Wind Velocity Estimation Research Articles

Uncertainties in the evaluation of one degree-of-freedom galloping onset

This study discusses the uncertainties inherent in the galloping onset conditions of wind-excited structural elements using error propagation techniques. The problem is dealt with considering two different technical situations: the estimate of the critical wind velocity for engineering applications and the assessment of the galloping factor derived from wind tunnel experiments over a specific structural element. In the former case, significant errors may arise from the scattering of the whole set of involved parameters. In the latter case, it is shown that the galloping factor obtained in the wind tunnel test is a random variable, unavoidably affected by uncertainties due to measuring errors and its estimation technique. In both cases, it is shown that the classic deterministic approach based on nominal values of the parameters may lead to unsafe estimations of the one degree-of-freedom galloping onset.

Оценка средней скорости ветра из корреляции смещений центров тяжести изображений некогерентных источников в турбулентной атмосфере

Оценка средней скорости ветра из корреляции смещений центров тяжести изображений некогерентных источников в турбулентной атмосфере

Оценивание интегральной скорости ветра и турбулентности в атмосфере по искажениям видеоизображений естественно освещенных объектов

Оценивание интегральной скорости ветра и турбулентности в атмосфере по искажениям видеоизображений естественно освещенных объектов

Development and Operational Analysis of an All-Fiber Coherent Doppler Lidar System for Wind Sensing and Aerosol Profiling

A 1.5- $\mu\mbox{m}$ all-fiber coherent Doppler lidar system for wind sensing was developed and characterized. The system design and implementation is presented. The system employs a 20-kHz pulse repetition rate transmitter and samples return signals at 400 MHz. A field-programmable gate array is programmed to generate and accumulate real-time periodograms representing average power spectra of the Doppler shifted echo from a series of more than 60 range gates, where each range gate is 48 m. The accumulated periodograms are streamed to a host computer for subsequent processing to yield the line-of-sight wind velocity. Wind velocity estimates with a precision value of 0.08 m/s can be made under nominal aerosol loading and nominal atmospheric turbulence conditions for ranges up to 3 km. Wind velocities and aerosol profiles are obtained while scanning the pointing direction of the lidar, thus producing both horizontal and vertical representations of the wind vectors.

Impact of Ocean Wave Height on L-band Passive and Active Microwave Observation of Sea Surfaces

The impact of ocean waves on L-band brightness temperatures and backscatter from the ocean surface was analyzed using Aquarius data. Matchups of Aquarius data with significant wave height (SWH) from National Oceanic and Atmospheric Administration (NOAA) WaveWatch3 reanalysis and the ocean surface wind are generated. We perform the analysis using two different wind speed products: special sensor microwave imager/sounder (SSMI/S) and National Center for Environmental Prediction (NCEP) operational data. Interestingly, the influence of SWH manifests itself differently for these two wind speed products. Conditionally, averaged normalized radar cross-section ( ${\sigma _0}$ ) and brightness temperatures ( ${\text{T}}_{\text{B}}$ ) by NCEP wind speed show strong influence by SWH over the entire range of NCEP wind speeds with a larger impact at lower wind speeds. However, performing the same analysis conditioned on the SSMI/S wind speed, the conclusion becomes entirely different: the SWH effects appear small at low wind speeds ( ${ ) and increase with increasing wind speed. The apparent contradiction is a result of the differing characteristics of NCEP and SSMI/S wind speeds. NCEP wind is an atmospheric model estimate of surface wind velocity, whereas the SSMI/S wind is a microwave remote sensing product, representing the characteristics of sea surface roughness. The impact of SWH needs to be considered when the SSMI/S wind speed is assimilated into the numerical weather prediction models, such as the NCEP.

Autonomous Airdrop Systems Employing Ground Wind Measurements for Improved Landing Accuracy

Aerial cargo delivery, also known as airdrop, systems are heavily affected by atmospheric wind conditions. Guided airdrop systems typically employ onboard wind velocity estimation methods to predict the wind in real time as the systems descend, but these methods provide no foresight of the winds near the ground. Unexpected ground winds can result in large errors in landing location, and they can even lead to damage or complete loss of the cargo if the system impacts the ground while traveling downwind. This paper reports on a ground-based mechatronic system consisting of a cup and vane anemometer coupled to a guided airdrop system through a wireless transceiver. The guidance logic running on the airdrop system's onboard autopilot is modified to integrate the anemometer measurements at ground level near the intended landing zone with onboard wind estimates to provide an improved, real-time estimate of the wind profile. The concept was first developed in the framework of a rigorous simulation model and then validated in the flight test. Both simulation and subsequent flight tests with the prototype system demonstrate reductions in the landing position error by more than 30% as well as a complete elimination of potentially dangerous downwind landings.

