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CONTENTS
Volume 38, Number 4, April 2024 (Special Issue)
 

Abstract
Non-synoptic winds, which depart from large-scale synoptic winds, have been observed to play a significant role in causing damage, particularly in specific geographic regions. These non-synoptic winds, such as tornadoes, waterspouts, thunderstorm downbursts, microbursts, and other local wind phenomena, display distinct spatial and temporal characteristics in the wind field, differing from the well-established knowledge of large-scale synoptic winds. The main differences rely on the three-dimensionality, stationarity, uniformity, specific wind profile, and associated statistics. These variations have been observed to result in different aerodynamic loads on structures. As awareness of the impact of non-synoptic winds grows, there has been a growing recognition of the importance of understanding and addressing non-synoptic winds in recent years. This Special Issue is devoted to advancing the understanding of the characteristics of non-synoptic winds and their impacts on various aspects, including structures, communities, vegetation, and ecosystems. Within this special edition, a diverse array of topics related to non-synoptic winds are covered. Shen et al. (2024) reconstructed the wind speed field in mountainous regions by employing Artificial Intelligence technology, i.e., Full Convolutional Neural Network (FCNN). They established a mapping relation between terrain, wind angle, height, and the corresponding velocity fields of three velocity components within a specific terrain range. Zhao et al. (2024) derived the vertical velocity component based on the horizontal velocities extracted from the radar-measured data using mass continuity principles. Subsequently, they investigated the tornadic wind fields by integrating the derived vertical velocity component into the inlet condition of CFD simulations. Xu et al. (2024) analyzed the similarity in the interaction of downburst with wave between a prototype and a scaled model. They proposed a method to mitigate scale effects in experimental simulations of the downburstgenerated wave and validated this approach through numerical simulations. Liu and Hong (2024) analyzed recorded tri-directional thunderstorm wind components by separating them into lower frequency time-varying mean wind speed and high-frequency fluctuating wind components in three orthogonal directions. They evaluated the coherence between each pair of fluctuating winds and developed empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components. Zou et al. (2024) investigated tornadic flow structures and aerodynamic pressures around a high-speed train by employing the improved delated detached eddy simulation. They validated their numerical simulations by comparing them with field observations and wind tunnel data, focusing particularly on aerodynamic loads on the high-speed train at various heights and radial locations. Tao et al. (2024) conducted a probabilistic analysis of gust factors and turbulence intensities of tropical cyclones based on field observations. They established empirical probabilistic models based on this analysis and validated the proposed models by comparing them with measured data. Yao and El Damatty (2024) proposed a simplified procedure to estimate the critical tornado-induced longitudinal force transmitted from the conductor to a tower for transmission line structure. They conducted a parametric study at the critical tornado position to evaluate the effects of different conductor parameters on the longitudinal response.

Key Words


Address
Jin Wang: Western University, Canada
Jinxin Cao: Tongji University, China

Abstract
As wind farms expand into low wind speed areas, an increasing number are being established in mountainous regions. To fully utilize wind energy resources, it is essential to understand the details of mountain flow fields. Reconstructing the wind speed field in complex terrain is crucial for planning, designing, operation of wind farms, which impacts the wind farm's profits throughout its life cycle. Currently, wind speed reconstruction is primarily achieved through physical and machine learning methods. However, physical methods often require significant computational costs. Therefore, we propose a Full Convolutional Neural Network (FCNN)-based reconstruction method for mountain wind velocity fields to evaluate wind resources more accurately and efficiently. This method establishes the mapping relation between terrain, wind angle, height, and corresponding velocity fields of three velocity components within a specific terrain range. Guided by this mapping relation, wind velocity fields of three components at different terrains, wind angles, and heights can be generated. The effectiveness of this method was demonstrated by reconstructing the wind speed field of complex terrain in Beijing.

