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Results for “wake characterization”

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 19 records

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

17 WIND ENERGY↗

Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns

In this article, we provide a methodological framework for designing the scanning strategies of nacelle-mounted scanning lidars for wind energy field experiments, and apply it at two major experimental field campaigns. For the Rotor Aerodynamics, Aeroelastics, and Wake project (RAAW), we leverage two scanning lidars on one turbine to characterize the incoming turbulence and the turbine wake. For the American WAKE experimeNt (AWAKEN), we use four scanning lidars on top of four turbines in a large wind power plant to investigate both individual wakes and wind-plant-scale flow features.

17 WIND ENERGY↗

Region-based convolutional neural network for wind turbine wake characterization from scanning lidars

A convolutional neural network is applied to lidar scan images from three experimental campaigns to identify and characterize wind turbine wakes. Initially developed as a proof-of-concept model and applied to a single data set in complex terrain, the model is now improved and generalized and applied to two other unique lidar data sets, one located near an escarpment and one located offshore. The model, initially developed using lidar scans collected in predominantly westerly flow, exhibits sensitivity to wind flow direction. The model is thus successfully generalized through implementing a standard rotation process to scan images before input into the convolutional neural network to ensure the flow is westerly. The sample size of lidar scans used to train the model is increased, and along with the generalization process, these changes to the model are shown to enhance accuracy and robustness when characterizing dissipating and asymmetric wakes. Applied to the offshore data set in which nearly 20 wind turbine wakes are included per scan, the improved model exhibits a 95% success rate in characterizing wakes and a 74% success rate in characterizing dissipating wake fragments. The improved model is shown to generalize well to the two new data sets, although an increase in wake characterization accuracy is offset by an increase in model sensitivity and false positive wake identifications.

17 WIND ENERGY↗

Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.

17 WIND ENERGY↗

Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models

Abstract. Wake measurements of a scanning Doppler lidar mounted on the nacelle of a full-scale wind turbine during a wake-steering experiment were used for the characterization of the wake flow, the evaluation of the wake-steering set-up, and the validation of analytical wake models. Inflow-scanning Doppler lidars, a meteorological mast, and the supervisory control and data acquisition (SCADA) system of the wind turbine complemented the set-up. Results from the wake-scanning Doppler lidar showed an increase in the wake deflection with the yaw angle and that the wake deflection was not in all cases beneficial for the power output of a downstream turbine due to a bias of the inflow wind direction perceived by the yawed wind turbine and the wake-steering design implemented. Both observations could be reproduced with an analytical model that was initialized with the inflow measurements. Error propagation from the inflow measurements that were used as model input and the power coefficient of a waked wind turbine contributed significantly to the model uncertainty. Lastly, the span-wise cross section of the wake was strongly affected by wind veer, masking the effects of the yawed wind turbine on the wake cross sections.

17 WIND ENERGY↗

Hypersonic rarefied wake characterization

Results of a numerical study using the direct simulation Monte Carlo (DSMC) method are presented for hypersonic rarefied flow over an aeroassisted space transfer vehicle (ASTV). The emphasis of the study is the characterization of the near wake region which includes the ASTV payload. The study covered the transitional flow regime from near continuum to free molecular. Calculations show that the character of the near wake is significantly affected by the presence of the payload. Flow separation occurs when an afterbody is present throughout the transitional flow regime. In contrast, when no afterbody is present, no separation is observed until the flow approaches continuum.

Brewer, E. B.↗

Performance and Wake Characterization of a Model Hydrokinetic Turbine: The Reference Model 1 (RM1) Dual Rotor Tidal Energy Converter

The mechanical power and wake flow field of a 1:40 scale model of the US Department of Energy’s Reference Model 1 (RM1) dual rotor tidal energy converter are characterized in an open-channel flume to evaluate power performance and wake flow recovery. The NACA-63(4)-24 hydrofoil profile in the original RM1 design is replaced with a NACA-4415 profile to minimize the Reynolds dependency of lift and drag characteristics at the test chord Reynolds number. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADV) aligned with each rotor centerline and the midpoint between the rotor axes. Flow conditions for each case were controlled to maintain a hub height velocity, uhub= 1.04 ms−1, a flow Reynolds number, ReD= 4.4 × 105, and a blade chord length Reynolds number, Rec= 3.1 × 105. Performance was measured for a range of tip-speed ratios by varying rotor angular velocity. Peak power coefficients, CP= 0.48 (right rotor) and CP= 0.43 (left rotor), were observed at a tip speed ratio, λ= 5.1. Vertical velocity profiles collected in the wake of each rotor between 1 and 10 rotor diameters are used to estimate the turbulent flow recovery in the wake, as well as the interaction of the counter-rotating rotor wakes. The observed performance characteristics of the dual rotor configuration in the present study are found to be similar to those for single rotor investigations in other studies. Similarities between dual and single rotor far-wake characteristics are also observed.

30 DIRECT ENERGY CONVERSION↗

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗

Recent NASA Wake-Vortex Flight Tests, Flow-Physics Database and Wake-Development Analysis

A series of flight tests over the ocean of a four engine turboprop airplane in the cruise configuration have provided a data set for improved understanding of wake vortex physics and atmospheric interaction. An integrated database has been compiled for wake characterization and validation of wake-vortex computational models. This paper describes the wake-vortex flight tests, the data processing, the database development and access, and results obtained from preliminary wake-characterization analysis using the data sets.

