Abstract
A wind power generation system consists electrical, mechanical, aerodynamics and structural dynamics in
its model. However, the most of the reported system dynamic models include either electrical and mechanical
dynamics or structural and aerodynamics. This may sometimes lead to imperfect analysis when someone is observing
impact of the electrical disturbance onto the structural dynamics. Therefore, this paper presents the complete model of
the wind power system considering aerodynamics and structural dynamics of the blade along with the electrical and
mechanical power balance. Also, the detection of the blade vibration using electrical measurements have been
performed through a nonlinear estimator, named Unscented Kalman Filter (UKF) which may further helps to design
a controller without additional sensors. The estimation of the impact of the electrical disturbance onto the blade
vibrations provide insights into the early detection and observation of the blade vibrations. It was observed that a
frequency of edgewise vibrations of the blades of 1.159 Hz other than the fundamental frequency corresponding to the
speed of the rotation of the wind turbine, is introduced when the system subjected to an electrical disturbance and it
should be taken care of during the control design. Further, the UKF estimates these vibrations perfectly, closely
matching with the actual frequency with an estimation error of only 0.35%. The structural model is prepared using
Euler–Lagrangian method (ELM) while Blade Element Momentum method (BEMM) is used for aerodynamic power
and forces. The structural and blade geometry data of NREL
Key Words
DFIG; blade element momentum method; blade vibrations; Euler–Lagrangian approach; nonlinear estimation
Address
Vikas Bhalla:Department of Electrical Engineering, Engineering College, Bikaner, Rajasthan -334004, India
Ganesh P. Prajapat:Department of Electrical Engineering, Engineering College, Bikaner, Rajasthan -334004, India
Abstract
Wind-hail disasters often cause severe damage to photovoltaic structures. Accurately predicting the peak
hail impact force under wind-hail conditions is essential for the safe design, structural optimization, and service life
evaluation of photovoltaic systems. In this study, based on the self-developed hail impact simulation integrated device,
extensive wind-hail coupled experiments were conducted to obtain the peak impact force of hail on photovoltaic
structures. Then, a correlation analysis was conducted on the independent and dependent variables. Finally, based on
the machine learning prediction framework proposed in this paper, the BP, PSO-BP, and FA-BP neural network models
were established. The results show that hail velocity exerts the most pronounced effect on the maximum hail impact
force. Conversely, turbulence exhibits an inverse relationship with this peak force. In terms of model robustness and
accuracy, the BP, FA-BP, and PSO-BP models all showcase commendable performance. Notably, the FA-BP model
stands out with the highest robustness and precision, trailed by the PSO-BP model. These findings are expected to offer
a reference for wind-hail resistance experiments on photovoltaic structures and provide insights for predicting the peak
hail impact force under wind-hail coupling conditions.
Key Words
BP neural network; firefly algorithm; photovoltaic structures; PSO algorithm; wind-hail coupled
experiments; wind tunnel test
Address
Yimi Dai:School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
Taiting Liu:School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
Yixin Li:School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
Ying Xu:School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
Wei Wang:School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
Abstract
Under building opening conditions, wind-induced internal pressure may significantly alter the structural
behavior of the building envelope. This study investigates the dynamic characteristics and response patterns of wind
induced internal pressure through transient CFD simulations, proposing a computational method for quantifying
Helmholtz resonance frequency in buildings with openings. The influence of opening size, quantity, and location on
dynamic characteristics and wind load responses was systematically examined. Key findings reveal: 1) The proposed
method effectively predicts Helmholtz resonance frequencies, demonstrating consistent trends with theoretical models;
2) The Helmholtz frequency exhibits strong linear correlation with opening area—larger openings increase Helmholtz
frequencies while reducing damping ratios, with leeward openings substantially diminishing damping ratios; 3)
Changes in indoor and outdoor pressures often exhibit an opposite trend to the net pressure, while an increase in the
damping ratio typically leads to higher internal pressure. These results provide critical theoretical support for
determining wind loads on openable curtain wall panels and roof penetrations in architectural engineering.