Key Words
complex mountain; convolution; deconvolution; surrogate model; wind speed fields reconstruction

Address
Ruifang Shen:School of Civil Engineering, Chongqing University, 400045, China

Bo Li:1)School of Civil Engineering, Chongqing University, 400045, China 2)Beijing's Key Laboratory of Structural Wind Engineering and Urban Wind Environment, Beijing 100044, China

Ke Li:1)School of Civil Engineering, Chongqing University, 400045, China 2)Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University),Ministry of Education, Chongqing, 400045, China

Bowen Yan:1)School of Civil Engineering, Chongqing University, 400045, China 2)Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University),Ministry of Education, Chongqing, 400045, China

Yuanzhao Zhang:School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China

Abstract
In a tornadic wind field, the vertical velocity component in certain regions of tornadoes can be significant, forming one of the major differences between tornadic wind fields and synoptic straight-line wind fields. To better understand the wind characteristics of tornadoes and properly estimate the action of tornadoes on civil structures, it is important to ensure that all the attributes of tornadoes are captured. Although Doppler radars have been used to measure tornadic wind fields, they can only directly provide information on quasi-horizontal velocity. Therefore, lots of numerical simulations and experimental tests in previous research ignored the vertical velocity at the boundary. However, the influence of vertical velocity in tornadic wind fields is not evaluated. To address this research gap, this study is to use an approach to derive the vertical velocity component based on the horizontal velocities extracted from the radar-measured data by mass continuity. This approach will be illustrated by using the radar-measured data of Spencer Tornado as an example. The vertical velocity component is included in the initial inflow condition in the CFD simulation to assess the influence of including vertical velocity in the initial inflow condition on the entire tornadic wind field.

Key Words
CFD simulation; radar-measured data; tornado; vertical velocity

Address
Yi Zhao:Department of Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology, Rolla, MO, USA

Guirong Yan:Department of Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology, Rolla, MO, USA

Ruoqiang Feng:The Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing, Jiangsu, China

Zhongdong Duan:School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, China

Houjun Kang:College of Civil Engineering and Architecture, Guangxi University, Nanning, Guangxi, China

Abstract
Before performing an experimental study on the downburst-generated wave, it is necessary to examine the scale effects and corresponding corrections or compensations. Analysis of similarity is conducted to conclude the non-dimensional force ratios that account for the dynamic similarity in the interaction of downburst with wave between the prototype and the scale model, along with the corresponding scale factors. The fractional volume of fluid (VOF) method in association with the impinging jet model is employed to explore the characteristics of the downburst-generated wave numerically, and the validity of the proposed scaling method is verified. The study shows that the location of the maximum radial wind velocity in a downburstwave field is a little higher than that identified in a downburst over the land, which might be attributed to the presence of the wave which changes the roughness of the underlying surface of the downburst. The impinging airflow would generate a concavity in the free surface of the water around the stagnation point of the downburst, with a diameter of about two times the jet diameter (Djet). The maximum wave height appears at the location of 1.5Djet from the stagnation point. Reynolds number has an insignificant influence on the scale effects, in accordance with the numerical investigation of the 30 scale models with the Reynolds number varying from 3.85 x 104 to 7.30 x 109 . The ratio of the inertial force of air to the gravitational force of water, which is denoted by G, is found to be the most significant factor that would affect the interaction of downburst with wave. For the correction or compensation of the scale effects, fitting curves for the measures of the downburst-wave field (e.g., wind profile, significant wave height), along with the corresponding equations, are presented as a function of the parameter G.

Key Words
downburst-generated wave; similarity; fractional volume of fluid method; scale effects; numerical simulation

Address
Xu Haiwei:College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Zheng Tong:College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Chen Yong:College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Lou Wenjuan:College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Shen Guohui:College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Abstract
The recorded thunderstorm winds at a point contain tri-directional components. The probabilistic characteristics of such recorded winds in terms of instantaneous mean wind speed and direction, and the probability distribution and the timefrequency dependent crossed and non-crossed power spectral density functions for the high-frequency fluctuating wind components are unclear. In the present study, we analyze the recorded tri-directional thunderstorm wind components by separating the recorded winds in terms of low-frequency time-varying mean wind speed and high-frequency fluctuating wind components in the alongwind direction and two orthogonal crosswind directions. We determine the time-varying mean wind speed and direction defined by azimuth and elevation angles, and analyze the spectra of high-frequency wind components in three orthogonal directions using continuous wavelet transforms. Additionally, we evaluate the coherence between each pair of fluctuating winds. Based on the analysis results, we develop empirical spectral models and lagged coherence models for the tridirectional fluctuating wind components, and we indicate that the fluctuating wind components can be treated as Gaussian. We show how they can be used to generate time histories of the tri-directional thunderstorm winds.

