Abstract
In this paper, the aerodynamic performance of the Basalt Fiber Reinforced Polymer (BFRP) bionic plate wind
turbine blade with different pitch angles, incoming wind speeds and rotational speeds was investigated. The influence of the
tower shadow effect on the wake velocity, aerodynamic load, displacement and stress of BFRP bionic plate wind turbine blade
under the rated condition was obtained by establishing the whole machine model including tower tube, and the error analysis of
the simplified calculation formula of aerodynamic load was carried out. Results show that the incoming wind speed has a great
influence on the stress and wind speed backflow and the tower shadow effect has a great influence on the horizontal thrust and
torque of BFRP bionic plate wind turbine blade. The simplified calculation formula of aerodynamic load can accurately simulate
the displacement and stress trend of BFRP bionic plate wind turbine blade and the recommended values of the pitch angle,
incoming wind speed and the rotational speed of BFRP bionic plate wind turbine blade were given. The research results can
provide the dynamic parameter reference for the engineering design of BFRP bionic plate wind turbine blade.
Address
Tengteng Zheng:1)The Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University,
Nanjing, Jiangsu Province 211189, China
2)School of Civil Engineering, Southeast University, Nanjing, Jiangsu Province 211189, China
3)School of Civil Engineering, The University of Queensland, St. Lucia, QLD 4072, Australia
Caiqi Zhao:1)The Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University,
Nanjing, Jiangsu Province 211189, China
2)School of Civil Engineering, Southeast University, Nanjing, Jiangsu Province 211189, China
Lijie Shang:1)The Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University,
Nanjing, Jiangsu Province 211189, China
2)School of Civil Engineering, Southeast University, Nanjing, Jiangsu Province 211189, China
Abstract
The current research on the wind resistance of standing seam metal roofs primarily focuses on the failure modes of
the entire roof panel and the contact areas between the seams and supports, with little consideration given to the synergy
between the roof seam reinforcements, the web, and the supports. As a result, the failure mechanisms of roof systems cannot be
accurately represented. This paper, based on wind uplift tests and ABAQUS simulation modeling, provides a detailed analysis of
the wind resistance and failure mechanisms of reinforced standing seam metal roof systems. The study reveals that the
deformation and failure of the roof system under wind load can be divided into three stages: elastic deformation, plastic
deformation, and failure. In the elastic deformation stage, the areas with higher stress are mainly distributed in the mid-span of
the roof panels and along the ribs, where the roof stress remains below the material's yield strength, and the displacement at the
roof panel seams is minimal. During the plastic deformation stage, as the load increases, significant vertical deformations appear
in the roof panels, the lateral displacement at the seams gradually increases, and the stress growth is pronounced. Without
reinforcement, the roof panel withstands a maximum wind pressure of 3.2 kPa, with a central vertical displacement of 109 mm,
while the ultimate lateral displacement at the seams reaches 2.3 mm, resulting in unseating failure, marking the structural failure.
With reinforcement, the roof panel can withstand a maximum wind pressure of 4.3 kPa, corresponding to a central vertical
displacement of 122 mm. The growth of lateral displacement at the seams slows down, and the reinforcement significantly
suppresses seam displacement. As the load continues to increase, the reinforcements and the web work synergistically,
exhibiting reciprocating counterclockwise and clockwise rotations, with the maximum lateral displacement at the seams
increasing to 3.05 mm. Ultimately, unseating occurs at the roof panel seams or tearing at the web. Therefore, the reinforcement
system significantly enhances the wind resistance of the roof system, providing theoretical guidance for wind-resistant design in
roofing engineering.
