Non-stationary Wind Research Articles

AStrion data validation of non-stationary wind turbine signals

AStrion data validation of non-stationary wind turbine signals

Effect of Gusty Wind on Road Tunnel Safety

The article deals with the effect of wind with its characteristics on the longitudinal ventilation of a road tunnel as a key segment of fire safety. Using CFD simulations, the influence of wind gusts, which differ and is more difficult to define than the influence of a constant wind on tunnel ventilation, is researched in more detail. On the basis of the simulation results, which have been validated with real measures, the findings are presented regarding the importance of taking into account the characteristics of non-stationary wind to ensure the adequate safety of tunnel users in the event of a fire, as well as of fire-fighting units during intervention.

Analysis of Nonstationary Wind Fluctuations Using the Hilbert-Huang Transform

AbstractClimatological patterns in wind fluctuations on time scales of 1–10 h are analyzed at a meteorological mast at the Yangmeishan wind farm, Yunnan Province, China, using a 2-yr time series of 10-min wind speed observations. For analyzing the spectral properties of nonstationary wind fluctuations in mountain terrain, the Hilbert-Huang transform (HHT) is applied to investigate climatological patterns between wind variability and several variables including time of year, time of day, wind direction, and pressure tendency. Compared with that for offshore sites, the wind variability at Yangmeishan wind farm has a more distinct diurnal cycle, but the seasonal discrepancies and the differences according to directions are not distinct, and the synoptic influences on wind variability are weaker. There is enhanced variability in spring and winter compared with summer and autumn. For flow from the main direction sector, the maximum wind variability is observed in spring. And the severe wind fluctuations are mo...

Extended modulating functions for simulation of wind velocities with weak and strong nonstationarity

Following the theory of evolutionary power spectral density (EPSD) for nonstationary processes, it is anticipated that the nonstationary wind velocities can be generated through modulating the stationary wind velocities by resorting to desirable modulating functions. Naturally, the key to the simulation of the nonstationary wind velocities lies in seeking out desirable modulating functions. The purpose of this study thus is how to obtain the modulating functions suitable for modulating stationary wind velocities. This work begins with systematically deducing the modulating function according to Kaimal power spectrum. The modulating functions corresponding respectively to other power spectra are subsequently presented. Derived modulating functions herein are collectively referred to as the extended modulating functions (EMFs). Employing the recent research by Li et al. (2009) that integration of both the spline interpolation algorithm (SIA) and spectral representation (SR) method, then forming the SIA-SR method, is able to remarkably reduce the increasing number of Cholesky decomposition of the time-varying spectral density matrix, the simulation of the nonstationary wind velocities has been carried out with an EMF. It can be inferred in terms of simulation results that the EMFs can fully capture the nonstationarity of wind velocities, including both the weak and strong nonstationary wind velocities.

Electromagnetic suspension in vertical axial wind-driven generators

To make a case for using electromagnetic suspension in vertical axial wind-driven generators, approximate evaluations of main design parameters of electromagnetic bearings of the wind-driven generator and their proper power consumption level are made. The functionality of the electromagnetic suspension is proven by calculations of dynamic modes of wind rotors of different types under nonstationary wind load.

Network of flexible capacitive strain gauges for the reconstruction of surface strain

Monitoring of surface strain on mesosurfaces is a difficult task, often impeded by the lack of scalability of conventional sensing systems. A solution is to deploy large networks of flexible strain gauges, a type of large area electronics. The authors have recently proposed a soft elastomeric capacitor (SEC) as an economical skin-type solution for large-scale deployment onto mesosurfaces. The sensing principle is based on a measurable change in the sensor’s capacitance upon strain. In this paper, we study the performance of the sensor at reconstructing surface strain map and deflection shapes. A particular feature of the sensor is that it measures surface strain additively, because it is not utilized within a Wheatstone bridge configuration. An algorithm is proposed to decompose the additive in-plane strain measurements from the SEC into principal components. The algorithm consists of assuming a polynomial shape function, and deriving the strain based on Kirchhoff plate theory. A least-squares estimator (LSE) is used to minimize the error between the assumed model and the SEC signals after the enforcement of boundary conditions. Numerical simulations are conducted on a symmetric rectangular cantilever thin plate under symmetric and asymmetric static loads to demonstrate the accuracy and real-time applicability of the algorithm. The performance of the algorithm is further examined on an asymmetric cantilever laminated thin plate constituted with orthotropic materials mimicking a wind turbine blade, and subjected to a non-stationary wind load. Results from simulations show good performance of the algorithm at reconstructing the surface strain maps for both in-plane principal strain components, and that it can be applied in real time. However, its performance can be improved by strengthening assumptions on boundary conditions. The algorithm exhibits robustness in performance with respect to load and noise in signals, except when most of the sensors’ signals are close to zero due to over-fitting form the LSE.

