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CONTENTS
Volume 37, Number 4, October 2023
 


Abstract
The aim of this paper is to enhance the accuracy of predicting time-averaged external surface pressures on low-rise buildings by utilizing Computational Fluid Dynamics (CFD) simulations. To achieve this, benchmark studies of the Silsoe cube and the Texas Tech University (TTU) experimental building are employed for comparison with simulation results. The paper is structured into three main sections. In the initial part, an appropriate domain size is selected based on the precision of mean pressure coefficients on the windward face of the cube, utilizing Reynolds Averaged Navier-Stokes (RANS) turbulence models. Subsequently, recommendations regarding the optimal computational domain size for an isolated building are provided based on revised findings. Moving on to the second part, the Silsoe cube model is examined within a horizontally homogeneous computational domain using more accurate turbulence models, such as Large Eddy Simulation (LES) and hybrid RANS-LES models. For computational efficiency, transient simulation settings are employed, building upon previous studies by the authors at the Windstorm Impact, Science, and Engineering (WISE) Lab, Louisiana State University (LSU). An optimal meshing strategy is determined for LES based on a grid convergence study. Three hybrid RANS-LES cases are investigated to achieve desired enhancements in the distribution of mean pressure coefficients on the Silsoe cube. In the final part, a 1:10 scale model of the TTU building is studied, incorporating the insights gained from the second part. The generated flow characteristics, including vertical profiles of mean velocity, turbulence intensity, and velocity spectra (small and large eddies), exhibit good agreement with full-scale (TTU) measurements. The results indicate promising roof pressures achieved through the careful consideration of meshing strategy, time step, domain size, inflow turbulence, near-wall treatment, and turbulence models. Moreover, this paper demonstrates an improvement in mean roof pressures compared to other state-of-the-art studies, thus highlighting the significance of CFD simulations in building aerodynamics.

Key Words
aerodynamics; bluff body; computational domain; Computational Fluid Dynamics (CFD); turbulence; wind loads

Address
Md Faiaz Khaled and Aly Mousaad Aly:Windstorm Impact, Science and Engineering (WISE) Research Lab, Department of Civil and Environmental Engineering, Louisiana State
University, 3230 H Patrick Taylor Hall, Baton Rouge, LA 70803, USA

Abstract
Subgrade differential settlement of high-speed railways was a pivotal issue that could increase the risk of trains operation. The risk will be further increased when trains in the subsidence zone are affected by crosswinds. In this paper, the computational fluid dynamics (CFD) model and finite element (FE) model were established, and the data transmission interface of the two models was established by fluid-solid interaction (FSI) method to form a systematic crosswind-train-track-subgrade dynamic model. The risk of high-speed train encountering crosswind in settlement area was analyzed. The results showed that the aerodynamic force of the trains increased significantly with the increase in crosswind speed. The aerodynamic force of the trains could reach 125.14 kN, significantly increasing the risk of derailment and overturning. Considering the influence of crosswind, the risk of train operation could be greatly increased. The safety indices and the wheel-rail force both increased with the increase of the wind speed. For the high-speed train running at 350 km/h, the warning value of wind speed was 10.2 m /s under the condition of subgrade settlement with wavelength of 20 m and amplitude of 15 mm.

Key Words
CFD-FE coupling; cosswind; high-speed trains; risk analysis; subgrade settlement

Address
Qian Zhang, Xiaopei Cai, Tao Wang, Yanrong Zhang:School of Civil Engineering, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District Beijing, China

Shusheng Yang:Jinan-Qingdao High-speed Railway Co., Ltd.,
Room 1011, Floor 1, Building 2, High-speed Railway City, 3799 Tangye East Road Jinan, China


