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To investigate the shielding effects of mountains in front of a bridge on the wind field at the bridge site in an area with complex topography, a numerical simulation model of the bridge site, which is located in a deep cut V-shaped gorge, was conducted by a computational fluid dynamics method. In this study, taking the shielding effects of mountai...
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... average elevation of the hilltop is 1800 m, which is 192 m higher than the design elevation of the main beam. The ichnography of the bridge site and elevation of the bridge site are shown in Figures 1 and 2. ...
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... the numerical model is reliable, and the results of the numerical simulation can reflect the wind field conditions at the bridge site. Figure 10 shows the relationship between the flow direction and the wind velocity of the v component at the bridge deck level. The mean velocity is the average value of the five observation points along the 1/4-3/4 span of the girder (the wind velocity area in Figure 6), the maximum value is the maximum wind velocity of the five observation points, and the minimum value is the minimum wind velocity of the five observation points. ...
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... investigate the effect of the high-steep mountain to the east of the bridge site on the mean velocity of the main girder, the wind velocities of three components are shown in Figures 11 and 12 for several typical cases. For SWC cases, it can be seen from Figure 11 that the wind velocity distribution along the girder is obviously uneven, and the wind velocity near the eastern side of the mountain decreases significantly. ...
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... investigate the effect of the high-steep mountain to the east of the bridge site on the mean velocity of the main girder, the wind velocities of three components are shown in Figures 11 and 12 for several typical cases. For SWC cases, it can be seen from Figure 11 that the wind velocity distribution along the girder is obviously uneven, and the wind velocity near the eastern side of the mountain decreases significantly. The transverse wind velocity even appears in the opposite direction, which indicates that the shielding effect of the mountain in front of the bridge is quite remarkable. ...
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... transverse wind velocity even appears in the opposite direction, which indicates that the shielding effect of the mountain in front of the bridge is quite remarkable. For NWC cases, it can be seen from Figure 12 that the wind velocity distribution is relatively even along the girder. The wind velocity of the girder side near the mountain is decreasing, but the reduction is not large. ...
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... wind velocity of the girder side near the mountain is decreasing, but the reduction is not large. The variation in the wind velocity of the girder side far from the mountain under different flow directions is shown in Figure 13, and the variation in the wind velocity of the girder side near the mountain under different flow directions is shown in Figure 14. It can be seen from Figures 13 and 14 that the nearer to the mountain the transverse wind velocity, the smaller it is, and the wind velocity under SWC cases is smaller than that under NWC cases. ...
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... wind velocity of the girder side near the mountain is decreasing, but the reduction is not large. The variation in the wind velocity of the girder side far from the mountain under different flow directions is shown in Figure 13, and the variation in the wind velocity of the girder side near the mountain under different flow directions is shown in Figure 14. It can be seen from Figures 13 and 14 that the nearer to the mountain the transverse wind velocity, the smaller it is, and the wind velocity under SWC cases is smaller than that under NWC cases. ...
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... variation in the wind velocity of the girder side far from the mountain under different flow directions is shown in Figure 13, and the variation in the wind velocity of the girder side near the mountain under different flow directions is shown in Figure 14. It can be seen from Figures 13 and 14 that the nearer to the mountain the transverse wind velocity, the smaller it is, and the wind velocity under SWC cases is smaller than that under NWC cases. When the direction of the incoming flow is parallel to the direction of the river or is nearly perpendicular to the main girder, the crosswind velocity is larger. ...
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... mean ratio values of the wind velocity compared to the upper gradient wind velocity at different main girders under different cases, including the SWC cases and NWC cases, are given in Figure 15. It can be seen that the closer the location is to the eastern side of the mountain, the smaller the mean ratio, which decreases rapidly for SWC cases. ...
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... ratio for NWC cases also tends to decrease, but the reduction is slow. The change pattern is basically the same as that in Figure 11. The wind load is proportional to the square of the wind velocity, that is, when the wind load is reduced by 50%, the corresponding wind velocity is reduced by 70%. ...
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... wind load is proportional to the square of the wind velocity, that is, when the wind load is reduced by 50%, the corresponding wind velocity is reduced by 70%. From Figure 15, the wind velocity at the mid-span region (observation point No. 5) is 51% of the maximum wind velocity of the main girder, and the corresponding wind load is 26% of the maximum wind load. Assuming the above boundary, it can be concluded that the wind load on the main girder near the mountain decreases significantly. ...