Key Words
continuous wavelet transform; simulation; thunderstorm winds; time-frequency analysis; time-frequency dependent power spectral density

Address
Y.X. Liu:Department of Civil and Environmental Engineering, University of Western Ontario, 1151 Richmond Street, London, N6A 5B9, Canada

H.P. Hong:Department of Civil and Environmental Engineering, University of Western Ontario, 1151 Richmond Street, London, N6A 5B9, Canada

Abstract
The funnel-shaped vortex structure of tornadoes results in a spatiotemporally varying wind velocity (speed and direction) field. However, very limited full-scale tornado data along the height and radius positions are available to identify and reliably establish a description of complex vortex structure together with the resulting aerodynamic effects on the high-speed train (HST). In this study, the improved delayed detached eddy simulation (IDDES) for flow structures and aerodynamic pressures around an HST under tornado-like winds are conducted to provide high-fidelity computational fluid dynamics (CFD) results. To demonstrate the accuracy of the numerical method adopted in this study, both field observations and wind-tunnel data are utilized to respectively validate the simulated tornado flow fields and HST aerodynamics. Then, the flow structures and aerodynamic pressures (as well as aerodynamic forces and moments) around the HST at various locations within the tornadolike vortex are comprehensively compared to highlight the importance of considering the complex spatiotemporal wind features in the HST-tornado interactions.

Key Words
aerodynamic pressure; computational fluid dynamics; flow structure; high-speed train; tornado

Address
Simin Zou:1)School of Civil Engineering, Central South University, Changsha, Hunan 410075, China
2)Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY 14260, USA

Xuhui He:1)School of Civil Engineering, Central South University, Changsha, Hunan 410075, China 2)National Engineering Laboratory for High-Speed Railway Construction, Changsha, Hunan 410075, China

Teng Wu:National Engineering Laboratory for High-Speed Railway Construction, Changsha, Hunan 410075, China

Abstract
The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cablestayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

Key Words
field measurement; gust factor; probabilistic analysis; tropical cyclone; turbulence intensity

Address
Tianyou Tao:1)Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China
2)School of Civil Engineering, Southeast University, Nanjing 211189, China

Zao Jin:School of Civil Engineering, Southeast University, Nanjing 211189, China

Hao Wang:1)Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China
2)School of Civil Engineering, Southeast University, Nanjing 211189, China

Abstract
The longitudinal force resulting from tornado loads on transmission line is considered a crucial factor contributing to the failure of transmission line structures during tornado events. Accurate estimation of this longitudinal force poses a challenge for structural designers. Therefore, the objective of this paper is to provide a set of charts that can be easily used to estimate the peak longitudinal forces transferred from the conductors to a tower. The critical wind field and corresponding configuration considered in this paper are previously studied and determined. The charts should account for all the conductor parameters that can affect the value of the longitudinal force. In order to achieve that, a parametric study is first conducted to assess the variation of the longitudinal forces with different conductor parameters, based on the critical tornado configuration. Results of this parametric study are used to develop the charts that can be used to calculate longitudinal forces by adopting a multi-variable line regression. The forces calculated from charts are validated by finite element analysis. An example for the usage of the charts is provided at the end of this paper.

Key Words
conductor; longitudinal force; tornado; transmission line system

Address
Dingyu Yao:Department of Civil and Environmental Engineering, Western University, London, ON, Canada

Ashraf El Damatty:1)Department of Civil and Environmental Engineering, Western University, London, ON, Canada
2)WindEEE Research Institute, Western University, London, ON, Canada

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