Wind-sensitive Structures Research Articles

Experimental and numerical study on creep deformation and failure characteristics of ETFE cushion structures

ETFE (ethylene-tetrafluoroethylene) cushion structures with small self-weight are typical wind-sensitive structures that are prone to large deformation and even failure under wind loads. This paper is aimed to investigate the deformation and failure behaviors of ETFE cushion structures subjected to static wind loads. Firstly, calibration mock-up experiments were carried out using a load simulation system and a photogrammetry system. Then, structural responses could be calculated based on force density theory, which were used to validate and correct the calibration numerical model inputs. Finally, same inputs from calibration numerical model were assigned to full-size numerical model and used to predict the structural behavior of a full-size mock-up in an inflation experiment. The comparison between experimental and simulation results validates numerical models integrating material creep response surface, real initial geometry, and actual loading protocol for predicting structural behavior of ETFE cushion structures. Additionally, it is observed that creep deformation constitutes a substantial portion of the total deformation under high static wind loads. The primary factors influencing the failure of ETFE cushions are identified as stress distribution and initial defects.

Buffeting induced fatigue damage assessment of long-span bridge decks under uncertain turbulence conditions

Fatigue in wind-sensitive structures is influenced by the mean wind speed and the turbulence characteristics. This study investigates the importance of uncertainty in the turbulence characteristics of buffeting-induced fatigue damage of flexible wind-sensitive structures, focusing on long-span bridges. We address the importance of the variability of uncertainty in the wind field by using a probabilistic wind field model, including uncertain turbulence parameters for calculating the accumulated fatigue damage throughout the structure’s design life. However, it has been demonstrated that a high computational load accompanies this approach. A new method is proposed that significantly reduces the computational effort through surrogate modelling. This is achieved through a sequentially updating Gaussian Process surrogate modelling approach, which integrates new simulation points into the training dataset and reduces the number of buffeting calculations required for the surrogate to converge to the true solution, thereby reducing the computational cost by almost 95%. The efficiency of the algorithm is demonstrated by using it to compute the fatigue damage accumulation through the design life for a long-span bridge girder, resulting in the increase of damage by several orders of magnitude in comparison to the conventional method of treating the turbulence parameters as deterministic and uncorrelated.

The reproduction of 2-D non-synoptic wind field in an actively controlled wind tunnel

This work mainly discusses the simulation of 2-D non-synoptic wind field in a novel actively controlled wind tunnel. The vibrating fins with airfoil shape are installed at the downstream of multiple fans in the updated active wind tunnel, which will work with fans simultaneously to generate 2-D non-synoptic flow. The fins mainly control the vertical flow while the fans control the along-wind flow, and the input signal of equipment can be adjusted in a predefined way. Then, based on Banach fixed-point theorem, the input signal of fans and fins is constantly updated by an iteration-based method to derive the generated wind characteristics to approach the different target values within an acceptable error range. According to the degree of interference between the longitudinal and the vertical wind characteristics, different iteration strategies are proposed for different wind fields. Two typical non-synoptic wind fields are taken as application examples: irregular turbulence spectra in typhoons and non-stationary winds in mountainous terrains. After iterations, both case studies were generated appropriately in the active tunnel. The simulated wind fields are crucial for wind-resistant design of wind-sensitive structures under non-synoptic wind climates.

Models for the estimation of gust-buffeting response in symmetrical wind-sensitive structures

The peak factor is an analytical development for estimating the expected maximum response caused by aerodynamic forces on wind-sensitive structures. It expresses the likelihood of how above the mean is the maximum amplitude of a stationary process in terms of its standard deviation. Such a process represents the structural response of a wind-sensitive structure in conventional applications. The methods and solutions used to approximate it in the along-wind direction have become ordinary to structural engineers. Notwithstanding, the structural response in combined orthogonal directions is often omitted since a criterion for such an estimation is still absent. This communication seeks to contribute to fill the gap in practical criteria for estimating response maxima in symmetric structures. It is done by proposing models to estimate the parameters describing the probability distribution of the maxima from the Euclidean norm of two correlated Gaussian variables. Although the applications to structural engineering are emphasized, the proposed models apply to other problems where the maxima from the norm of two Gaussian variables is relevant.