Key Words
building wind engineering; CFD; Helmholtz resonance; wind-induced internal pressure
Address
Xiangqiu Fu:1)Shenzhen Technology Institute of Urban Public Safety, Key Laboratory of Urban Safety Risk Monitoring and
Early Warning, Ministry of Emergency Management, Shenzhen, Guangdong, 518023, China
2)State Key Laboratory of Building Safety and Built Environment, China Academy of Building Research,
Beijing 100013, China
Nan Jin:1)1Shenzhen Technology Institute of Urban Public Safety, Key Laboratory of Urban Safety Risk Monitoring and
Early Warning, Ministry of Emergency Management, Shenzhen, Guangdong, 518023, China
2)Shenzhen Key Laboratory of Urban Disasters Digital Twin, Shenzhen, Guangdong,518023, China
Xichen Zhang:Institute of Building Environment and Energy, China Academy of Building Research, Beijing 100013, China
Yuan Cao:State Key Laboratory of Building Safety and Built Environment, China Academy of Building Research,
Beijing 100013, China
Siyuan Ma:State Key Laboratory of Building Safety and Built Environment, China Academy of Building Research,
Beijing 100013, China
Abstract
Wind-driven rain (WDR) research has predominantly targeted building facades and low-rise buildings,
leaving gaps in understanding its effects on large-span roof structures. This study addresses this by analyzing WDR
impacts on roofs through computational modeling, focusing on rainfall intensity, rise-to-span ratios, and aerodynamic
interactions. The study focuses on the immediate mechanical loading effects of WDR events on intact roof structures.
Firstly, raindrop catch ratio evaluations to quantify WDR distribution across curved roofs. Secondly, pressure
coefficient comparisons between WDR and wind loading under varying geometries and wind angles. Finally,
turbulence intensity assessments on low-sloped roofs using point vortex and Stokes theories. Results demonstrate that
95% of WDR impact was concentrated within 50%-60% of the windward roof surface, diminishing with higher
rainfall intensities. Compared to wind-only conditions, WDR results in significantly altered pressure distributions and
turbulence patterns, with more pronounced effects observed on curved roofs. On the low-sloped roofs, WDR induces
stronger turbulence under equivalent wind angles. These findings demonstrate the spatial non-uniformity of WDR and
its compounded interaction with wind loads, challenging conventional wind-resistant design assumptions. Roof
covering type exerts only a marginal influence on wind-driven-rain characteristics. The study underscores the necessity
of integrating coupled wind-rain simulations into large-span roof engineering to enhance weather resilience. By
bridging gaps between architectural aerodynamics and precipitation dynamics, this work provides a foundational
framework for optimizing roof geometries and improving predictive models against multi-hazard environmental
conditions.
Key Words
large-span space roofs; multi-phase flow simulation; vortex strength; wind-driven rain
Address
Jingbo Zhao:School of Civil Engineering, Xi'an University of Architecture and Technology, Xi
Abstract
The vortex-induced vibration (VIV) is prone to occur in the long-span bridges in operation within the
specific wind speed range, which can lead to the issues of structural durability and driving comfort. To quantitatively
assess driving comfort and limit values of VIV based on comfort criteria, a method for analyzing the driving comfort
of long span bridges under VIV is proposed using Matlab/Simulink modules in this study. Based on the established
method, the VIVs of the Humen Bridge in China and the corresponding traffic control measures are analyzed based
on human comfort levels. Firstly, a four-wheel stochastic road excitation model, an eight-degree-of-freedom vehicle
model, and a nine-degree-of-freedom seated human body model are established, respectively. Secondly, combined
with the established models, the VIV response is converted into wheel excitation and the root mean square (RMS) of
comprehensive weighted acceleration of the human body is obtained. Furthermore, based on the VIV observed on
the Humen Bridge in China, the driving comfort of passengers and limit value of VIV are further studied by the finite
element software LS-DYNA and the established models in this study. The results show that the RMS of the human
body in the car calculated with the proposed method in this study agree well with the results of commercial software
LS-DYNA. Moreover, by reducing vehicle speed, the comfort level of human body during driving can change from
'A Little Uncomfortable' to 'Not Uncomfortable', ensuring the normal operation of the Humen Bridge and
preventing disruptions caused by traffic closures.
Address
Han Xiao:1)State Key Laboratory of Bridge Safety and Resilience, College of Civil Engineering, Hunan Univ, Changsha, Hunan, 410082, China
2)College of Civil Engineering, Hunan Univ., Changsha 410082, China
3)Institute of Steel Structures, Technische Universität Braunschweig, Braunschweig, 38106, Germany
Zhiwen Liu:1)State Key Laboratory of Bridge Safety and Resilience, College of Civil Engineering, Hunan Univ, Changsha, Hunan, 410082, China
2)College of Civil Engineering, Hunan Univ., Changsha 410082, China
Zhijun Jiang:College of Civil Engineering, Hunan Univ., Changsha 410082, China
Zhengqing Chen:1)State Key Laboratory of Bridge Safety and Resilience, College of Civil Engineering, Hunan Univ, Changsha, Hunan, 410082, China
2)College of Civil Engineering, Hunan Univ., Changsha 410082, China
Klaus Thiele:Institute of Steel Structures, Technische Universität Braunschweig, Braunschweig, 38106, Germany
Yabing Xin:Hunan Construction Investment Transportation Construction Co., Ltd, Changsha, Hunan, 410004, China