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... of the wind profile of the main girder Figure 16 shows the wind profiles at different observation points above the bridge deck (Case 5). It can be seen that the wind profiles at different positions of the bridge deck present S-shaped curves, which is quite different from the conventional exponential distribution. ...
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... wind profiles at the mid-span region of the bridge under SWC cases are shown in Figure 17. From the results, when the angle between the incoming flow direction and the mountain is close to 90°, the shielding effect of the mountain is much more significant. ...
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... to the effect of shielded mountains, wind profiles at bridge site do not obey the exponential distribution, but obey S curve distribution. Figure 18. From the results, the shielding effect of the mountain on the main girder is not obvious for the bridge site downstream of the mountain. ...
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... wind velocity distribution along the girder is basically even, and the wind profile also obeys the exponential distribution. As shown in Figure 19, the effect of shielded mountains increases with the flow direction changes, and the wind profiles gradually show the trend of S-shaped curve. ...
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Citations
... The natural frequencies of structures, damping ratios, and mode shape vectors are structural modal parameters that could affect the structure's design. [3][4][5] In engineering, the most common methods of modal parameter identification are the traditional methods and the methods under ambient excitation. 6 The traditional method generates free vibrations by using artificial excitation. ...
In the wind tunnel test, the full-bridge aeroelastic model needs to simulate both the shape and dynamic characteristics of the real bridge, and modal parameters are key dynamic parameters. Therefore, it is essential to identify the modal parameters of the model accurately. To get accurate modal parameters of the long-span bridge model in the wind tunnel test, the applications of the Hilbert-Huang transform for modal parameter identification were analyzed in this paper. Then a band-pass filter is designed to filter the original signal so that the intrinsic mode function obtained by empirical mode decomposition can satisfy the single-component signal requirement and eliminate the mode mixing effect effectively. Meanwhile, the endpoint data extension method based on SVM (Support Vector Machine) was presented to restrain the end effects of empirical mode decomposition. Finally, taking the Oujiang Bridge as the engineering background, the improved algorithm was applied to modal parameter identification of the bridge under ambient excitation. The modal parameters such as modal frequency and damping ratio were obtained. The reliability of the improved method was verified by comparing the identified modal parameters with the results of the finite element method, and it turns out that the improved method can reduce the frequency identification error of vertical bend, lateral bend, and torsion to 1.01%, 4.07%, and 1.68%. The results indicated that the improved method based on the Hilbert-Huang transform can accurately identify the main modal parameters of the structure and can be better applied to identify the modal parameters of long-span bridge structures.
... The research about characteristics of wind fields in mountainous areas for the placement of wind speed measurement points and health monitoring of large-span bridges have important significance (Arangio and Bontempi, 2014;Bedon et al., 2018;Wu et al., 2023), combined with deep learning techniques to further ensure the safety of mountainous bridges (Ko et al., 2009;Zhou and Sun, 2018;Vazque-Ontiveros, 2021). Thus, the study of wind characteristics of complex mountainous areas has significant value (Zhang et al., 2019;Jiang et al., 2021;Xing et al., 2021;Zhang et al., 2023). ...
Bridges in mountainous areas are indispensable nodes in transportation networks, and wind resistance capabilities have become a controlling factor of long-span bridges built in mountain areas. Therefore, it is necessary to study the characteristics of wind fields under complex terrain. An improved inlet boundary by fitting the boundary curve was proposed in this study. The inlet fluctuating wind field was generated by the Correlation Improved Random Flow Generation method (CIRFG). The results of the numerical simulations show that the fluctuating wind input generated by CIRFG tallies with the target wind field, which proves the reliability of the proposed method. The method of fitting boundary curves to give inlet wind speed profiles can achieve non-uniform wind profile inputs. The results show the wind direction of the gorge varies significantly by height. The wind speed at the summit will accelerate affected by the terrain. Also influenced by the terrain, the turbulence intensity profiles in the simulated area show an S-shape. The transverse wind and angle of attack are uneven along the main girder, especially near slopes. The conclusions obtained in the study can provide references for the wind resistance of bridges built in mountainous areas.
... A numerical model was established to investigate the shielding effects of mountains on the wind field in front of the bridge. The calculation results indicate that the characteristics of the wind field near the mountain at the bridge site are influenced by both the mountain and the direction of the incoming flow [29]. The simulation of the canyon terrain reveals the spatial distribution characteristics of the wind field and proposes a formula for calculating the wind speed amplification coefficient [30]. ...