Wind-Induced Vibration Analysis of a Pentagonal Three–Four Strut Hybrid Open-Type Cable Dome

Previous research has confirmed that the newly proposed pentagonal three–four strut hybrid cable dome exhibits superior static performance compared to traditional cable domes, though its dynamic characteristics still require further study. Cable domes are wind-sensitive structures, and the results of a wind-induced vibration analysis are beneficial for the selection and construction of cable domes. In this study, a finite element model of a new open-type cable dome with a span of 120 m is established. The MATLAB 2017a programming language is employed to simulate pulsating winds, followed by a nonlinear dynamic analysis to analyze the wind-induced vibrations of the structure. The reliability of the pulsating wind model is confirmed by comparing the simulated spectrum with the target spectrum. Moreover, a wind-induced vibration time history analysis is performed to obtain the node displacement and internal force of components wind vibration coefficients, aiding in the approximation of pulsating winds with average winds in a wind-resistant design. Furthermore, a parametric analysis is carried out, ranking nodes and components based on sensitivity. The result shows that the structure exhibits the strongest wind resistance when the rise–span ratio is f/l=0.07 and the thickness–span ratio is h/l=0.08. Notably, the outer upper chord node, 2a, and the inner lower chord hoop cable, H1, are identified as the most sensitive node and component within the structure, respectively. Overall, the structure demonstrates excellent wind resistance performance, and the maximum wind vibration coefficient value remains below 3.

Experimental and numerical studies on unsteady galloping driving mechanism of a truss beam with solid barriers

The long-span bridges with truss beam are widely recognized as typical wind-sensitive structures, and its wind-induced divergence events may become a very predominant issue. This work evaluates the galloping performance of a typical truss beam with wind barriers, which is detected to be susceptible to the infrequent vertical instability at specific attack angles, as evidenced by experimentation and numerical analysis. Since the truss beam constitutes a complex cross section, this study employs energy analysis to distinguish the crucial parts affected by vibration and discovers that the galloping vibration is mostly caused by the surfaces of the deck. Rather than relying on conventional quasi-steady theory, this study explores the unsteady aerodynamic forces to identify the underlying galloping driving mechanism. Our findings reveal that the instigator of galloping instability is the phase rising of lift with increasing wind speed. Additionally, the nonlinear mechanical damping is not a decisive parameter. Furthermore, we have investigated the impact of an essential ancillary facility, the wind barrier, and discovered that its galloping stability can be enhanced by increasing its porousness and decreasing its height. However, the underlying mechanisms behind this improvement are distinct.

An optimal sensor placement scheme for wind flow and pressure field monitoring

Sensing of wind pressures on wind-sensitive structures and wind speeds in densely populated cities is crucial to ensure structure safety and monitoring urban wind environment. However, these wind pressure or wind speed sensors are often sparsely distributed due to their high cost, and consequently the collected wind pressure or speed information is limited. Under these circumstances, it is particularly important to place these limited number of sensors in the optimal locations with the capacity of extracting the most information. In this study, an optimal sensor placement scheme based on multi-resolution dynamic mode decomposition (mrDMD), a space post-processing function: signed distance function (SDF) and particle swarm optimization-random forest (PSO-RF) is proposed, called mrDMD-SDF-PSO-RF (mrDSPR). The effectiveness of the proposed scheme is verified using two case studies of reconstruction based on sparse sensors: wind flow field of a city block and wind pressure field of a single building. The result indicates that the proposed scheme significantly improves the efficiency of the sensors. Therefore, based on the proposed optimal sensor placement scheme, the locations of placing sensors can be well-designed for various wind engineering problems, which builds a solid foundation of super-resolution reconstruction of wind pressure on buildings and wind flow field in urban environment.

