backscatter are discussed. The radar scatterometer design is analyzed along with the model function, which is an empirical relationship between the backscatter value and the wind speed, wind direction, and incidence angle of the radar beam with the sea surface. The results of Monte Carlo studies of mesoscale turbulence and of studies of wind stress on the sea surface involving SASS are reviewed.

Pierson, W. J., Jr.↗

DOE OSTI2023

Wind Fields in Category 1–3 Tropical Cyclones Are Not Fully Represented in Wind Turbine Design Standards

Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy simulations of three tropical cyclones (one Category 1, one Category 2, and one Category 3 storms) using the Weather Research and Forecasting model. Wind conditions near the eyewall of Cat‐1, Cat‐2, and Cat‐3 storms can exceed current design standards for offshore wind turbines. Winds at 90 m can be faster than outlined in the design criteria for Class I and Class T turbines for 50‐year recurrence periods. Wind speed shear across the turbine rotor layer is also larger than assumed in design specifications. Moreover, vertical variations in wind direction across the turbine rotor layer are large for tropical cyclones of all intensity levels, suggesting design standards should include veer, which can amplify loads in wind turbines. The existence of hurricane wind field characteristics that are not represented in design standards does not imply that damage or failure will certainly occur. Engineering safety factors incorporated in the design of the turbine's blades and structural components may prevent damage from occurring.

17 WIND ENERGY↗