Adaptive distributed Kalman filtering with wind estimation for astronomical adaptive optics.

In the framework of adaptive optics (AO) for astronomy, it is a common assumption to consider the atmospheric turbulent layers as "frozen flows" sliding according to the wind velocity profile. For this reason, having knowledge of such a velocity profile is beneficial in terms of AO control system performance. In this paper we show that it is possible to exploit the phase estimate from a Kalman filter running on an AO system in order to estimate wind velocity. This allows the update of the Kalman filter itself with such knowledge, making it adaptive. We have implemented such an adaptive controller based on the distributed version of the Kalman filter, for a realistic simulation of a multi-conjugate AO system with laser guide stars on a 30m telescope. Simulation results show that this approach is effective and promising and the additional computational cost with respect to the distributed filter is negligible. Comparisons with a previously published slope detection and ranging wind profiler are made and the impact of turbulence profile quantization is assessed. One of the main findings of the paper is that all flavors of the adaptive distributed Kalman filter are impacted more significantly by turbulence profile quantization than the static minimum mean square estimator which does not incorporate wind profile information.

Wavelet transform‐based methods for removal of ground clutter and denoising the radar wind profiler data

Various non-atmospheric signals contaminate radar wind profiler (RWP) data, which produce bias in estimation of moments and wind velocity. Especially, in ultra high frequency (UHF) RWPs, ground clutter severely degrades wind velocity estimation. Furthermore, at higher altitudes, noise dominates the clear air signal. Thus, the important tasks of signal processing in a RWP are (i) to eliminate the clutter signal, (ii) to detect the weak atmospheric signals buried inside the noise and (iii) to improve signal-to-noise ratio. Wavelet analysis is a powerful tool to differentiate the characteristics of the ground clutter and noise from the atmospheric turbulence echo at the time series level. The authors have implemented the signal processing for lower atmospheric wind profiler radar at National Atmospheric Research Laboratory, Gadanki, India, using wavelet transforms. In this study, they present the implementation approach and results. The wavelet-based algorithms use different threshold levels to identify and remove ground clutter and to denoise the data. The obtained results using this method are validated with collocated global positioning system radiosonde data.

Improved Moments Estimation for VHF Active Phased Array Radar Using Fuzzy Logic Method

AbstractVarious nonatmospheric signals contaminate radar wind profiler data, introducing bias into the moments and wind velocity estimation. This study applies a fuzzy logic–based method to Doppler velocity spectra to identify and eliminate the clutter echoes. This method uses mathematical analyses and a fuzzy inference system applied to each Doppler velocity spectrum to separate the atmospheric signals from the clutter. After eliminating the clutter, an adaptive algorithm is used to estimate mean Doppler velocities accurately. This combination of techniques is applied to the spectral data obtained by the newly developed 53-MHz active phased array radar located at the National Atmospheric Research Laboratory (NARL), Gadanki, India (13.5°N, 79°E). Winds derived using the conventional method and the method developed for this study are compared with those obtained by collocated GPS radiosonde. The comparison shows that the present method derives the winds more accurately compared to the conventional method.