... The velocity inlet boundary adopted a wind speed profile with the surface friction coefficient of the B-type surface [5,29], as shown in Figure 3. The height of gradient wind speed was 1000 m, and the gradient wind speed was assumed to be 50 m/s. ...
As an important part of road transportation, bridge engineering plays a pivotal role in infrastructure construction. The wind field characteristics of the bridge site area have an essential influence on both the construction and operation period of the bridge, especially in mountainous canyon terrain. In this paper, a numerical simulation using computational fluid dynamics software was conducted to examine the intricate wind field characteristics in mountainous regions. The study focused on ideal V-shaped and U-shaped canyons, aiming to investigate the influence of various parameters. These parameters included three distinct heights, seven angles, and seven widths of the canyon. The findings indicate that in both ideal V-shaped and U-shaped canyons, the canyon acceleration effect weakens as the angles or widths of the canyon increase. The wind speed amplification effect gradually disappears when the V-shaped canyon angle exceeds 160° or when the U-shaped canyon has a width-to-height ratio of approximately 5:1. The wind speed amplification effect strengthens as the canyon height increases. The wind speed acceleration effect exhibits a linear relationship with the angle of the V-shaped canyon, while it demonstrates a logarithmic relationship with the width of the U-shaped canyon. Additionally, the wind speed amplification factor follows a logarithmic distribution along the canyon height. The wind field characteristics observed in this study offer valuable insights for future bridge designs in mountainous regions featuring V-shaped and U-shaped canyons.
... The mountain topography only affects a local region. In addition, existing researches of mountainous wind system including field measurement (Whiteman 1990;Mingjin et al. 2019;Zhang et al. 2020a), numerical simulation (Maurizi et al. 1998;Kim et al. 2000;Bitsuamlak et al. 2004;Cao et al. 2012) and wind tunnel test (Li et al. 2017(Li et al. , 2010 also proves that the speed of local wind systems vary from place to place, depending on many factors including terrain characteristics, ground cover, soil moisture, altitude and etc. Therefore, in mountainous areas, it is not accurate to use the extreme wind speed from the nearby weather station on the proposed structure in the other valley. ...
In addition to common synoptic wind system, the mountainous terrain forms a local thermally driven wind system, which makes the mountain wind system have strong terrain dependence. Therefore, in order to estimate the reliable design wind speeds for structural safety, the samples for extreme wind speeds for certain return periods at mountainous areas can only come from field measurements at construction site. However, wind speeds measuring duration is usually short in real practice. This work proposes a novel method for calculating extreme wind speeds in mountainous areas by using short-term field measurement data and long-term nearby meteorological observatory data. Extreme wind speeds in mountainous area are affected by mixed climates composed by local-scale wind and large-scale synoptic wind. The local winds can be recorded at construction site with short observatory time, while the extreme wind speeds samples from synoptic wind climate from nearby meteorological station with long observatory time is extracted for data augmentation. The bridge construction site at Hengduan Mountains in southwestern China is taken as an example in this study. A 10-month dataset of field measurement wind speeds is recorded at this location. This study firstly provides a new method to extract wind speed time series of windstorms. Based on the different windstorm features, the local and synoptic winds are separated. Next, the synoptic wind speeds from nearby meteorological stations are converted and combined with local winds to derive the extreme wind speeds probability distribution function. The calculation results shows that the extreme wind speed in the short return period is controlled by the local wind system, and the long-period extreme wind speed is determined by the synoptic wind system in the mountain area. The descending slope of the synoptic wind speed exceeding probability exceeds the local wind by about 20%. If the influence of mixed climate is not considered, and the wind speed samples are not divided by category, the decline slope will be 7% lower.
... However, the applicability of these distributions in mountain valleys needs to be further verified. Furthermore, with the increase of wind speed, the angle of attack decreases, and it remains within a specific range (Huang et al., 2019;Zhang et al., 2019). According to the measured samples of the bridge site area in the gorge area, J. Zhang et al. (2020) and Zhang et al. (2021) fitted the angle of attack distribution using the normal and Gumbel distribution functions. ...
... The mountain gorge areas are greatly affected by topography, and the wind field in such sites has a noticeable wind direction effect and high angle of attack (J. Zhang et al., 2020b;Zhang et al., 2021Zhang et al., , 2019. Therefore, the joint distribution of wind direction, wind speed, and wind angle of attack should be considered when calculating the design wind parameters of structures in such areas. ...
