Search NASA⌕ Search

SEARCH · Search NASA

Results for “speed”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Results of NASA Technical Challenge to Demonstrate Two-Speed Drive for Vertical Lift Vehicle

Currently, manned vertical lift vehicles are flown in a manner such that the rotors operate over a narrow range of rotating speed regardless if the vehicle's flight condition is one of vertical takeoff and landing, hover, or forward cruise. The propulsion systems are optimized for operation at the same, corresponding narrow range of rotor speed. However, certain missions and markets benefit greatly if the rotor speed can be adjusted over a wide range of speed to match demands of different missions and flight regimes. A vehicle that can operate with a wide range of rotor speeds would address key barriers to enable new markets and missions for vertical lift vehicles. Key barriers addressed by the wide-range of rotor speed include noise reduced via lower rpm rotor, increase of maximum forward flight speed, increased payload and range, reduced fuel burn, and lower operating costs. A new paradigm for the propulsion system is needed to enable these key benefits. One viable approach is to make use of a two-speed ratio drive system such that the engine can continue to operate over a narrow speed range, whereby engine performance is optimal, while adjusting the rotor speed as needed using the two-speed drive system. Motivated by such needs and by results of several system studies, a NASA Revolutionary Vertical Lift Technology Challenge was established to develop and demonstrate required technologies and designs for achieving a 50% reduction in rotor rpm via a two-speed drive system that incurs less than 2% power loss and maintains current power-to-weight ratios. The technical challenge work was completed and the technical objectives were achieved. This report describes the motivations, the research approach and the significant outcomes.

Transmissions↗
DOE OSTI2021

Assessment of Model Hub Height Wind Speed Performance Using DOE Lidar Buoy Data

As the offshore wind industry continues to gain momentum both in the U.S. and globally, reanalysis products remain essential tools for the lifecycle of a wind farm. From project siting and production estimates to determining construction and maintenance windows, reanalysis products play an important role. These regional and global long-term models also serve as inputs to higher resolution models. With such wide-ranging impacts on the offshore wind industry, the need for validation of reanalysis products is strong, particularly at typical turbine hub heights. Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinelTM buoys for the U.S. Department of Energy (DOE) in order to collect meteorological and oceanographic data, including hub height wind speed, in areas of interest for offshore wind development. This work uses DOE buoy observations off the coasts of New Jersey and Virginia to evaluate the performance of Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), the European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th generation (ERA5), and the National Oceanic and Atmospheric Administration (NOAA) assimilation system Rapid Refresh (RAP). Biases and degrees of correspondence are determined for each reanalysis product in order to provide insights on the performance and uncertainty for long-term wind resource characterization. With the baseline metrics determined, this work proceeds with an investigation into the sources of large deviations between the modeled and observed hub height wind speeds during the East Coast lidar buoy deployments. Consistent sources of reanalysis model error include stably stratified flow conditions, high wind shear, flow parallel to the coastline, and tropical and winter storms. For the near shore New Jersey location, offshore winds (i.e. blowing from land to water) tend to be associated with model overestimation of observed hub height wind speed, while winds parallel to the coastline are correlated with model underestimation of wind speed. Similarly, near the Virginia buoy, during southerly winds (parallel to the coastline) models underestimate the observed wind speed due to coastal upwelling. Reanalysis model wind speeds underestimate the hub height winds with increasing stable atmospheric stratification. Reanalysis model biases are seen when the observed wind speeds approach or exceed typical turbine cut-out speeds (around 20 m s-1). Large model errors during winter and tropical storm events, high wind speed events, and ramp events are often the result of wind speed timing and magnitude offsets. Overall, ERA5 provides the most successful representation of observed offshore hub height wind speeds at the U.S. East Coast buoy locations and is therefore best suited as an input boundary condition for model case studies. ERA5 performs well for a variety of atmospheric phenomena, including storms and sea breezes, however RAP, the next most successful reanalysis model, performs best in capturing the frequency of ramp events.

