Abstract
This work investigates the effects of transverse inclination on an aeroelastic prism through forced-vibration wind
tunnel experiments. The aerodynamic characteristics are tri-parametrically evaluated under different wind speeds, inclination
angles, and oscillation amplitudes. Results show that transverse inclination fundamentally changes the wake phenomenology by
impinging the fix-end horseshoe vortex and breaking the separation symmetry. The aftermath is a bi-polar, one-and-for-all
change in the aerodynamics near the prism base. The suppression of the horseshoe vortex unleashes the Karman vortex, which
significantly increases the unsteady crosswind force. After the initial morphology switch, the aerodynamics become independent
of inclination angle and oscillation amplitude and depend solely on wind speed. The structure's upper portion does not feel the
effect, so this phenomenon is called Base Intensification. The phenomenon only projects notable impacts on the low-speed and
VIV regime and is indifferent in the high-speed. In practice, Base Intensification will disrupt the pedestrian-level wind
environment from the unleashed Bernard-Karman vortex shedding. Moreover, it increases the aerodynamic load at a structure
base by as much as 4.3 times. Since fix-end stiffness prevents elastic dissipation, the load translates to massive stress, making
detection trickier and failures, if they are to occur, extreme, and without any warnings.
Address
Zengshun Chen,Yemeng Xu, Sijia Li, Jianmin Hua, and Xuanyi Xue:School of Civil Engineering, Chongqing University, Chongqing 400045, China
Jie Bai:China State Construction Silk Road Investment Group Co., Ltd., Xian, People's Republic of China
Cruz Y. Li:Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology,
Clear Water Bay, Kowloon, Hong Kong, China
Abstract
The along-wind coefficient is the key parameter for wind load calculations in tower crane structure design. It is
often calculated using overall parameter characteristics, which may lead to inaccurate results. In this study, six types of tower
masts and four types of tower jibs with different overall structural characteristics and member characteristics are established.
Through wind tunnel force tests and CFD numerical simulation, the along-wind coefficient of the overall structure and each
member are obtained. Based on the characteristics of the slenderness ratio and spacing ratio of the members, a mathematical
model for calculating the along-wind coefficient of the tower crane structure is proposed. The calculated results are in
accordance with the wind tunnel test results. The maximum relative error is -6.25%, and the minimum relative error is 0.68%.
To ensure accuracy, it is necessary to calculate the along-wind coefficient of the tower crane structure based on the load of each
structure member rather than using overall parameter characteristics.
Key Words
along-wind coefficient; CFD; structure member; tower crane; wind tunnel test
Address
Wei Chen:School of mechanical engineering, Shijiazhuang Tiedao University, No.17, North 2nd Ring Road East, Shijiazhuang, P. R. China
Xianrong Qin and Zhigang Yang:School of mechanical engineering, Tongji University, 1239 Si-ping Road, Shanghai, P. R. China
Abstract
Suspended monorail trains (SMTs) are sensitive to crosswinds, and instantaneous aerodynamic characteristics of
two SMTs passing each other under crosswinds are particularly complicated. In this study, a pressure measurement test is carried
out on stationary train-bridge models arranged in several critical positions. In addition, a validated moving CFD model is
developed with the dynamic and sliding mesh method to explore the realistic train movement effects. The time-varying
aerodynamic forces and surface pressure distribution on, as well as the flow field around running trains and bridges during trains
passing each other, are computed in detail to illustrate the shielding effect of the upstream train. The results reveal that when two
trains begin to pass each other, the side force coefficient of the downstream train reduces significantly to negative values due to
the wind shielding effect of the upstream train. The moving model successfully captures that airflow is separated on the middle
line of the head car for the suspended monorail train, and the surrounding bluff double-beams can significantly affect the flow
structures around the train. The wind shielding effect of the upstream train on the downstream train will weaken as the relative
yaw angle decreases.
Key Words
aerodynamic characteristics; CFD simulation; crosswind; suspended monorail train; wind tunnel test
Address
Yulong Bao:Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, 611756 Chengdu, P.R. China
Wanming Zhai, Chengbiao Cai and Shengyang Zhu:State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, 610031 Chengdu, P.R. China
Yongle Li:1)National Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University, 611756 Chengdu, P.R. China
2)Wind Engineering Key Laboratory of Sichuan Province, Southwest Jiaotong University, 610031 Chengdu, P.R. China
Abstract
The aerodynamic characteristics of a circular cylinder with a wavy splitter plate were experimentally studied,
specifically the potential reduction of drag and fluctuations in drag. To study the individual effects of amplitude and wavelength,
the experiments were conducted by varying one parameter at a time while holding the other one constant. To study the effect of
amplitude (A), the wavelength to diameter ratio (λ⁄D) was fixed at 0.115 and the amplitude to diameter ratio (A⁄D) was varied
as 0.005, 0.010, 0.015 and 0.020. Similarly, to study the effect of wavelength, A⁄D was fixed as 0.020 and λ⁄D was varied as
0.46, 0.23, 0.15 and 0.12. Analysis of the data indicated that the wavy splitter plate caused a significant reduction in both the
magnitude and the fluctuation of drag. The variation of aerodynamic forces and the fluctuations with them corresponding to
different Reynolds numbers were computed and the spectral aspects of fluctuating forces due to vortex shedding is analysed and
effective reduction in both shedding frequency and magnitude was observed.
Address
Liang Gao, J. :School of Civil Engineering and Architecture, Xi'an University of Technology, Xi'an 710048, China
J. Jegadeeshwaran, S. Ramaswami and S. Nadaraja Pillai:Turbulence & Flow Control Lab, School of Mechanical Engineering, SASTRA Deemed University, Tamil Nadu 613401, India
S. B. M. Priya:School of Electrical and Electronics Engineering, SASTRA Deemed University, Tamil Nadu 613401, India
Abstract
In the Structural Health Monitoring (SHM) system of civil engineering, data missing inevitably occurs during the
data acquisition and transmission process, which brings great difficulties to data analysis and poses challenges to structural
health monitoring. In this paper, Convolution Neural Network (CNN) is used to recover the nonstationary wind speed data
missing randomly at sampling points. Given the technical constraints and financial implications, field monitoring data samples
are often insufficient to train a deep learning model for the task at hand. Thus, simulation combined transfer learning strategy is
proposed to address issues of overfitting and instability of the deep learning model caused by the paucity of training samples.
According to a portion of target data samples, a substantial quantity of simulated data consistent with the characteristics of target
data can be obtained by nonstationary wind-field simulation and are subsequently deployed for training an auxiliary CNN
model. Afterwards, parameters of the pretrained auxiliary model are transferred to the target model as initial parameters, greatly
enhancing training efficiency for the target task. Simulation synergy strategy effectively promotes the accuracy and stability of
the target model to a great extent. Finally, the structural dynamic response analysis verifies the efficiency of the simulation
synergy strategy.
Key Words
missing data recovery; nonstationary simulation; nonstationary wind speed; simulation synergy strategy; transfer
learning
Address
Qiushuang Lin:1)College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China
2)Henan New Environmentally-Friendly Civil Engineering Materials Engineering Research Center, Xinyang Normal University,
Xinyang 464000, China
Xuming Bao:1)Institute of Structural Engineering, Zhejiang University, Hangzhou 310058, China
2)School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China
Ying Lei:School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China
Chunxiang Li:School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China