The temporal and spatial distribution of wind fields in the deep-cut gorge bridge site is complex, and the impact of different incoming flows on the structure is also essentially different. Therefore, it is essential to comprehensively consider the correlation between wind direction, wind speed, and angle of attack. The joint probability models between average wind parameters are first established using the Pair-Copula decomposition based on the field-measured data. Then, the concept of the probability-segmentation-based first order inverse reliability method (PSB-IFORM) is proposed for calculating the environmental surface of the multi-peak joint distribution model. The results show that the mixed von Mises distribution is ideal to fit the wind direction with multi-peak characteristics. The trivariate joint probability model constructed in this paper ultimately represents the correlation of average wind parameters, and the most unfavorable combination of design wind parameters can be found on the environmental surface. Furthermore, the proposed PSB-IFORM can effectively avoid the defects of the inverse first-order reliability method (IFORM) and the conservative highest probability contour (HDC) method in solving the multi-peak joint probability distribution model. This study is of particular interest to researchers and engineers engaged in wind resistance of mountain structures.
... Determining the intense wind characteristics in mountain terrain is the basis of mountain wind field simulation and analyzing its impact on these wind-sensitive structures, which then can be applied to predict the wind-induced structural response (e.g., Fenerci and Øiseth, 2018;. Wind characteristics are widely studied through field measurements (Lystad et al., 2018;, wind tunnel tests (Chen et al., 2019;Song et al., 2020), and computational fluid dynamics (Sharma et al., 2020;Zhang et al., 2019). Field measurement is the most telling way that obtains reliable data directly, despite the high cost of equipment and the limited measure points. ...
Driven by local heat, the periodic thermally-developed wind often occurs in mountain terrain, and there is a strong correlation between wind speed and temperature. Other intense winds such as thunderstorms and sudden intense winds may also occur. Classifying mixed wind climates into homogeneous families helps accurately obtain the wind field characteristics and is essential to the structural wind-excited response in mountain terrain. For this reason, based on the long-term field measured data of the bridge site in a typical U-shaped canyon, a framework is set up to detect and extract periodic thermally-developed wind. Its statistical and time-varying wind characteristics are analyzed subsequently. Results show that the mean wind has a dominant direction along the canyon during the intense wind period, strongly correlated with the attack angle. The mean and fluctuating wind parameters will change obviously and periodically with wind speed every day. Due to the strong nonstationarity of these events, the power spectrum of pulsating components extracted from periodic thermally-developed intense wind events by the nonstationary model can be well described by Von Kármán power spectrum function. This study is of great significance to the structural durability and comfort for wind-sensitive structures in mountain terrain.
... This phenomenon, named "artificial cliff" [17], leads to flow separation and baffling flow at the leading edge, changing inflow conditions and inaccuracies in the test. Several methods have been proposed to address the "artificial cliff" [18][19][20]. For example, a transition section, which was used to connect the floor of the wind tunnel or numerical computational domain and the terrain model edge, was proposed to avert flow separation. ...
Wind tunnel tests are a commonly used method for studying wind characteristics of complex terrain; but truncation of the terrain model is usually unavoidable and affects the accuracy of the test results. For this reason, the effects of truncated and original terrain models on the simulation of wind characteristics for complex terrain were investigated by considering both nontruncated and truncated models, with the truncated model considering the applicability of two types of transition sections. The results show that the effect of topographic truncation on profiles of mean velocity and turbulence intensity is different for regions and that inclination angle profiles are extremely sensitive to the changing topographic features upwind. In those cases, the spectra of streamwise velocity were overestimated in the low-frequency range but underestimated in the high-frequency range due to topographic truncation. At the same time, the less negative value of the slope of the spectra was found at the inertial subrange. Furthermore, the normalized bandwidth was also influenced by topographic truncation, which was narrowed in windward and leeward regions and broadened in the valley region. We should note that the performance of the transition sections used in this study was quite limited and even resulted in inaccuracies in the simulation.
... However, unlike coastal and plain regions, the wind characteristic parameters of mountainous regions are too complicated to be comprehensively specified by limited standards or specifications (Architectural Institute of Japan 2004; American Society of Civil Engineers 2010; Ministry of Communications of the People's Republic of China 2018). Therefore, the wind characteristics in mountainous regions have been studied in recent years and many outstanding contributions have been made based on field measurements (Fenerci et al., 2017;Huang et al., 2019;Li et al., 2015Li et al., , 2017aWang et al., 2020), wind tunnel experiments (Bullard et al., 2000;Hu et al., 2016;Li et al., 2017b;Zhang et al., 2020) and numerical simulations (Han et al., 2018;Hong et al., 2017;Li et al., 2016;Zhang et al., 2019b). ...