17 WIND ENERGY↗
NASA NTRS1994

Speeds of coronal mass ejections: SMM observations from 1980 and 1984-1989

The speeds of 936 features in 673 coronal mass ejections have been determined from trajectories observed with the Solar Maximum Mission (SMM) coronagraph in 1980 and 1984 to 1989. The distribution of observed speeds has a range (from 5th to 95th percentile) of 35 to 911 km/s; the average and median speeds are 349 and 285 km/s. The speed distributions of some selected classes of mass ejections are significantly different. For example, the speeds of 331 'outer loops' range from 80 to 1042 km/s; the average and median speeds for this class of ejections are 445 and 372 km/s. The speed distributions from each year of SMM observations show significant changes, with the annual average speeds varying from 157 (1984) to 458 km/s (1985). These variations are not simply related to the solar activity cycle; the annual averages from years near the sunspot maxima and minimum are not significantly different. The widths, latitudes, and speeds of mass ejections determined from the SMM observations are only weakly correlated. In particular, mass ejection speeds vary only slightly with the heliographic latitudes of the ejection. High-latitude ejections, which occur well poleward of the active latitudes, have speeds similar to active latitude ejections.

Hundhausen, A. J.↗
NASA NTRS1995

Source region of low-speed wind

We have been carrying out the interplanetary scintillation observations at a frequency of 327 MHz. The IPS measurements at this frequency can probe the distance range of 0.1-1 AU. We will report on source regions of the low-speed winds which were observed within 0.3 AU by the IPS method. The source regions of low-speed winds have been studied. In 1991, two spacecraft of Sakigake and IMP observed two low-speed streams in one solar rotation, which originated from a magnetic neutral line on the source surface. However speeds are slightly different from each other: one is 300 km/s while the other one is 400 km/s. Similar speed difference was also observed by the IPS method. We examined differences of these source regions in the soft X-ray images observed by the Yohkoh satellite. At the source region of the lower speed wind, sun spots were found under the neutral line, while nothing except the neutral line was found for the higher speed wind. We made a synoptic chart of the solar wind speeds which were observed within 0.3 AU. In this chart, compact regions of very low speed can be found clearly, and the amplitude of a low-speed belt is smaller than that of a magnetic neutral line. Distribution of the low-speed belt is rather suited above active regions than on a neutral line calculated by the potential field model.

Watanabe, H.↗
NASA NTRS1999

Speed tuning of motion segmentation and discrimination

Motion transparency requires that the visual system distinguish different motion vectors and selectively integrate similar motion vectors over space into the perception of multiple surfaces moving through or over each other. Using large-field (7 degrees x 7 degrees) displays containing two populations of random-dots moving in the same (horizontal) direction but at different speeds, we examined speed-based segmentation by measuring the speed difference above which observers can perceive two moving surfaces. We systematically investigated this 'speed-segmentation' threshold as a function of speed and stimulus duration, and found that it increases sharply for speeds above approximately 8 degrees/s. In addition, speed-segmentation thresholds decrease with stimulus duration out to approximately 200 ms. In contrast, under matched conditions, speed-discrimination thresholds stay low at least out to 16 degrees/s and decrease with increasing stimulus duration at a faster rate than for speed segmentation. Thus, motion segmentation and motion discrimination exhibit different speed selectivity and different temporal integration characteristics. Results are discussed in terms of the speed preferences of different neuronal populations within the primate visual cortex.

NASA Center ARC↗
NASA NTRS2007

A Sequential Shifting Algorithm for Variable Rotor Speed Control

A proof of concept of a continuously variable rotor speed control methodology for rotorcraft is described. Variable rotor speed is desirable for several reasons including improved maneuverability, agility, and noise reduction. However, it has been difficult to implement because turboshaft engines are designed to operate within a narrow speed band, and a reliable drive train that can provide continuous power over a wide speed range does not exist. The new methodology proposed here is a sequential shifting control for twin-engine rotorcraft that coordinates the disengagement and engagement of the two turboshaft engines in such a way that the rotor speed may vary over a wide range, but the engines remain within their prescribed speed bands and provide continuous torque to the rotor; two multi-speed gearboxes facilitate the wide rotor speed variation. The shifting process begins when one engine slows down and disengages from the transmission by way of a standard freewheeling clutch mechanism; the other engine continues to apply torque to the rotor. Once one engine disengages, its gear shifts, the multi-speed gearbox output shaft speed resynchronizes and it re-engages. This process is then repeated with the other engine. By tailoring the sequential shifting, the rotor may perform large, rapid speed changes smoothly, as demonstrated in several examples. The emphasis of this effort is on the coordination and control aspects for proof of concept. The engines, rotor, and transmission are all simplified linear models, integrated to capture the basic dynamics of the problem.