Review of Wind-Induced Effects Estimation through Nonlinear Analysis of Tall Buildings, High-Rise Structures, Flexible Bridges and Transmission Lines

The nonlinear effects exhibited by structures under the action of wind loads have gradually stepped into the vision of wind-resistant researchers. By summarizing the prominent wind-induced nonlinear problems of four types of wind-sensitive structures, namely tall buildings, high-rise structures, flexible bridges, and transmission lines, the occurrence mechanism of their nonlinear effects is revealed, providing cutting-edge research progress in theoretical studies, experimental methods and vibration control. Aerodynamic admittance provides insights into the aerodynamic nonlinearity (AN) between the wind pressure spectrum and wind speed spectrum of tall building surfaces. The equivalent nonlinear equation method is used to solve nonlinear vibration equations with generalized van-der-Pol-type aerodynamic damping terms. The elastic–plastic finite element method and multiscale modeling method are widely employed to analyze the effects of geometric nonlinearity (GN) and material nonlinearity (MN) at local nodes on the wind-induced response of latticed tall structures. The AN in blunt sections of bridges arises from the amplitude dependence of the aerodynamic derivative and the higher-order term of the self-excited force. Volterra series aerodynamic models are more suitable for the nonlinear aerodynamic modeling of bridges than the polynomial models studied more in the past. The improved Lindstedt–Poincare perturbation method, which considers the strong GN in the response of ice-covered transmission lines, offers high accuracy. The complex numerical calculations and nonlinear analyses involved in wind-induced nonlinear effects continue to consume significant computational resources and time, especially for complex wind field conditions and flexible and variable structural forms. It is necessary to further develop analytical, modeling and identification tools to facilitate the modeling of nonlinear features in the future.

A comprehensive review on estimation of equivalent static wind loads on long-span roofs

Equivalent static wind load (ESWL) is helpful information for designing wind-sensitive structures since it converts complex wind-induced structural dynamic analysis into a simplified static analysis and facilitates combination of other loads or actions in structural designs. In recent years, there have been a growing number of long-span roof structures, most of which are sensitive to wind actions. Indeed, the accurate determination of ESWLs has been a primary concern in their wind-resistant design. Although some significant progress has been made on this topic, there are various issues to be addressed or improved due to a variety of reasons. With the further development of long-span roofs, there will be higher requirements for their ESWLs. This paper first combs through the existing representative methods depending on wind-induced structural responses (WISRs) and wind-induced structural stability (WISS), where the ESWLs linked with the former are the mainstream and the ones concerned with the latter are still somewhat in their initial stages of development. In each broad category, some momentous tactics of mathematics and mechanics are utilized to derive different methods. In the conclusion, this paper finally summarizes the existing achievements, highlights the technical challenges that hinder the current methods from being widely adopted and proposes some latent solutions for the future research. This review paper is anticipated to be a comprehensive reference for researchers and professionals in this field of study.

Long-term response of a curved floating bridge to inhomogeneous wind fields

A numerical model of a 5 km long curved floating bridge, planned for the Bjørnafjord, in Norway, is subjected to strong wind events with stationary mean properties that vary along the bridge axis. A Weather Research and Forecasting model (WRF) is used to estimate the mean wind speeds and directions in the fjord, with a 500 m resolution, during a 20-year period. The wind turbulence intensities are estimated as functions of the position along the bridge and the wind direction, using an artificial neural network trained on nearby sonic anemometer data and formulations given in the national annex of the Eurocode. A skew wind buffeting formulation is used to estimate the linear static response and the linear quasi-steady buffeting response in the frequency domain. The response under inhomogeneous winds is compared with the response under equivalent homogeneous winds. The inhomogeneous wind response is, on average, 1.5% to 47% larger, depending on the type of analysis and response component, but a high variability is observed, with much larger differences for some wind cases. These findings motivate case-specific investigations of inhomogeneous wind effects to improve fatigue and extreme response predictions of long wind-sensitive structures.