Long-span bridges are strongly sensitive to wind, and it is important to accurately assess the wind field of bridge sites. Thus, to strengthen the understanding of the wind field of deep-cut gorges and study the influence effect of the wind direction on the wind characteristic parameters, the wind data from an ultrasonic anemometer installed on a catwalk and bridge tower were used to perform statistical analysis. The results show that the wind characteristic parameters (including wind speed, wind attack angle, turbulence intensity and turbulence integral scale) vary greatly between directions. In addition, the wind speed, turbulence intensity and turbulence integral scale in all directions follow the log-normal distribution, whereas the attack angle follows the normal distribution. At the same time, the effects of incoming flow direction on the distribution of wind parameters differs between spatial points. In addition, without considering the influence of wind speed, the statistical distribution of the attack angle and turbulence intensity has adverse effects on the wind resistance of the structure. Therefore, the combined effect of wind speed and incoming flow direction should be considered in the wind resistance of structures.
... Although Baoshan site is still located in the mountain area, its terrain is relatively flat, so the mean wind direction fluctuates greatly in different seasons, but the wind direction generally remains as the south. It is also pointed out in some literatures that due to the influence of local topography, the wind direction in mountainous areas has a dominant direction (Zhang et al., 2020(Zhang et al., , 2019b. For diurnal wind speed profiles for six sites, mean wind speed is closely related to the rise and fall of the sun. ...
As a clean and highly valuable renewable energy, wind energy has gradually become an important
branch of energy technology. By means of measurement methods, the wind characteristics, energy
applications for distributed wind energy source (DWES) in six sites in Henduan Mountains and
economic evaluation are investigated. According to the results, the wind characteristics including wind
speed and wind direction in mountainous regions are affected significant by topography. Wind speed is
season-dependent, while the mean wind direction is not. The maximum wind speed occurs in spring,
the minimum wind speed occurs in summer. As for extreme value distribution, the wind data in
mountainous areas are more in line with Frechet distribution type. By using Weibull distribution
function, Weibull parameters are calculated and energy potential are estimated with five methods.
Estimation methods suitable for coastal areas can also be used for energy assessment in mountain
environments. The maximum wind power density is over 200 W/m2
, occurred in Zanli site, while
the minimum value is less than 10 W/m2
in Yimen-A. Similar to mean wind characteristics, wind
power density shows strong seasonality, with the maximum value in spring and the lowest value
in summer. In addition, power generation facilities should be built in valleys or on the top of the
mountain, and should not be built in the flat land surrounded by mountains. And the total cost of
1kWh wind-generated electricity is 0.305 CNY/kWh and 0.406 CNY/kWh with different type of wind
turbine.
... Based upon previous works of the authors (Niu et al., 2019;Ti et al., 2019;Zhang et al., 2019;Zhu et al., 2018aZhu et al., , 2018bZhang, 2018, 2016), an innovative WTB interaction analysis framework that utilizes the LAI-E model to reproduce realistic traffic behavior is developed, in which the general procedure is displayed in Fig. 3. ...
The performance of a long-span bridge under strong wind and traffic loads is of great importance to ensure the functionality and the serviceability of the bridge as well as the safety of running vehicles. In this paper, an innovative wind-traffic-bridge (WTB) interaction model for predicting the dynamic performance of the long-span bridge and running vehicles under the crosswind is proposed, considering realistic traffic behavior and vehicle inertia force. In this regard, the LAI-E traffic simulation model aiming to faithfully reproduce realistic traffic flow is developed by integrating the kinetics theory, vehicle capabilities, and driver reactions. The results indicate that using the traditional NaSch traffic model results in a significant overestimation of the vehicle lateral response under a windy environment, whereas the LAI-E traffic model can overcome this issue by ensuring a smooth speed transition during the vehicular acceleration/deceleration process. Additionally, when the vehicle accelerates or decelerates at the emergency capability, the additional pitching moment caused by the vehicle inertia force can result in remarkable increase of vertical wheel contact forces. The present study suggests the necessity of considering both realistic traffic behavior and vehicle inertia force during the WTB analysis.