Litt, Jonathan S.↗
NASA NTRS2013

Comprehensive Modeling and Analysis of Rotorcraft Variable Speed Propulsion System With Coupled Engine/Transmission/Rotor Dynamics

This project develops comprehensive modeling and simulation tools for analysis of variable rotor speed helicopter propulsion system dynamics. The Comprehensive Variable-Speed Rotorcraft Propulsion Modeling (CVSRPM) tool developed in this research is used to investigate coupled rotor/engine/fuel control/gearbox/shaft/clutch/flight control system dynamic interactions for several variable rotor speed mission scenarios. In this investigation, a prototypical two-speed Dual-Clutch Transmission (DCT) is proposed and designed to achieve 50 percent rotor speed variation. The comprehensive modeling tool developed in this study is utilized to analyze the two-speed shift response of both a conventional single rotor helicopter and a tiltrotor drive system. In the tiltrotor system, both a Parallel Shift Control (PSC) strategy and a Sequential Shift Control (SSC) strategy for constant and variable forward speed mission profiles are analyzed. Under the PSC strategy, selecting clutch shift-rate results in a design tradeoff between transient engine surge margins and clutch frictional power dissipation. In the case of SSC, clutch power dissipation is drastically reduced in exchange for the necessity to disengage one engine at a time which requires a multi-DCT drive system topology. In addition to comprehensive simulations, several sections are dedicated to detailed analysis of driveline subsystem components under variable speed operation. In particular an aeroelastic simulation of a stiff in-plane rotor using nonlinear quasi-steady blade element theory was conducted to investigate variable speed rotor dynamics. It was found that 2/rev and 4/rev flap and lag vibrations were significant during resonance crossings with 4/rev lagwise loads being directly transferred into drive-system torque disturbances. To capture the clutch engagement dynamics, a nonlinear stick-slip clutch torque model is developed. Also, a transient gas-turbine engine model based on first principles mean-line compressor and turbine approximations is developed. Finally an analysis of high frequency gear dynamics including the effect of tooth mesh stiffness variation under variable speed operation is conducted including experimental validation. Through exploring the interactions between the various subsystems, this investigation provides important insights into the continuing development of variable-speed rotorcraft propulsion systems.

DeSmidt, Hans A.↗
DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Non-intrusive speed sensor

In Phase I of the Non-Intrusive Speed Sensor program, a computerized literature search was performed to identify candidate technologies for remote, non-intrusive speed sensing applications in Space Shuttle Main Engine (SSME) turbopumps. The three most promising technologies were subjected to experimental evaluation to quantify their performance characteristics under the harsh environmental requirements within the turbopumps. Although the infrared and microwave approaches demonstrated excellent cavitation immunity in laboratory tests, the variable-source magnetic speed sensor emerged as the most viable approach. Preliminary design of this speed sensor encountered no technical obstacles and resulted in viable and feasible speed nut, sensor housing, and sensor coil designs. Phase II of this program developed the variable-source magnetic speed sensor through the detailed design task and guided the design into breadboard fabrication. The speed sensor and its integral speed nut were evaluated at both unit and system level testing. The final room-temperature and cryogenic spin testing of the hardware demonstrated that the sensor was capable of generating sufficient output signal to enable remote speed sensing from 1500 to 40000 rpm over a speed nut/sensor separation of 3.5 inches.

Wyett, L.↗
NASA NTRS1925

Aerodynamic Characteristics of Airfoils at High Speeds

This report deals with an experimental investigation of the aerodynamical characteristics of airfoils at high speeds. Lift, drag, and center of pressure measurements were made on six airfoils of the type used by the air service in propeller design, at speeds ranging from 550 to 1,000 feet per second. The results show a definite limit to the speed at which airfoils may efficiently be used to produce lift, the lift coefficient decreasing and the drag coefficient increasing as the speed approaches the speed of sound. The change in lift coefficient is large for thick airfoil sections (camber ratio 0.14 to 0.20) and for high angles of attack. The change is not marked for thin sections (camber ratio 0.10) at low angles of attack, for the speed range employed. At high speeds the center of pressure moves back toward the trailing edge of the airfoil as the speed increases. The results indicate that the use of tip speeds approaching the speed of sound for propellers of customary design involves a serious loss in efficiency.

