Abstract
This study analyzes long-term wind speed data from mountainous areas, focusing on the non-stationary
characteristics of the wind field and their impact on wind speed simulations. Due to the complexity of wind speeds in
mountainous regions, the paper proposes a correction model combining time-varying mean wind speed and non
stationary wind speed models. Through systematic preprocessing and stationarity testing, significant non-stationary
features are identified, particularly in high wind speed ranges during strong gusts and complex terrain conditions. The
time-varying mean wind speed and fluctuating wind speed show distinct evolving patterns, impacting simulation
accuracy. To capture these characteristics, the Priestley Evolutionary Power Spectral Density (EPSD) method is
employed to fit the time-varying power spectrum, creating a time-frequency model for non-stationary wind fields in
mountainous areas. Compared to traditional stationary model, the proposed correction model provides better
accuracy in handling multi-peak structures, low-frequency variations, and turbulence. A clustering analysis of
multiple measured correction models is used to derive a representative model, offering more reliable parameters for
wind field simulations and improving simulation accuracy. This research provides new methods and data support for
simulating non-stationary wind fields.
Key Words
measured wind speed; modulation function; non-stationary; time-varying mean wind speed
model
Address
Xinqi Zhang: School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Jun Hu: School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Yukun Zhou: School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Abstract
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author's actual abstract.
Abstract
This study investigates the vibration characteristics of 10 MW, 8 MW, and 6.7 MW large-capacity jacket
supported offshore wind turbines (OWTs) with varying conditions and foundation types in a deep-sea wind farm. By
using an improved Natural Excitation Technique combined with Eigensystem Realization Algorithm (NExT-ERA)
to accurately identify modal parameters of OWTs under operational harmonic interference across six operational
phases (shutdown, startup, grid-connection, transition, rated speed, cut-out) using high-precision accelerometers (50
Hz) and SCADA data. Research on vibration characteristics revealed that the improved NExT-ERA algorithm,
reduced harmonic-induced errors in fundamental frequencies by 0.2–0.5 Hz during operational states. Still, due to the
complex operation of the grid-connection phase and the transition phase, the modal recognition showed a positive
deviation and has a large degree of discreteness. Besides, the influence of foundation type on vibration amplitude is
more significant near the foundation, while the effects of installed capacity and turbine manufacturer dominate closer
to the tower. Advanced aerodynamic designs and modern control optimizations significantly reduce vibration
amplitudes, thereby enhancing structural durability, as demonstrated by the greater vibration amplitudes of the 6.7
MW turbine compared to larger, more optimized turbines. While a single sensor can identify overall modes, the
tower top's sensitivity to complex loading necessitates multi-level monitoring to comprehensively capture vibration
modes, ensuring robust structural health assessment.
Abstract
Skew wind and tower interference have significant impacts on the buffeting performance of cable-stayed
bridges in the cantilever state. Based on a cable-stayed bridge, the effects of skew wind and tower aerodynamic
interference on the aerodynamic admittance function (AAF) and buffeting response of the bridge at the maximum
cantilever state are investigated. The results indicate that the AAFs are significantly smaller than the Sears function,
particularly in the low-frequency region that contributes most to structural buffeting behavior. Skew wind and tower
interference notably influence the bridge AAF. As the wind yaw angle increases, AAF generally exhibit a
monotonically decreasing trend, indicating that the orthogonal wind direction being the most critical condition. For the
main girder located leeward side of the tower, a larger wind yaw angle leads to more pronounced characteristic
turbulence effects from the tower and greater local abrupt changes in AAF. Based on test results, empirical models of
AAF under different wind yaw angles, accounting for skew wind and tower interference effect, are proposed. Under
skew wind conditions with a same yaw angle, the presence of tower interference increases the bridge buffeting
response. Furthermore, the tower interference effect is related to the distance between the girder segment and the tower,
diminishing as the distance increases. Therefore, for the most critical cantilever state of cable-stayed bridges, the
identification of AAF must realistically consider the effects of skew wind and tower interference under various
conditions; otherwise, the evaluation of structural buffeting performance may be significantly inaccurate.
Key Words
aerodynamic admittance function; bridge under construction state; buffeting response; cable
stayed bridge under construction state; skew wind
Address
Bin Jian:School of Civil Engineering and Architecture, Southwest University of Science and Technology,
No. 59, Middle Section of Qinglong Avenue, Fucheng District, Mianyang 621010, Sichuan, China
Jinhao Li:School of Civil Engineering and Architecture, Southwest University of Science and Technology,
No. 59, Middle Section of Qinglong Avenue, Fucheng District, Mianyang 621010, Sichuan, China
Yu Qin:School of Civil Engineering, Chongqing University,
No. 83 Shabeijie, Shapingba District, Chongqing 400045, China
Yinping Ma:School of Civil Engineering, Chongqing University, No. 83 Shabeijie, Shapingba District, Chongqing 400045, China
Mingshui Li:Research Centre for Wind Engineering, Southwest Jiaotong University, No. 111 North 1st Section of second Ring Road, Chengdu 610031, Sichuan, China
Minghao Chen:School of Civil Engineering and Architecture, Southwest University of Science and Technology,
No. 59, Middle Section of Qinglong Avenue, Fucheng District, Mianyang 621010, Sichuan, China
Zhiyuan Jiang:China Railway Jinan Group Co Ltd., No. 2 Zhanqian Road, Tianqiao District, Jinan 250001, Shandong, China
Yongqing Li:CCCC First Highway Consultants Co., Ltd., No. 63, Keji second Road, Gaoxin District, Xi'an 710075, Shanxi, China
Abstract
In order to reduce the winter wind damage of solar greenhouses, a windbreak structure is designed, and
its parameters (length and height) are comparatively evaluated using computational fluid dynamics (CFD) under
different incoming air velocity (4 m∙s-1 or 13.9 m∙s-1) and different ventilation conditions (vents are fully closed or
opened). The results shows that the windbreak structure with a height of 0.5 m and a length of 10 m can more
effectively reduce the wind load shape coefficient compared to other cases. At two incoming air velocities (4 m∙s-1
and 13.9 m∙s-1), the wind load shape coefficient near the west gable (the LP1 and UP1 areas) is reduced by 23.57%
and 24.88% compared with the non-windbreak structure when the greenhouse is closed, and by 12.12% and 15.97%
when the greenhouse is opened. The average WRM (wind resistance efficiency per unit material) value of this
windbreak structure specification is 0.61, and compared to other cases, resource utilization is more efficient under
different conditions. In this study, the maximum deformation deflection of the windbreak structure under different
conditions was 0.75 mm, meeting the requirements and demonstrating its practicality.
Key Words
computational fluid dynamics; natural ventilation; solar greenhouse; wind pressure coefficient;
windbreak structure
Address
Guanglin Hu:China Agricultural University Yantai Research Institute, No. 2006, Binhai Mid-Rd, Gaoxin Zone, Yantai, Shandong, P. R. China
Xiaoyan Fan:China Agricultural University Yantai Research Institute, No. 2006, Binhai Mid-Rd, Gaoxin Zone, Yantai, Shandong, P. R. China
Yunfei Ma: China Agricultural University Yantai Research Institute, No. 2006, Binhai Mid-Rd, Gaoxin Zone, Yantai, Shandong, P. R. China