State augmentation method for buffeting responses of wind-sensitive structures in wind environments with large turbulence intensity

Recent studies have shown that wind fields with large turbulence intensity are frequently observed in non-synoptic winds such as typhoons and hurricanes. The quadratic terms of the fluctuating wind speed are important for calculating buffeting responses of wind-sensitive structures under high turbulence. In this study, a moment-based method, which is called the state augmentation method, is used to obtain high-order response moments and avoid the large computational cost of the high-order frequency domain method. First, the buffeting force formula with nonlinear velocity terms is established, and the Non-Gaussian buffeting force is further approximated as a polynomial of the Ornstein–Uhlenbeck (OU) process. Then, an augmented state vector is introduced to express the relationship between the statistical moments of each order, and the 1st to 4th response moments can be solved sequentially by a particular set of linear equations. Finally, the extreme responses of a single-degree-of-freedom (SDOF) tower and a long-span suspension bridge are calculated as engineering examples. By comparing the computation results with the frequency method, it is proven that this moment-based method has a sufficient accuracy in analysing quadratic terms. The calculation results also show that quadratic terms under high turbulence significantly amplify the non-Gaussian peak factor and extreme responses.

Full long-term extreme buffeting response calculations using sequential Gaussian process surrogate modeling

The full long-term method (FLM) provides the most accurate estimates of the long-term (i.e., 10–100 years) extreme buffeting responses in the design of wind-sensitive structures. However, it suffers from high computational demand if the number of uncertain turbulence parameters becomes high. In this paper, we propose a new algorithm for efficient solution of the full long-term problem through sequential Gaussian Process (GP) surrogate modeling. The algorithm efficiently trains a GP surrogate model that replaces the buffeting response calculation while exploiting the specific properties of the long-term problem. The performance of the algorithm is demonstrated on a practical design problem of estimating extreme buffeting-induced stresses of a long-span suspension bridge, where the results are compared with the ones obtained from other viable methods. The results show that the algorithm achieves computational efficiency comparable to the highly efficient IFORM, while also significantly enhancing the accuracy of the response estimate. The algorithm also has the added benefit of converging to the true solution of the full long-term problem, in contrast to the IFORM solution, which converges to an approximate solution.

Simulation of turbulent wind field in multi-spatial dimensions using a novel non-uniform FFT enhanced stochastic wave-based spectral representation method

Simulation of stochastic wind field is necessary for wind-induced vibration analysis of wind-sensitive structures. Stochastic wave-based spectral representation method (SWSRM) is one of the most widely used methods for wind field simulation. However, it may face challenges to simulate turbulent wind field in multi-spatial dimensions due to its large memory consumption and low simulation efficiency. In this study, a novel non-uniform FFT (NUFFT) enhanced SWSRM is proposed. The approach for selecting sampling points of wave number is also established based on adaptive integral method. Numerical experiments are further designed to demonstrate the validity and effectiveness of the enhanced SWSRM. Results show that the proposed method can significantly improve the simulation efficiency and reduce the memory consumption in multi-spatial dimensions. In addition, the simulation points can be arbitrarily selected using NUFFT enhanced SWSRM. More importantly, the proposed method can improve the turbulent spectral accuracy in low-frequency region.

Probabilistic method for wind speed prediction and statistics distribution inference based on SHM data-driven

For wind-sensitive structures, such as long-span bridges, high-rise buildings, transmission towers, etc., the prediction of wind speed and its statistical distribution are vital steps in the design and operation stages. Specifically, wind speed prediction is directly related to the value of wind load in the next occurrence; the statistical distribution of wind speed has regular characteristics, which can represent the random characteristics of wind field. In this paper, a probabilistic prediction model of wind speed based on Bayes’ theorem is proposed and verified based on structural health monitoring (SHM) data. Firstly, the Gaussian process is derived and used as an a priori function in Bayes’ theorem. In addition, the influence of six covariance functions on the prediction performance are discussed, that is, squared exponential (SE), Matern-3/2 (MA-3/2), Matern-5/2 (MA-5/2), automatic relevance determination SE (ARDSE), ARDMA-3/2, and ARDMA-5/2. Secondly, the correlation between the next wind speed and the previous wind speed is discussed by using the moving window method. Finally, the parameters in the three wind speed probability distribution functions (PDF), that is, Gumbel distribution, Weibull distribution, Rayleigh distribution, are updated in real time by increasing the SHM data based on Bayes’ theorem.