Key Words
failure criterion; nite element simulation; metal roof; reinforcement system; standing seam; wind uplift failure
Address
Zhitao Zheng:1)China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
2)Anhui University of Science& Technology, Huainan Anhui, 232001, China
Wenbing Shen:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Chuang Li:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Sheng Li:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Hongliang Deng:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Mengjie Lu:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Cheng Zhang:China Construction Fifth Engineering Division Second Construction Co., Ltd, Hefei Anhui,230041, China
Abstract
The multiple-fan wind tunnel is an important facility for reproducing target wind field. Existing control methods for
the multiple-fan wind tunnel can generate wind speeds that satisfy the target statistical characteristics of a wind field (e.g., power
spectrum). However, the frequency-domain features cannot well represent the nonstationary winds of extreme storms (e.g.,
downburst). Therefore, this study proposes a multiple-fan wind tunnel control scheme based on Deep Reinforcement Learning
(DRL), which will completely transform into a data-driven closed-loop control problem, to reproduce the target wind field in the
time domain. Specifically, the control scheme adopts the Deep Deterministic Policy Gradient (DDPG) paradigm in which the
strong fitting ability of Deep Neural Networks (DNN) is utilized. It can establish the complex relationship between the target
wind speed time series and the current control strategy in the DRL-agent. To address the fluid memory effect of the wind field,
this study innovatively designs the system state and control reward to improve the reproduction performance based on historical
data. To validate the performance of the model, we established a simplified flow field based on Navier Stokes equations to
simulate a two-dimensional numerical multiple-fan wind tunnel environment. Using the strategy of DRL decision maker, we
generated a wind speed time series with minor error from the target under low Reynolds number conditions. This is the first time
that the AI methods have been used to generate target wind speed time series in a multiple-fan wind tunnel environment. The
hyperparameters in the DDPG paradigm are analyzed to identify a set of optimal parameters. With these efforts, the trained
DRL-agent can simultaneously reproduce the wind speed time series in multiple positions.
Key Words
active flow control; DDPG paradigm; deep reinforcement learning; multiple-fan wind tunnel; wind speed
reproduction
Address
Qingshan Yang:1)Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University),
Ministry of Education, Chongqing, China, 400045
2)School of Civil Engineering, Chongqing University, Chongqing, China, 400045
Zhenzhi Luo:School of Civil Engineering, Chongqing University, Chongqing, China, 400045
Ke Li:1)Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University),
Ministry of Education, Chongqing, China, 400045
2)School of Civil Engineering, Chongqing University, Chongqing, China, 400045
Teng Wu:Department of Civil, Structural & Environmental Engineering, The University at Buffalo, New York, US, 14260
Abstract
An accurate assessment of aerodynamic effects on structures is essential for a reliable wind design for high-rise
buildings. Turbulence model is a key ingredient of computational fluid dynamics (CFD) in calculating the wind flow fields. This
paper aims to identify the properties of representative RANS and LES models particularly for wind load determination. The
models investigated are the realizable k-
Key Words
CFD; high-rise building; RANS; LES; wind effect; wind tunnel test
Address
Min Kyu Kim:Department of Architecture and Architectural Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
Soonpil Kang:Department of Applied Mathematics, Naval Postgraduate School, 1 University Circle, Monterey, 93943, CA, U.S.A.
Thomas H.-K. Kang:Department of Architecture and Architectural Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
Abstract
This paper reviews measurements of wind profiles in the atmospheric boundary layer in strong wind (thermally
neutral) conditions over open water and the ocean, and the variation of the roughness parameters with mean wind speed. Based
on the wind data recorded on the coast of the island of FrØya (Norway) in the 1980s, and dropwindsonde profiles in hurricanes,
the paper shows that 'capping', or saturation, of the surface drag coefficient becomes apparent at a mean wind speed at 10 m
height of about 25 m/s. Wind speed models used in the offshore industries were investigated, (the ISO model, the API 'tropical
cyclone' model and the IEC model). The ISO model, although based on good quality data from FrØya, does not allow for the
saturation of the roughness above about 25-30 m/s, even though that was apparent in the FrØya data. 'Capping' of the
aerodynamic roughness length for wind speeds greater than 28 m/s is represented appropriately in the API 'tropical
cyclone' model, and hence the model represents the mean wind properties reasonably well in severe tropical cyclone conditions.
However, the turbulence intensities in the API 'tropical cyclone' model, based on over-land measurements (ESDU), are overpredicted for winds over the ocean, at heights above 20 m. The IEC models are entirely based on over-land measurements, and
hence are not representative of over-water conditions such as those required for offshore wind farms. New model profiles for
over-ocean strong winds are proposed for wind speeds up to hurricane strength, based on the ISO profiles, but with capping of
the surface drag coefficient at a value of 0.0025, at a mean wind speed at 10m height of 25 m/s. The proposed turbulence
intensity model is also a revision of the ISO profile, also with capping above 25 m/s. The proposed model profiles are in better
general agreement with recorded data in strong winds than those currently specified in international standards, and are applicable
to all wind speeds in synoptic-scale events, including those in tropical cyclones, typhoons and hurricanes. As well as the FrØya
data, the revised strong-wind models are supported by measurements from Atlantic hurricanes, gales in the North Sea,
landfalling typhoons in Japan and Cyclone 'Yasi' in Queensland, Australia.
Key Words
ocean; profile; roughness; saturation; turbulence; wind speed
Address
John D. Holmes:JDH Consulting, PO Box 269, Mentone, Victoria, 3194, Australia