실측 및 해석을 통한 단순 산악지형의 바람장 분포 연구

산림 화재는 여러 가지 변수를 포함하고 있지만 바람장에 의한 영향이 다른 어떠한 변수보다 상대적으로 크므로 봄철 산림지형에서의 풍향풍속을 알고 있다는 것은 산불진화기술 및 산불확산예측을 결정하는데 핵심 요소이다. 현재는 산림 지역의 풍향풍속 산정을 위하여 기상관측소의 데이터를 의존하게 된다. 기상청의 automatic weather station (AWS)는 넓은 지역에 골고루 분포하고 있어 비교적 간편하게 데이터를 취득할 수 있으나 실제 산림지역의 기상인자와는 차이가 있음을 확인하였다. 본 연구에서는 AWS가 설치되어 있지 않은 산악지형의 바람장을 실측하고 이를 통하여 바람장 예측의 가능성을 타진하였다. 실측 지형으로 단순 구릉 지형을 선택하여 주변의 지형지물에 의한 바람장의 왜곡을 최소화 하였으며, 이들 지형에서 바람장의 실측 및 전산유체해석을 통하여 얻어진 결과를 비교 분석하였다. 단순 구릉 지형으로는 제주도 오름과 안면도 마검포 지형을 선택하여 바람장 데이터를 취득 하였으며, 이를 분석한 결과 바람장의 패턴추출이 가능하다는 사실을 알 수 있었다. Forest fire has a number of variables and since the effects of wind fields are bigger than any other variables, it is essential to know wind direction and velocity for the forest fire extinguishing techniques and the prediction of fire spread. With regards to the local area that has a high chance of forest fire, the data from meteorological observatory in the area is used for the estimation of wind velocity. It is relatively easy to obtain automatic weather station (AWS) data which are available for the whole nation. There is a chance that the data from the weather station may be different with the actual data at the mountain areas. In this study simply shaped hills (Sae-byeol hill of Jeju Island and port Ma-geum in An-myeon Island in the sea side) were selected as the experimental locations to minimize the distortion of the wind field by the adjacent geographic features. Spot measurements and analysis of computational fluid dynamics (CFD) for the given geographic features were conducted to examine and compare their consistency. As a conclusion It is possible to predict wind patterns in these simple locations.

Meteor Trail Echo Rejection in Atmospheric Phased Array Radars Using Adaptive Sidelobe Cancellation

AbstractStrong meteor trail echoes are interferences in the wind velocity estimates made from mesosphere radar observations. Contaminated spectra are detected by their discontinuity and are removed at the risk of greater fluctuations of spectra, leading to a severe reduction of the signal-to-noise ratio (SNR) and inaccurate wind estimates for weak atmospheric echoes. This paper presents an adaptive signal processing technique for the suppression of spectral contaminations by meteor trail echoes. The method is based on the norm-constrained and directionally constrained minimization of power (NC-DCMP), which balances the capability of canceling the clutter and the robustness of beam shaping, at the cost of a slight decrease in the SNR, which can be determined in advance. Simulation results show that with a 3-dB decrease of the SNR being allowed, the method improves the signal-to-interference ratio (SIR) by 15 dB, giving wind estimates that are about 8 m s−1 better in terms of root-mean-square error and providing 4 times as wide an observable range when compared with the results of the ordinary nonadaptive beamforming method. The results for an actual observation show that the improvement of both the SIR and the observable range are achieved as in the simulations, which implies that the method should provide the simulated accuracy for the estimation of wind velocity from actual observations.

Improvement alternatives for determining the watertightness performance of building facades

The accurate determination of a facade's watertightness performance is important for optimizing design. Different micro-climatic conditions can affect water penetration. The recently developed Bayesian method allows this performance to be estimated for any operating condition and location, based on the results of standardized watertightness tests. This performance-based method uses semi-empirical calculations for wind-driven rain, estimates of wind velocity based on the wind profile power law and analyses of the annual maximum climatic data. This method determines the return period of climatic conditions that each facade system can withstand. Alternative approximations are studied that may be implemented using the Bayesian method to obtain more precise or functional estimations: improved friction coefficients, peaks-over-threshold analyses or catch ratios from computational fluid dynamics (CFD), among others. The effects of these alternatives on the results of the Bayesian method were evaluated by analysing different case studies in two cities in Spain. This analysis suggests that the original formulation of the method underestimates watertightness performance and highlights the fundamental importance of wind velocity to estimate the performance of any facade accurately. This will provide greater precision for estimating facade performance and provides potential for introducing performance-based codes for watertightness.