Modeling Multidimensional Multivariate Turbulent Wind Fields Using a Correlated Turbulence Wave Number–Frequency Spectral Representation Method

Accurate and efficient simulation of turbulent stochastic fields lays a solid foundation for dynamic response analysis and reliability evaluation of wind-sensitive structures. In this paper, a correlated-turbulence wave number–frequency spectral representation method (CT-WSRM) is proposed for simulating turbulent wind fields. Turbulent spectra that consider the correlation of turbulence are established using wind data measured during Typhoon Yanhua at the Ma’anshan Yangtze River (MYR) Bridge site in China. Using the established spectra, a customized turbulence wave number–frequency spectra density (WSD) matrix is defined and adopted in the proposed CT-WSRM. The proposed method can be utilized to simulate multidimensional multivariate two dimensional-three variate (2D-3V) spatial-temporal turbulent wind fields. In addition, a dimension-reduction model is introduced to describe turbulent wind fields in the probability density level within three random variables. The fast Fourier transform (FFT) algorithm is also embedded in the CT-WSRM to alleviate the computational burden. The stochastic turbulent wind fields for the MYR Bridge were simulated. Results demonstrated the effectiveness of the proposed method against the measured turbulent spectra. This method can be further utilized in the dynamic reliability analysis, providing structural reliability evaluation from the probabilistic view.

Experimental investigation of wind effects on a 282-meter-high tower with complex aerodynamic shapes based on a rigid model and multi-degree-of-freedom aeroelastic model

Slender and flexible high-rise structures are very sensitive to large wind-induced vibration phenomena such as vortex-induced vibration and galloping under strong winds. However, pressure measurements on rigid models cannot consider coupling aeroelastic effects, and single-degree-of-freedom aeroelastic model wind tunnel tests can only consider the contribution of the first-order linear mode. For wind-sensitive structures with complex aerodynamic shapes, the effect of higher-order modes on the wind-induced response may not be ignored. In this study, a series of multi-degree-of-freedom (MDOF) aeroelastic model wind tunnel tests and pressure measurements of a rigid model were conducted to comparatively investigate the wind effects of a 282-meter-high tower with complex aerodynamic shapes. A detailed analysis of the aeroelastic effects on the high-rise tower is presented, and the effects of the structural damping ratio, wind speed, and wind direction are also discussed. The results show that the variation trends of the peak acceleration responses are generally consistent, while in those wind-sensitive directions (165-degree wind direction), the peak acceleration responses of the MDOF model are almost 1.5 times larger than those of the rigid model, indicating that the aeroelastic effects are remarkable. The corresponding response spectral peak values of the MDOF model are significantly larger than those of the rigid model by a factor of more than 3 and the correlations of responses in the two orthogonal directions also increase greatly by 43.5%. However, the “set-back” aerodynamic shape (180-degree wind direction) can considerably weaken aeroelastic effects and the peak acceleration responses are close to those of the rigid model. The generalized aerodynamic force spectrum also shows broadband features, implying its superior aerodynamic performance. The comfort assessments for different structural damping ratios are conducted based on various codes and criteria, suggesting that the structural damping ratio should be larger than 3%. The equivalent static wind loads on the upper floors are notably affected by aeroelastic effects while the lower floors are relatively insensitive. This study provides a detailed perspective of the aeroelastic effect for slender tower, and hence facilitates the wind-resistant design of flexible structures.

Assessment of approaching wind field for high-rise buildings based on wind pressure records via machine learning techniques

Many accidents of buildings and bridges in service suggest it is essentially important for wind-sensitive structures to timely clarify approaching wind field so as to better understand associated wind effects and then adopt appropriate wind-resistant measures. However, difficulties usually exist for directly measuring undisturbed wind flows on or around large-scale structures. This paper presents a study on the assessment of approaching wind field for a supertall building via Machine Learning (ML) methods based on wind pressure records. A total of 8 specific ML models, i.e., AdaBoost, Bagging, Decision Tree, Extra Tree, Gradient Boosting, KNN, Random Forest, and SVR, are exploited to deduce associated wind information (in terms of mean values of speed and direction and turbulence intensity of speed) from the time series or statistical parameters of wind pressure. The models are trained and validated by results from wind tunnel experiments, and tested by field measurements from the prototype building. It is shown that most of the models driven by “statistical parameters” rather than “time series” are able to map wind pressure information to that for approaching wind field accurately, which reflects the importance of selecting appropriate input variable to driven ML models. The robustness of these models is further examined through a series of tests with reduced training/validation data. The presented results are helpful to further understand the correlations between the statistical features of wind pressure on high-rise buildings and corresponding wind field. The documented ML techniques can also be adopted to determine the approaching wind field for other wind-sensitive structures on the basis of various kinds of wind-effect records.