Derivation of time-varying mean for non-stationary downburst winds

Non-stationary extreme winds cause significant damages to buildings and other structures worldwide. Accurate modeling of these winds is crucial to the evaluation of structural safety. However, the derivation of a reasonable time-varying mean for these extreme winds appears to be not straightforward due to the non-stationarity, which is different from the stationary boundary layer winds. Currently, a variety of techniques have been developed to derive the time-varying mean for non-stationary winds, such as moving average, kernel regression (KR), discrete wavelet transform (DWT) and empirical mode decomposition (EMD). However, these approaches with different parameters may lead to inconsistent time-varying means and ensuing fluctuations. The evaluation of these approaches and corresponding non-stationary wind effects on structures has not been sufficiently addressed in previous research. In this study, two sets of full-scale non-stationary downburst wind records are used as examples to evaluate the performance of three approaches including KR, DWT and ensemble EMD with different time window sizes in deriving the time-varying mean. Based on these evaluations, the recommendations about the selection of the appropriate approach and time window size to derive a reasonable time-varying mean are provided.

Spectrum Models for Nonstationary Extreme Winds

AbstractNonstationary extreme winds are responsible for many structural damages. However, empirical models are not available for these winds, especially for fluctuations, mainly due to the difficulties in mathematical treatments. In this study, nonstationary wind characteristics are studied and analytic models are also proposed based on field measurements of wind speeds. Firstly, the discrete wavelet transform and kernel regression method are used to infer the time-varying mean and variance of the nonstationary extreme wind, respectively. Then, based on the estimated evolutionary power spectral density (EPSD), transient features of nonstationary winds are examined. Results show that spectral variations in nonstationary wind fluctuations including concerned downbursts and typhoons are relatively weak. This means that these nonstationary fluctuations can be modeled as uniformly modulated processes. Also, the validity of nonstationary wind spectrum models directly extended from current stationary wind spectr...

Influence of Uncertainties on Crosswind Stability of Vehicles

Crosswind stability is an important criterion for the modern design of railway and road vehicles. In the past, most of the studies on the influence of crosswind on vehicles are based on deterministic models. This paper investigates the crosswind stability by a stochastic model, in which uncertainties are taken into account. A wind model with nonstationary wind turbulence is developed. As the excitation of the vehicle is a stochastic process, a risk analysis has to be carried out and failure probabilities have to be calculated. The proposed method has been utilized to analyze the crosswind stability of road vehicles and railway vehicles on both straight and curved tracks. Besides, in order to find the most influential parameters, a sensitivity analysis has been undertaken.

Oscillation of hydrophysical fields on the shelf and continental slope caused by nonstationary wind

Barotropic and baroclinic oscillations typical of the spring period have been studied based on the three-dimensional thermohydrodynamic model of the Black Sea. This season can be considered transient between the termination of the effect of strong winter winds and the onset of seasonal thermocline formation. The three-dimensional numerical model with a free surface and boundary conditions, corresponding to the real wind field for April 2006 and to the heat and salt flows on the surface, has been used. The horizontal and vertical spatial resolutions of the model are 1.5 km and 27 levels, respectively; the time discreteness is 1 h. This makes it possible to perform detailed modeling in the South Coastal Crimean sea sector. The spatial-time structure of the level, kinetic energy, and temperature fields has been studied using the spectral analysis method. The maximal energy-carrying frequency has been interpreted. Manifestations of Poincare and Kelvin waves, as well as captured shelf waves, have been distinguished in the submesoscale spectral region. A comparison with previous studies has been performed. It is indicated that the stratification variability caused by synoptic processes affects spectral characteristics of wave processes on smaller scales, making its contribution to the Black Sea water mixing.

Fatigue life estimation of existing bridges under vehicle and non-stationary hurricane wind

During hurricane events, additional damages to existing bridge details might be accumulated from the large stress cycles generated by the non-stationary wind and dynamic vehicle loads. The environmental corrosion could also reduce the structural fatigue strength. Based on the non-stationary wind field modeling techniques and the vehicle–bridge–wind dynamic analysis framework, this paper initiates a fatigue damage assessment of existing bridges with corrosion under vehicle and non-stationary extreme hurricane wind loads. The non-stationary hurricane wind is simulated as a summation of time-varying mean and fluctuating non-stationary components with a time-varying spectrum. Dynamic stress histories are obtained by solving the vehicle–bridge–wind dynamic system. The rain flow counting method is used to obtain the stress ranges and numbers of stress cycles. The corrosion induced fatigue strength degradation is included in the analysis. Numerical examples of an existing long span bridge under simulated non-stationary hurricane winds and vehicles are presented to demonstrate the effects of the dynamic loads and corrosions on the fatigue life estimation of existing bridges.