Estimate for the doppler shift of a non-Gaussian signal upon coherent detection of scattered optical radiation in a turbulent atmosphere

A non-Gaussian model for estimating the radial velocity of turbulent flows in the atmosphere for coherent detection of scattered optical radiation is proposed. The model was obtained based on a theoretical approach that includes results of the statistical analysis of a pulse Doppler lidar signal in a turbulent medium, as well as on the perturbation-theory methods that have been developed in the theory of probability and mathematical statistics. It is shown that the estimate of the Doppler shift in the first-order perturbation theory is a sum of a regular component and two conditional fluctuation components—Gaussian and non-Gaussian ones. In the case of a homogeneous and isotropic turbulence, the estimate of the radial wind velocity is approximately equal to its true average value. The statistical uncertainty in measurements of the average radial wind velocity is determined by the behavior of conditional Gaussian and non-Gaussian components and significantly depends on the state of atmospheric turbulence. It is shown that basic equations of the non-Gaussian model in the limit case coincide with formulas of the local and nonlocal models, as well as with those of the Gaussian model.

Designing laboratory wind simulations using artificial neural networks

While experiments in boundary layer wind tunnels remain to be a major research tool in wind engineering and environmental aerodynamics, designing the modeling hardware required for a proper atmospheric boundary layer (ABL) simulation can be costly and time consuming. Hence, possibilities are sought to speed-up this process and make it more time-efficient. In this study, two artificial neural networks (ANNs) are developed to determine an optimal design of the Counihan hardware, i.e., castellated barrier wall, vortex generators, and surface roughness, in order to simulate the ABL flow developing above urban, suburban, and rural terrains, as previous ANN models were created for one terrain type only. A standard procedure is used in developing those two ANNs in order to further enhance best-practice possibilities rather than to improve existing ANN designing methodology. In total, experimental results obtained using 23 different hardware setups are used when creating ANNs. In those tests, basic barrier height, barrier castellation height, spacing density, and height of surface roughness elements are the parameters that were varied to create satisfactory ABL simulations. The first ANN was used for the estimation of mean wind velocity, turbulent Reynolds stress, turbulence intensity, and length scales, while the second one was used for the estimation of the power spectral density of velocity fluctuations. This extensive set of studied flow and turbulence parameters is unmatched in comparison to the previous relevant studies, as it includes here turbulence intensity and power spectral density of velocity fluctuations in all three directions, as well as the Reynolds stress profiles and turbulence length scales. Modeling results agree well with experiments for all terrain types, particularly in the lower ABL within the height range of the most engineering structures, while exhibiting sensitivity to abrupt changes and data scattering in profiles of wind-tunnel results. The proposed approach allows for quicker and more effective achieving targeted flow and turbulence features of the ABL wind-tunnel simulations as compared to the common trial and error procedures. This methodology is expected to enable wind-tunnel modelers a quick and time-efficient designing of ABL simulations in studies dealing with air pollutant dispersion, wind loading of structures, wind energy, and urban micrometeorology, where atmospheric flow and turbulence play a key role.

A Low-Cost System for Measuring Horizontal Winds from Single-Engine Aircraft

Abstract The implementation and accuracy of a low-rate (~1 Hz) horizontal wind measurement system is described for a fixed-wing aircraft without modification to the airframe. The system is based on a global positioning system (GPS) compass that provides aircraft heading and a ground-referenced velocity, which, when subtracted from the standard true airspeed, provides estimates of the horizontal wind velocity. A series of tests was performed flying “L”-shaped patterns above the boundary layer, where the winds were assumed to be horizontally homogeneous over the area bounded by the flight (approximately 25 km2). Four headings were flown at each altitude at a constant airspeed. Scaling corrections for both heading and airspeed were found by minimizing the variance in the 1-s wind measurements; an upper limit to the error was then computed by calculating the variance of the corrected wind measurements on each of the four headings. A typical uncertainty found in this manner tends to be less than 0.2 m s−1. The measurement system described herein is inexpensive and relatively easy to implement on single-engine aircraft.

Solution of the Fokker–Planck equation in a wind turbine array boundary layer

Hot-wire velocity signals from a model wind turbine array boundary layer flow wind tunnel experiment are analyzed. In confirming Markovian properties, a description of the evolution of the probability density function of velocity increments via the Fokker–Planck equation is attained. Solution of the Fokker–Planck equation is possible due to the direct computation of the drift and diffusion coefficients from the experimental measurement data which were acquired within the turbine canopy. A good agreement is observed in the probability density functions between the experimental data and numerical solutions resulting from the Fokker–Planck equation, especially in the far-wake region. The results serve as a tool for improved estimation of wind velocity within the array and provide evidence that the evolution of such a complex and turbulent flow is also governed by a Fokker–Planck equation at certain scales.