Briggs, L J↗
NASA NTRS1994

Handling qualities of the High Speed Civil Transport

The low speed handling qualities of a High Speed Civil Transport class aircraft have been investigated by using data of the former Advanced Supersonic Transport (AST) 105. The operation of such vehicles in the airport terminal area is characterized by 'backside' performance. Main objectives of this research effort were: (Q) determination of the nature and magnitude of the speed instability associated with the backside of the thrust required curve; (2) confirmation of the validity of existing MIL-SPEC handling qualities criteria; (3) safety of operation of the vehicle in the event of autothrottle failure; and (4) correlation of required engine responsiveness with level of speed instability. Preliminary findings comprise the following: (1) The critical velocity for speed instability was determined to be 196 knots, well above the projected approach speed of 155 knots. This puts the vehicle far on the backside of its thrust required curve. While the aircraft can be configured to have static and dynamic stability at this trim point, a significant speed instability emerges, if a pilot or autopilot attempts flight path control with elevator and/or canard control surfaces only. This requires a properly configured autothrottle and/or variable aerodynamic drag devices which can provide speed stability; (2) An AST 105 type vehicle meets MIL-SPEC criteria only in part. While the damping criteria for phugoid and short period motion are met easily, the AST 105 falls short of the required minimum short period frequency, meaning that the HSCT is too sluggish in pitch to meet the military criteria. Obviously the military specification do not consider a vehicle with such high pitch inertia. With regard to speed stability and flight path stability criteria, the vehicle meets levels 2 and 3 of the military requirements, indicating that it would be landed safety with manual controls in case of an autothrottle failure, even though the pilot workload would be high; and (3) This requires quick thrust response to throttle adjustment, however. If the engine responsiveness is slow, the aircraft handling qualities are further deteriorated. Progress has been made in correlating required engine responses dyanmics with the given level of speed instability of the vehicle.

Solies, U. Peter↗
NASA NTRS1997

Speed Sensorless Induction Motor Drives for Electrical Actuators: Schemes, Trends and Tradeoffs

For a decade, induction motor drive-based electrical actuators have been under investigation as potential replacement for the conventional hydraulic and pneumatic actuators in aircraft. Advantages of electric actuator include lower weight and size, reduced maintenance and operating costs, improved safety due to the elimination of hazardous fluids and high pressure hydraulic and pneumatic actuators, and increased efficiency. Recently, the emphasis of research on induction motor drives has been on sensorless vector control which eliminates flux and speed sensors mounted on the motor. Also, the development of effective speed and flux estimators has allowed good rotor flux-oriented (RFO) performance at all speeds except those close to zero. Sensorless control has improved the motor performance, compared to the Volts/Hertz (or constant flux) controls. This report evaluates documented schemes for speed sensorless drives, and discusses the trends and tradeoffs involved in selecting a particular scheme. These schemes combine the attributes of the direct and indirect field-oriented control (FOC) or use model adaptive reference systems (MRAS) with a speed-dependent current model for flux estimation which tracks the voltage model-based flux estimator. Many factors are important in comparing the effectiveness of a speed sensorless scheme. Among them are the wide speed range capability, motor parameter insensitivity and noise reduction. Although a number of schemes have been proposed for solving the speed estimation, zero-speed FOC with robustness against parameter variations still remains an area of research for speed sensorless control.

Elbuluk, Malik E.↗
NASA NTRS1950

Effect of Various Modifications on Drag and Longitudinal Stability and Control Characteristics at Transonic Speeds of a Model of the XF7U-1 Tailless Airplane: NACA Wing-FLow Method, TED No. NACA DE 307

An investigation was made by the NACA wing-flow method to determine the drag, pitching-moment, lift, and angle-of-attack characteristics at transonic speeds of various configurations of a semispan model of an early configuration of the XF7U-1 tailless airplane. The results of the tests indicated that for the basic configuration with undeflected ailavator, the zero-lift drag rise occurred at a Mach number of about 0.85 and that about a five-fold increase in drag occurred through the transonic speed range. The results of the tests also indicated that the drag increment produced by -8.0 degrees deflection of the ailavator increased with increase in normal-force coefficient and was smaller at speeds above than at speeds below the drag rise. The drag increment produced by 35 degree deflection of the speed brakes varied from 0.040 to 0.074 depending on the normal-force coefficient and Mach number. These values correspond to drag coefficients of about 0.40 and 0.75 based on speed-brake frontal area. Removal of the fin produced a small positive drag increment at a given normal-force coefficient at speeds during the drag rise. A large forward shift of the neutral-point location occurred at Mach numbers above about 0.90 upon removal of the fin, and also a considerable forward shift throughout the Mach number range occurred upon deflection of the speed brakes. Ailavator ineffectiveness or reversal at low deflections, similar to that determined in previous tests of the basic configuration of the model in the Mach number range from about 0.93 to 1.0, was found for the fin-off configuration and for the model equipped with skewed (more highly sweptback) hinge-line ailavators. With the speed brakes deflected, little or no loss in the incremental pitching moment produced by deflection of the ailavator from O degrees to -8.00 degrees occurred in the Mach number range from 0.85 to 1.0 in contrast to a considerable loss found in previous tests with the speed brakes off.