Analysis of Multimode Coupled Buffeting Response of Long-Span Bridges to Nonstationary Winds with Force Parameters from Stationary Wind

AbstractThis paper presents a general frequency domain framework for predicting multimode coupled buffeting response of long-span bridges to nonstationary winds. Within this framework, the wind speed field, aerodynamic forces, and bridge response are separated into deterministic time-varying mean and evolutionary random fluctuating components. Under the assumption of low variation rate of mean wind speed, the time-varying mean and self-excited and buffeting forces are modeled in static force coefficients, flutter derivatives, and admittance functions, determined in a wind tunnel under stationary wind, but with consideration of nonstationary wind characteristics in a quasi-steady manner. The time-varying mean bridge response is calculated through static analysis at each time instant. The random buffeting response is expressed in generalized modal displacements governed by the equations of a frequency-dependent linear time-variant (LTV) system. An equivalent frequency-independent LTV system is introduced, w...

Characterizing the near shore wave energy resource on the west coast of Vancouver Island, Canada

Global wave energy inventories have shown that the west coast of Canada possesses one of the most energetic wave climates in the world, with average annual wave energy transports of 40–50 kW/m occurring at the continental shelf. With this energetic climate, there is an opportunity to generate significant quantities of electricity from this renewable source through the use of wave energy conversion (WEC) technologies. To help evaluate the feasibility of deploying wave energy conversion technologies along the west coast of Vancouver Island, a detailed Simulating WAves Nearshore (SWAN) model was developed to assess the wave resource. The SWAN model hindcasted wave conditions along the west coast over the 2005–2012 period, at a 3 h time resolution. Detailed sensitivity studies within this report illustrate that the Fleet Numerical Meteorology and Oceanography Centre's (FNMOC) WaveWatch 3 results exhibited superior model performance when used as wave input boundary conditions. The corresponding Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) wind fields were used as non-stationary wind forcing functions within the computational domain. Yearly and monthly mean variations of spectral and parametric wave characteristics for two reference locations were plotted to indicate both the spatial and temporal variability of the wave climate. The mean annual wave energy transport for Amphitrite Bank was calculated to be 34.5 kW/m, while the shallower second location featured 27.8 kW/m just 500 m from shore. Wave energy resources of this magnitude are not common globally and, as a consequence, signify that the west coast of Vancouver Island may be an excellent candidate location for future wave energy development.

Dynamic processes and their influence on the transformation of the passive admixture in the sea of Azov

In this model, we apply a nonlinear three-dimensional sigma-coordinate model to study the waves and currents in the Sea of Azov generated by different fields of wind forcing: a constant wind, a quickly varying real wind obtained using the data of reanalysis applying the SKIRON model, and the wind resulting from their combined forcing. This mathematical model was also applied to study the transformation of the passive admixture appearing under the influence of wind fields in the Sea of Azov considered here. We compared the results of numerical calculations with the field data obtained under the wind forcing at a number of hydrological stations. We found the regularities of the water transport driven by onshore and offshore winds, the velocities of the currents, and the characteristics of the evolution of polluted regions at different depths as functions of the nonstationary wind intensity and the velocities of the stationary currents.

Dynamic analysis of wind turbine drive train subjected to nonstationary wind load excitation

The dynamic analysis of wind turbine drive train is presented in this paper. A typical wind turbine drive train consists of a rotor, gearbox and generator. The dynamic modelling of epicyclic gearbox that exists in wind turbine is challenging due to the fact that it has both rotating and orbiting gears. The dynamic equations of motion are obtained based on the rigid multibody modelling with discrete flexibility approach by Lagrange’s formulation. The dynamic model accounts for the time varying gear tooth mesh stiffness, linear stiffness of bearings and torsional shaft stiffness. The aerodynamic torque that a wind turbine drive train subjected to, is modelled based on the simplified method for load calculation in wind turbine, Danish Standard DS472. The characteristic load value acting per unit length at the two-thirds length of the blade is used for calculating the total load of the torsional moment. The vibration signals that are obtained from wind turbine drive train are nonlinear and nonstationary in nature. This is due to the fact that the applied torque load on drive train is nonlinear and nonstationary in nature. The coupled dynamic model of 18 degrees of freedom is solved for responses in time and frequency domains for some nonstationary wind load realizations. The dynamic responses of the system, contact forces between gear tooth pairs in time and frequency domains are obtained numerically. The study envisages that this dynamic model of wind turbine drive train is very useful for subsequent studies on condition monitoring.