Estimation of the OSCAT Spatial Response Function Using Island Targets

Originally designed for wind velocity estimation over the ocean, scatterometers have been applied to weather forecasting, global climatological studies, and monitoring of large-scale human interaction on the planet. Launched in September of 2009, the Oceansat-2 Ku-band scatterometer (OSCAT) is an excellent candidate for continuing the data time series begun with QuikSCAT, which was the SeaWinds scatterometer flown on the QuikSCAT mission 1999-2009. Some processing algorithms require knowledge of the spatial response function (SRF) of the scatterometer. With limited knowledge of OSCAT implementation, and thus its SRF, a procedure is developed for estimating the SRF. The estimation procedure uses scatterometer measurements over islands to invert the radar equation. A mathematical model is developed that reduces the solution to rank-reduced least-squares estimation. The geographic sampling region is discussed, and a simulation is performed to verify the efficacy of the method, while also providing guidelines for island choice and the number of singular values used in rank reduction. The utility of OSCAT SRF estimates is demonstrated through the construction of an enhanced-resolution radar backscatter image over the Amazon rainforest.

1004 レンズ風車によるBetz限界の超越に向けて

The new type of diffuser augmented wind turbine (DAWT) called "wind-lens turbine" has been developed. The wind-lens turbine has a diffuser with brim called "wind-lens", by which the wind concentration on the turbine rotor and the significant enhancement of the turbine output can be achieved. A wind-lens turbine which has the higher output power coefficient than the Betz limit and other DAWTs has been developed. The reasons that the wind-lens turbine achieved higher output power coefficient than those of others are the wind-lens turbine was designed with the appropriately estimated wind velocity at the rotor inlet and the optimization method has been applied to the aerodynamic design of the wind-lens turbine.

WSR-88D doppler radar detection of corn earworm moth migration

Corn earworm (Lepidoptera: Noctuidae) (CEW) populations infesting one crop production area may rapidly migrate and infest distant crop production areas. Although entomological radars have detected corn earworm moth migrations, the spatial extent of the radar coverage has been limited to a small horizontal view above crop production areas. The Weather Service Radar (version 88D) (WSR-88D) continuously monitors the radar-transmitted energy reflected by, and radial speed of, biota as well as by precipitation over areas that may encompass crop production areas. We analyzed data from the WSR-88D radar (S-band) at Brownsville, Texas, and related these data to aerial concentrations of CEW estimated by a scanning entomological radar (X-band) and wind velocity measurements from rawinsonde and pilot balloon ascents. The WSR-88D radar reflectivity was positively correlated (r2=0.21) with the aerial concentration of corn earworm-size insects measured by a scanning X-band radar. WSR-88D radar constant altitude plan position indicator estimates of wind velocity were positively correlated with wind speed (r2=0.56) and wind direction (r2=0.63) measured by pilot balloons and rawinsondes. The results reveal that WSR-88D radar measurements of insect concentration and displacement speed and direction can be used to estimate the migratory flux of corn earworms and other nocturnal insects, information that could benefit areawide pest management programs. In turn, identification of the effects of spatiotemporal patterns of migratory flights of corn earworm-size insects on WSR-88D radar measurements may lead to the development of algorithms that increase the accuracy of WSR-88D radar measurements of reflectivity and wind velocity for operational meteorology.

Noise cancellation in Doppler moment estimation of array weather radar signals using lifted biorthogonal wavelets

A new approach to estimate wind velocity and spectral width for weather radar is presented. In this paper, we deal with spectrum estimation and moments estimation of the received signal with a phased array Doppler weather radar. The lifted wavelet transform is applied on the estimated power spectral density prior to estimate the wind features (velocity, direction, spectral width). We apply the soft thresholding strategy on the lifted wavelet transform coefficients using the well-known minimax threshold as first guess. We estimate the velocity and the corresponding spectral width. We, iteratively, threshold the detail signal, in the wavelet domain, using an incremented threshold value until we obtain (using a stopping test) the optimal value of the initial threshold (minimax). In the first stage of the work, we have chosen a radar model used for meteorology to generate synthetic data on which we applied our algorithm. In the second stage, we used actual data got from the real radar that we used as model. The probative results we got with synthetic data are strengthened by the results obtained by the actual data.