Abstract
Insulating glass units (IGUs) have been widely used in buildings in recent years due to their superior thermal insulation performance. However, because of the panel reciprocating motion and fatigue deterioration of sealants under longterm wind loads, many IGUs have the problem of early failure of watertight properties in real usage. This study aimed to propose a statistical method for wind-induced deflection of IGU panels during the whole life service period, for further precise analysis of the accumulated fatigue damage at the sealed part of the edge bond. By the estimation of the wind occurrence regularity based on wind pressure return period, the events of each wind speed interval during the whole life were obtained for the IGUs at 50m height in Beijing, which are in good agreement with the measured data. Also, the wind-induced deflection analysis method of IGUs based on the formula of airspace coefficient was proposed and verified as an improvement of the original stiffness distribution method with the average relative error compared to the test being about 3% or less. Combining the two methods above, the deformation of the outer and inner panes under wind loads during 30 years was precisely calculated, and the deflection and stress state at selected locations were obtained finally. The results show that the compression displacement at the secondary sealant under the maximum wind pressure is close to 0.3 mm (strain 2.5%), and the IGUs are in tens of thousands of times the low amplitude tensile-compression cycle and several times to dozens of times the relatively high amplitude tensilecompression cycle environment. The approach proposed in this paper provides a basis for subsequent studies on the durability of IGUs and the wind-resistant behaviors of curtain wall structures.

Key Words
airspace coefficient; insulating glass units; load sharing ratio; wind-induced deflection; wind load statistics

Address
Zhiyuan Wang:1)China Academy of Building Research, Beijing 100013, China
2)Department of Civil Engineering, Tongji University, Shanghai 200092, China

Junjin Liu and Jianhui Li:China Academy of Building Research, Beijing 100013, China

Suwen Chen:Department of Civil Engineering, Tongji University, Shanghai 200092, China


Abstract
In this study, two steady RANS turbulence models (SST k–ω and Realizable k–ε) and four unsteady turbulence models (URANS SST k–ω and Realizable k–ε, SST–SAS, and SST–IDDES) are evaluated with respect to their capacity to predict crosswind characteristics on high-speed trains (HSTs). All of the numerical simulations are compared with the wind tunnel values and LES results to ensure the accuracy of each turbulence model. Specifically, the surface pressure distributions, time-averaged aerodynamic coefficients, flow fields, and computational cost are studied to determine the suitability of different models. Results suggest that the predictions of the pressure distributions and aerodynamic forces obtained from the steady and transient RANS models are almost the same. In particular, both SAS and IDDES exhibits similar predictions with wind tunnel test and LES, therefore, the SAS model is considered an attractive alternative for IDDES or LES in the crosswind study of trains. In addition, if the computational cost needs to be significantly reduced, the RANS SST k–ω model is shown to provide relatively reasonable results for the surface pressures and aerodynamic forces. As a result, the RANS SST k–ω model might be the most appropriate option for the expensive aerodynamic optimizations of trains using machine learning (ML) techniques because it balances solution accuracy and resource consumption.

Key Words
crosswind; high-speed train; IDDES; RANS; SAS; URANS

Address
Xiao-Shuai Huo, Tang-Hong Liu,Hong-Rui Gao and Bin Xu:Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic & Transportation Engineering, Central South University,
Changsha 410075, PR China

Zheng-Wei Chen:Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, PR China

Wen-Hui Li:School of Rail Transportation, Soochow University, Suzhou, Jiangsu 215131, PR China

Abstract
We investigated the wind characteristics in the near-surface layer during the landfall of Typhoon Mujigae (2015) based on observations from wind towers in the coastal areas of Guandong province. Typhoon Mujigae made landfall in this region from 01:00 UTC to 10:00 UTC on October 4, 2015. In the region influenced by the eyewall of the tropical cyclone, the horizontal wind speed was characterized by a double peak, the wind direction changed by 〉180°, the vertical wind speed increased by three to four times, and the angle of attack increased significantly to a maximum of 7°, exceeding the recommended values in current design criteria. The vertical wind profile may not conform to a power law distribution in the near-surface layer in the region impacted by the eyewall and spiral rainband. The gust factors were relatively dispersed when the horizontal wind speed was small and tended to a smaller value and became more stable with an increase in the horizontal wind speed. The variation in the gust factors was the combined result of the height, wind direction, and circulation systems of the tropical cyclone. The turbulence intensity and the downwind turbulence energy spectrum both increased notably in the eyewall and spiral rainband and no longer satisfied the assumption of isotropy in the inertial subrange and the −5/3 law. This result was more significant in the eyewall area than in the spiral rainband. These results provide a reference for forecasting tropical cyclones, wind-resistant design, and hazard prevention in coastal areas of China to reduce the damage caused by high winds induced by tropical cyclones.

Key Words


Address
Lin Xue:School of Finance, Yunnan University of Finance and Economics, Kunming 650221, China

Ying Li:State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China

Lili Song:Chinese Academy of Meteorological Sciences, Beijing 100081, China


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