Sawyer, Richard H.↗
NASA NTRS2005

Drive Motor Improved for 8- by 6-Foot Supersonic Wind Tunnel/9- by 15-Foot Low-Speed Wind Tunnel Complex

An operational change made recently in the drive motor system for the 8- by 6-Foot Supersonic Wind Tunnel (8x6 SWT)/9- by 15-Foot Low-Speed Wind Tunnel (9x15 LSWT) complex resulted in dramatic power savings and expanded operating range. The 8x6 SWT/9x15 LSWT complex offers a unique combination of wind tunnel conditions for both high- and low-speed testing. Prior to the work discussed in this article, the 8- by 6-ft test section offered airflows ranging from Mach 0.36 to 2.0. Subsonic testing was done in the 9-ft high, 15-ft wide test area in the return leg of the facility. The air speed in this test section can range from 0 to 175 mph (Mach 0.23). In the past, we varied the air speed by using a combination of the compressor speed and the position of the tunnel flow-control doors. When very slow speeds were required in the 9x15 LSWT, these large tunnel flow control doors might be very nearly full open, bleeding off large quantities of air, even with the drive system operating at its previous minimum speed of about 510 rpm. Power drawn during this mode of operation varied between 15 and 18 MW/hr, but clearly much of this power was not being used to provide air that would be used for testing in the test section. The air exiting these large doors represented wasted power. Early this year, the facility's tunnel drive system was run on one motor instead of three to see if lower drive speeds could be achieved that would, in turn, result in large power savings because unnecessary air would not be blown out of the flow-control doors unnecessarily. In addition, if the drive could be run slower, then slower speeds would also be possible in the 8x6 SWT test section as an added benefit. Results of the first tests performed early last year showed that in fact the drive, when operating on only one motor, actually reached a steady-state speed of only 337 rpm and drew an amazingly small 6 MW/hr of electrical power. During daytime operation of the drive, this meant that it would be possible to save as much as 10 MW/hr, or nearly $600 per hour of operation, for many of the 9x15 LSWT's testing regimes. An added benefit of this power-saving venture was that since the 8x6 SWT and 9x15 LSWT are indeed on a common loop, if the compressor is slowed down to benefit the 9x15 LSWT, then the air moving through the 8x6 SWT is also moving slower than ever before. In fact, testing has proven that the 8x6 SWT can now achieve Mach 0.25, whereas its previous lower limit was Mach 0.36. This added benefit has attracted additional customers

Source record↗
NASA NTRS2004

Stereomotion speed perception: contributions from both changing disparity and interocular velocity difference over a range of relative disparities

The role of two binocular cues to motion in depth-changing disparity (CD) and interocular velocity difference (IOVD)- was investigated by measuring stereomotion speed discrimination and static disparity discrimination performance (stereoacuity). Speed discrimination thresholds were assessed both for random dot stereograms (RDS), and for their temporally uncorrelated equivalents, dynamic random dot stereograms (DRDS), at relative disparity pedestals of -19, 0, and +19 arcmin. While RDS stimuli contain both CD and IOVD cues, DRDS stimuli carry only CD information. On average, thresholds were a factor of 1.7 higher for DRDS than for RDS stimuli with no clear effect of relative disparity pedestal. Results were similar for approaching and receding targets. Variations in stimulus duration had no significant effect on thresholds, and there was no observed correlation between stimulus displacement and perceived speed, confirming that subjects responded to stimulus speed in each condition. Stereoacuity was equally good for our RDS and DRDS stimuli, showing that the difference in stereomotion speed discrimination performance for these stimuli was not due to any difference in the precision of the disparity cue. In addition, when we altered stereomotion stimulus trajectory by independently manipulating the speeds and directions of its monocular half-images, perceived stereomotion speed remained accurate. This finding is inconsistent with response strategies based on properties of either monocular half-image motion, or any ad hoc combination of the monocular speeds. We conclude that although subjects are able to discriminate stereomotion speed reliably on the basis of CD information alone, IOVD provides a precise additional cue to stereomotion speed perception.

