Abstract
To investigate the optimal aerodynamic parameters of wind barriers for the T-beam of high-speed railway (HSR)
bridge and the wind field of the wind barrier-train-bridge system, the three-component forces of the system and the wind
pressure on the vehicle surface were tested and analyzed through the sectional model wind test. The effects of wind velocity,
with/without wind barrier, the height of wind barrier, and the air permeability of the wind barrier on the aerodynamic
characteristics of the train-bridge system are discussed. Additionally, a CFD numerical model is constructed to evaluate the wind
environment of the bridge surface with/without the wind barrier, and the impact of wind barrier on the running safety of vehicles
are analyzed. Comprehensively considering the running safety of the train and the wind-resistant stability of the bridge, it is
more appropriate to set the wind barrier height H as 3.5 m and the porosity β as 30% respectively.
Abstract
By using a computational program of three-dimensional aerostatic and aerodynamic stability analysis of long-span
bridges under skew wind, the dynamic characteristics and structural stability (including the aerostatic and aerodynamic stability)
of a three-tower cable-stayed-suspension hybrid bridge with main span of 1 400 meters are investigated numerically under skew
wind, and the skew wind and aerostatic effects on the aerostatic and aerodynamic stability of three-tower cable-stayedsuspension hybrid bridge are ascertained. The results show that the three-tower cable-stayed-suspension hybrid bridge is a longspan structure with greater flexibility, and it is more susceptible to the wind action. The aerostatic instability of three-tower
cable-stayed-suspension hybrid bridges is characterized by the coupling of vertical bending and torsion of the girder, and the
skew wind does not affect the aerostatic instability mode. The skew wind has positive or negative effects on the aerostatic
stability of the bridge, the influence is between -5.38% and 4.64%, and in most cases, it reduces the aerostatic stability of the
bridge. With the increase of wind yaw angle, the critical wind speed of aerostatic instability does not vary as the cosine rule as
proposed by the skew wind decomposition method, the skew wind decomposition method may overestimate the aerostatic
stability, and the maximum overestimation is 16.7%. The flutter critical wind speed fluctuates with the increase of wind yaw
angle, and it may reach to the minimum value under the skew wind. The skew wind has limited effect on the aerodynamic
stability of three-tower cable-stayed-suspension hybrid bridge, however the aerostatic effect significantly reduces the
aerodynamic stability of the bridge under skew wind, the reduction is between 3.66% and 21.86%, with an overall average drop
of 11.59%. The combined effect of skew and static winds further reduces the critical flutter wind speed, the decrease is between
7.91% and 19.37%, with an overall average decrease of 11.85%. Therefore, the effects of skew and static winds must be
comprehensively considered in the aerostatic and aerodynamic stability analysis of three-tower cable-stayed-suspension hybrid
bridges.
Address
Xin-Jun Zhang:1)College of Civil Engineering, Zhejiang University of Technology, Hangzhou, 310023, P.R. China
2)Key Laboratory of Civil Engineering Structures & Disaster Prevention and Mitigation Technology of Zhejiang Province,
Hangzhou, 310023, P.R. China
Li Bowen:College of Civil Engineering, Zhejiang University of Technology, Hangzhou, 310023, P.R. China
Nan Zhou:College of Civil Engineering, Zhejiang University of Technology, Hangzhou, 310023, P.R. China
Abstract
To model the aeroelasticity in vortex-induced vibrations (VIV) of slender tubular towers, this paper presents an
approach where the aerodynamic damping distribution along the height of the structure is calculated not only as a function of the
normalized lateral oscillation but also considering the local incoming wind velocity ratio to the critical velocity (velocity ratio).
The three-dimensionality of aerodynamic damping depending on the tower's displacement and the velocity ratio has been
observed in recent studies. A contour map model of aerodynamic damping is generated based on the forced vibration tests. A
sectional calculation procedure based on the spectral method is developed by defining the aerodynamic damping locally at each
increment of height. The proposed contour map model of aerodynamic damping and the sectional calculation procedure are
validated with full-scale measurement data sets of a rotorless wind turbine tower, where good agreement between the prediction
and measured values is obtained. The prediction of cross-wind response of the wind turbine tower is performed over a range of
wind speeds which allows the estimation of resulting fatigue damage. The proposed model gives more realistic prediction in
comparison to the approach included in current standards.
Abstract
A reliable wind speed forecasting method is crucial for the applications in wind engineering. In this study, the
generalized S-transform (GST) is innovatively applied for wind speed forecasting to uncover the time-frequency characteristics
in the non-stationary wind speed data. The improved grey wolf optimizer (IGWO) is employed to optimize the adjustable
parameters of GST to obtain the best time-frequency resolution. Then a hybrid method based on IGWO-optimized GST is
proposed to validate the effectiveness and superiority for multi-step non-stationary wind speed forecasting. The historical wind
speed is chosen as the first input feature, while the dynamic time-frequency characteristics obtained by IGWO-optimized GST
are chosen as the second input feature. Comparative experiment with six competitors is conducted to demonstrate the best
performance of the proposed method in terms of prediction accuracy and stability. The superiority of the GST compared to other
time-frequency analysis methods is also discussed by another experiment. It can be concluded that the introduction of IGWOoptimized GST can deeply exploit the time-frequency characteristics and effectively improving the prediction accuracy
Key Words
extreme learning machine; generalized S-transform; improved grey wolf optimizer; long short-term memory;
wind speed forecasting
Address
Ruwei Ma:School of Civil Engineering, Shanghai Normal University, Shanghai, 201418, China
Zhexuan Zhu:Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China
Chunxiang Li:Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China
Liyuan Cao:Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China
Abstract
This study presents a comprehensive investigation of wind load characteristics and wind-induced responses
associated with different wind incidence angles and terrains of the 1000kV UHV substation frame. High-frequency force
balance (HFFB) force measurement wind tunnel tests are conducted on the overall and segment models to characterize wind
loads characteristics such as the aerodynamic force coefficients and the shape factors. The most unfavorable wind incidence
angles and terrains for aerodynamic characteristics are obtained. A finite element model of the substation frame is built to
determine the wind-induced response characters based on the aerodynamic force coefficients and bottom forces of the segment
models. The mean and root mean square (RMS) values of displacement responses at different heights of the frame structure are
compared and analyzed. The influence of wind incidence angle and terrains on wind-induced responses is also examined. The
displacement responses in terms of the crest factor method are subsequently transformed into dynamic response factors. The
recommended values of dynamic response factors at four typical heights have been proposed to provide a reference for the wind
resistance design of such structures.
Key Words
1000kV UHV substation frame; aerodynamic force coefficient; dynamic response factor HFFB; shape factor;
wind-induced response
Address
Hao Tang:College of Civil Engineering, Heilongjiang University, Harbin 150086, P.R. China
Fanghui Li:College of Civil Engineering, Heilongjiang University, Harbin 150086, P.R. China
Xudong Zhi:1)Key Lab of Structures Dynamic Behavior and Control (Harbin Institute of Technology), Ministry of Education, Harbin 150090, P.R. China
2)Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters (Harbin Institute of Technology), Ministry of Industry and
Information Technology, Harbin 150090, P.R. China
Jie Zhao:The Second Supervision and Inspection Station of Construction Engineering Quality of Anhui Province, Hefei 230000, P.R. China