Multikernel least mean square algorithm.

The multikernel least-mean-square algorithm is introduced for adaptive estimation of vector-valued nonlinear and nonstationary signals. This is achieved by mapping the multivariate input data to a Hilbert space of time-varying vector-valued functions, whose inner products (kernels) are combined in an online fashion. The proposed algorithm is equipped with novel adaptive sparsification criteria ensuring a finite dictionary, and is computationally efficient and suitable for nonstationary environments. We also show the ability of the proposed vector-valued reproducing kernel Hilbert space to serve as a feature space for the class of multikernel least-squares algorithms. The benefits of adaptive multikernel (MK) estimation algorithms are illuminated in the nonlinear multivariate adaptive prediction setting. Simulations on nonlinear inertial body sensor signals and nonstationary real-world wind signals of low, medium, and high dynamic regimes support the approach.

Oscillation of Hydrophysical Fields on the Shelf and Continental Slope Caused by Nonstationary Wind

Oscillation of Hydrophysical Fields on the Shelf and Continental Slope Caused by Nonstationary Wind

Efficacy of Averaging Interval for Nonstationary Winds

AbstractIn comparison with atmospheric boundary-layer winds, which are generally regarded as stationary, windstorms such as hurricanes and thunderstorms/downbursts have strong nonstationary features characterized by rapid changes in wind speed and direction. The averaging interval associated with turbulent wind characteristics in boundary-layer winds is typically varied between 10 min and 1 h. A fixed averaging interval (FAI), which uses a constant mean to isolate the fluctuating wind component, has been effective in characterizing boundary-layer winds; however, the question remains as to whether the user-defined interval is appropriate for nonstationary winds. To address this concern, a variable averaging interval (VAI) scheme is proposed. For better understanding of the characteristics of nonstationary winds, traditional FAI methods are compared with alternative FAI approaches that use time-varying means and the proposed VAI approaches. In addition, the definitions for gust factor, turbulence intensity,...

Typhoon-induced non-stationary buffeting response of long-span bridges in complex terrain

This paper presents a framework for predicting typhoon-induced non-stationary buffeting response of long-span cable-supported bridges located in a complex terrain. First, a non-stationary typhoon wind model is proposed based on observations from measured typhoon wind data. The wind model includes mainly time-varying mean wind speed, mean wind speed profile and evolutionary power spectral density (EPSD) function. Typhoon-induced wind loading on a bridge deck is then represented by time-varying mean wind forces, non-stationary buffeting forces associated with time-dependent aerodynamic coefficients and self-excited forces characterized by time-dependent aerodynamic derivatives. A nonlinear static analysis is performed to determine time-varying mean wind response, whereas the pseudo excitation method is employed to compute the EPSD-expressed non-stationary buffeting response of a long-span cable-supported bridge. The proposed framework is finally applied to predict non-stationary buffeting responses of a long-span cable-stayed bridge located in a complex terrain during a strong typhoon as a case study. The case study demonstrates how to apply the proposed framework and the results show that the proposed framework is feasible and necessary.

Vulnerability assessment of container cranes under stochastic wind loading

Container cranes, an essential component in any seaport facility system, are highly susceptible to failure during natural disasters such as severe windstorms. Damage or collapse of these structures can lead to significant amount of economic loss in terms of both repair or replacement and downtime. To study how various parameters such as boom position, yaw angle, gradient height and gradient wind speed affect the failure vulnerability of a crane, in this work, a representative container crane has been modelled in a commercial software considering both material and geometric nonlinearities. Stochastic wind fields are simulated as a stationary process by means of the spectral representation method using power spectrum in conjunction with along- and across-wind coherence functions. Wind fields are also simulated as a non-stationary stochastic process utilising the modulation functions from the available literature to consider the situations of thunderstorm downbursts. Nonlinear time history analyses are then performed and a few responses are compared for stationary and non-stationary wind field cases. It is observed that for the given simulation parameters, the responses considering stationary wind fields are larger than those of the non-stationary wind fields. Failure vulnerability of the crane is then assessed in terms of fragility curves. The results of this study show that the failure vulnerability may not be maximum for the set of parameter values for which the aerodynamic forces are maximum. This study provides a better understanding of crane vulnerability that may be utilised to achieve a better crane design.