Depth Perception/physiology↗
NASA NTRS2006

Solar Wind Helium Abundance as a Function of Speed and Heliographic Latitude: Variation through a Solar Cycle

We present a study of the variation of the relative abundance of helium to hydrogen in the solar wind as a function of solar wind speed and heliographic latitude over the previous solar cycle. The average values of A(sub He), the ratio of helium to hydrogen number densities, are calculated in 25 speed intervals over 27-day Carrington rotations using Faraday Cup observations from the Wind spacecraft between 1995 and 2005. The higher speed and time resolution of this study compared to an earlier work with the Wind observations has led to the discovery of three new aspects of A(sub He), modulation during solar minimum from mid-1995 to mid-1997. First, we find that for solar wind speeds between 350 and 415 km/s, A(sub He), varies with a clear six-month periodicity, with a minimum value at the heliographic equatorial plane and a typical gradient of 0.01 per degree in latitude. For the slow wind this is a 30% effect. We suggest that the latitudinal gradient may be due to an additional dependence of coronal proton flux on coronal field strength or the stability of coronal loops. Second, once the gradient is subtracted, we find that A(sub He), is a remarkably linear function of solar wind speed. Finally, we identify a vanishing speed, at which A(sub He), is zero, is 259 km/s and note that this speed corresponds to the minimum solar wind speed observed at one AU. The vanishing speed may be related to previous theoretical work in which enhancements of coronal helium lead to stagnation of the escaping proton flux. During solar maximum the A(sub He), dependences on speed and latitude disappear, and we interpret this as evidence of two source regions for slow solar wind in the ecliptic plane, one being the solar minimum streamer belt and the other likely being active regions.

Kasper, J. C.↗
NASA NTRS2024

High Spectral Resolution Lidar – Generation 2 (HSRL-2) Retrievals of Ocean Surface Wind Speed: Methodology and Evaluation

Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of −0.13 and −1.05 m s−1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 m s−1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 m s−1, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 m s−1 and between 7 and 13.3 m s−1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 m s−1 and an error of ∼ 1.5 m s−1, a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (−0.18 ± 1.52 m s−1) than in the winter (0.63 ± 2.07 m s−1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets.

Sanja Dmitrovic↗
DOE OSTI2020

How Should Machine Learning Be Successfully Used for Wind Speed Vertical Extrapolation?

An accurate characterization of the wind resource available at hub-height is required for an efficient and bankable wind farm project. However, direct measurement of wind speed at the constantly increasing height of the hub of commercial wind turbines is oftentimes challenging and expensive, so that it is common practice to vertically extrapolate the wind resource from lower and more easily accessible levels. Conventional techniques for wind speed vertical extrapolation include the use of a power law and a logarithmic profile. While simple, the limits in accuracy of these methods have been shown in various studies. Recently, machine learning has been proposed as a new method to vertically extrapolate winds. All the published studies on the topic assess the performance of machine learning techniques in vertically extrapolating the wind resource at the same location where the algorithm has been trained. However, in real-world applications, the wind resource is measured at the instrument location, but it then needs to be extrapolated at hub height at the location of the wind turbines within the find farm. To be able to fully recommend the use of machine learning techniques over the simple power law and logarithmic law, the spatial variability of the performance improvements of the machine learning approaches needs to be assessed. Here, we propose a round-robin validation of a machine learning-based method for wind speed extrapolation. We use 20 months of observations at four locations spanning a 100 km wide region at the Southern Great Plains (SGP) atmospheric observatory, in north-central Oklahoma. At each location, we train a random forest to predict 30-min average wind speed at 143 m AGL. We use as input features lidar wind speed at 65 m AGL, time of day, sonic anemometer wind speed at 4 m AGL, turbulent kinetic energy, and Obukhov length. First, we perform a same-site comparison of the performance of the proposed random forest against the conventional techniques for wind speed extrapolation (namely power law and logarithmic profile, with widely accepted stability corrections). We find that the random forest outperforms the power law in vertically extrapolating wind speed in all the considered stability regimes, with a 33% reduction in MAE for stable conditions, and a 31% reduction in unstable conditions. Similar results are found when comparing predictions of extrapolated winds from the logarithmic profile and the random forest with the observed values. Next, we propose a round-robin validation, to use the random forest trained at each site to extrapolate wind speed at the remaining three sites. We find that the performance of the random forest approach degrades when the algorithm is tested at a site different than the training one. However, even under those circumstances, the machine learning-based approach still outperforms the conventional techniques for wind speed extrapolation, with, on average, a reduction in mean absolute error between 15 and 20% over the conventional methods, with the largest benefits obtained under stable conditions.

Monte Carlo↗