Characteristics of Extreme Wind Pressure on the Open Prefabricated Spatial Grid Structure of Evergrande Stadium

Large-span open prefabricated spatial grid structures are characterized by light mass, high flexibility, low self-oscillation frequency, and low damping, resulting in wind-sensitive structures. Meanwhile, their height tends to be relatively low, located in the wind field with a large wind speed gradient and high turbulence area. Therefore, surface airflow is complex, and many flow separations, reattachment, eddy shedding, and other phenomena occur, causing damage to local areas. This paper took the Evergrande Stadium in Guiyang, China, as the research object and used the random number cyclic pre-simulation method to study its surface extreme wind pressure. Firstly, five conventional distributions (Gaussian, Weibull, three-parameter gamma, generalized extreme value, and lognormal distribution) were fitted to the wind pressure probability densities at different measurement points on the surface of the open stadium. It is found that the same distribution could not be chosen to describe the probability density distribution of wind pressure at all measurement points. Hence, based on the simulation results, the Gaussian and non-Gaussian regions of this structure were divided to determine where to apply which distribution. Additionally, the accuracy of the peak factor, improved peak factor, and modified Hermite moment model method were compared to check their applicability. Finally, the effect of roughness on the extreme wind pressure distribution on the open stadium surface was also investigated according to the highest accuracy method above. The findings of this study will provide a reference for engineers in designing large-span open stadiums for wind resistance to minimize the occurrence of wind damage.

Characterizing wind pressure on CAARC standard tall building with various façade appurtenances: An experimental study

Tall buildings are usually considered as wind-sensitive structures. While extensive studies have been conducted concerning the wind load characteristics on tall buildings, the effect of façade appurtenances has not been fully understood. In this study, a 1:300 scaled CAARC (Commonwealth Advisory Aeronautical Research Council) standard tall building was tested in wind tunnel to diagnose the effect of various façade appurtenances on wind pressure characteristics. It is shown that, the change of façade appurtenances can significantly influence the fluctuating wind pressure on the windward and leeward surfaces, with the maximum reduction reaching 21%. By contrast, the effect of façade appurtenance on mean wind pressure is somewhat less pronounced. The results also indicated that adding vertical strips is likely to reduce the horizontal coherence of surface wind pressure, with the maximum reduction of horizontal coherence coefficient reaching 38%. Comparatively, the effect of façade appurtenance on vertical coherence is less significant.

Performance Evaluation of Linear and Nonlinear Models for Short-Term Forecasting of Tropical-Storm Winds

Wind-sensitive structures usually suffer from violent vibrations or severe damages under the action of tropical storms. It is of great significance to forecast tropical-storm winds in advance for the sake of reducing or avoiding consequent losses. The model used for forecasting becomes a primary concern in engineering applications. This paper presents a performance evaluation of linear and nonlinear models for the short-term forecasting of tropical storms. Five extensively employed models are adopted to forecast wind speeds using measured samples from the tropical storm Rumbia, which facilitates a comparison of the predicting performances of different models. The analytical results indicate that the autoregressive integrated moving average (ARIMA) model outperforms the other models in the one-step ahead prediction and presents the least forecasting errors in both the mean and maximum wind speeds. However, the support vector regression (SVR) model has the worst performance on the selected dataset. When it comes to the multi-step ahead forecasting, the prediction error of each model increases as the number of steps expands. Although each model shows an insufficient ability to capture the variation of future wind speed, the ARIMA model still appears to have the least forecasting errors. Hence, the ARIMA model can offer effective short-term forecasting of tropical-storm winds in both one-step and multi-step scenarios.