Vicroy, Dan D.↗

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗

Characterizing the wake vortex signature for an active line of sight remote sensor

A recurring phenomenon, described as a wake vortex, develops as an aircraft approaches the runway to land. As the aircraft moves along the runway, each of the wing tips generates a spiraling and expanding cone of air. During the lifetime of this turbulent event, conditions exist over the runway which can be hazardous to following aircraft, particularly when a small aircraft is following a large aircraft. Left to themselves, these twin vortex patterns will converge toward each other near the center of the runway, harmlessly dissipating through interaction with each other or by contact with the ground. Unfortunately, the time necessary to disperse the vortex is often not predictable, and at busy airports can severely impact terminal area productivity. Rudimentary methods of avoidance are in place. Generally, time delays between landing aircraft are based on what is required to protect a small aircraft. Existing ambient wind conditions can complicate the situation. Reliable detection and tracking of a wake vortex hazard is a major technical problem which can significantly impact runway productivity. Landing minimums could be determined on the basis of the actual hazard rather than imposed on the basis of a worst case scenario. This work focuses on using a windfield description of a wake vortex to generate line-of-sight Doppler velocity truth data appropriate to an arbitrarily located active sensor such as a high resolution radar or lidar. The goal is to isolate a range Doppler signature of the vortex phenomenon that can be used to improve detection. Results are presented based on use of a simplified model of a wake vortex pattern. However, it is important to note that the method of analysis can easily be applied to any vortex model used to generate a windfield snapshot. Results involving several scan strategies are shown for a point sensor with a range resolution of 1 to 4 meters. Vortex signatures presented appear to offer potential for detection and tracking.

Heil, Robert Milton↗

Flight Data Reduction of Wake Velocity Measurements Using an Instrumented OV-10 Airplane

A series of flight tests to measure the wake of a Lockheed C- 130 airplane and the accompanying atmospheric state have been conducted. A specially instrumented North American Rockwell OV-10 airplane was used to measure the wake and atmospheric conditions. An integrated database has been compiled for wake characterization and validation of wake vortex computational models. This paper describes the wake- measurement flight-data reduction process.

Vicroy, Dan D.↗

Follow-on Low Noise Fan Aerodynamic Study

The focus of the project was to investigate the effects of turbulence models on the prediction of rotor wake structures. The Advanced Ducted Propfan Analysis (ADPAC) code was modified through the incorporation of the Spalart-Allmaras one-equation turbulence model. Suitable test cases were solved numerically using ADPAC employing the Spalart-Allmaras turbulence model and another prediction code for comparison. A near-wall spacing study was also completed to determine the adequate spacing of the first computational cell off the wall. Solutions were also collected using two versions of the algebraic Baldwin-Lomax turbulence model in ADPAC. The effects of the turbulence model on the rotor wake definition was examined by obtaining ADPAC solutions for the Low Noise Fan rotor-only steady-flow case using the standard algebraic Baldwin-Lomax turbulence model, a modified version of the Baldwin-Lomax turbulence model and the one-equation Spalart-Allmaras turbulence model. The results from the three different turbulence modeling techniques were compared with each other and the available experimental data. These results include overall rotor performance, spanwise exit profiles, and contours of axial velocity taken along constant axial locations and along blade-to-blade surfaces. Wake characterizations were also performed on the experimental and ADPAC predicted results including the definition of a wake correlation function. Correlations were evaluated for wake width and wake depth. Similarity profiles of the wake shape were also compared between all numerical solutions and experimental data.

Heidegger, Nathan J.↗

Coherent Pulsed Lidar Sensing of Wake Vortex Position and Strength, Winds and Turbulence in the Terminal Area

NASA Langley Research Center (LaRC) has field tested a 2.0 gm, 100 Hertz, pulsed coherent lidar to detect and characterize wake vortices and to measure atmospheric winds and turbulence. The quantification of aircraft wake-vortex hazards is being addressed by the Wake Vortex Lidar (WVL) Project as part of Aircraft Vortex Spacing System (AVOSS), which is under the Reduced Spacing Operations Element of the Terminal Area Productivity (TAP) Program. These hazards currently set the minimum, fixed separation distance between two aircraft and affect the number of takeoff and landing operations on a single runway under Instrument Meteorological Conditions (IMC). The AVOSS concept seeks to safely reduce aircraft separation distances, when weather conditions permit, to increase the operational capacity of major airports. The current NASA wake-vortex research efforts focus on developing and validating wake vortex encounter models, wake decay and advection models, and wake sensing technologies. These technologies will be incorporated into an automated AVOSS that can properly select safe separation distances for different weather conditions, based on the aircraft pair and predicted/measured vortex behavior. The sensor subsystem efforts focus on developing and validating wake sensing technologies. The lidar system has been field-tested to provide real-time wake vortex trajectory and strength data to AVOSS for wake prediction verification. Wake vortices, atmospheric winds, and turbulence products have been generated from processing the lidar data collected during deployments to Norfolk (ORF), John F. Kennedy (JFK), and Dallas/Fort Worth (DFW) International Airports.

Brockman, Philip↗

Evaluation of Fast-Time Wake Vortex Models using Wake Encounter Flight Test Data

This paper describes a methodology for the integration and evaluation of fast-time wake models with flight data. The National Aeronautics and Space Administration conducted detailed flight tests in 1995 and 1997 under the Aircraft Vortex Spacing System Program to characterize wake vortex decay and wake encounter dynamics. In this study, data collected during Flight 705 were used to evaluate NASA's fast-time wake transport and decay models. Deterministic and Monte-Carlo simulations were conducted to define wake hazard bounds behind the wake generator. The methodology described in this paper can be used for further validation of fast-time wake models using en-route flight data, and for determining wake turbulence constraints in the design of air traffic management concepts.

Ahmad, Nashat N.↗