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Wind tunnel tests and CFD simulations for snow redistribution on 3D stepped flat roofs

  • Yu, Zhixiang (School of Civil Engineering, Southwest Jiaotong University) ;
  • Zhu, Fu (School of Civil Engineering, Southwest Jiaotong University) ;
  • Cao, Ruizhou (School of Civil Engineering, Southwest Jiaotong University) ;
  • Chen, Xiaoxiao (School of Civil Engineering, Southwest Jiaotong University) ;
  • Zhao, Lei (School of Civil Engineering, Southwest Jiaotong University) ;
  • Zhao, Shichun (School of Civil Engineering, Southwest Jiaotong University)
  • Received : 2018.01.30
  • Accepted : 2018.12.29
  • Published : 2019.01.25

Abstract

The accurate prediction of snow distributions under the wind action on roofs plays an important role in designing structures in civil engineering in regions with heavy snowfall. Affected by some factors such as building shapes, sizes and layouts, the snow drifting on roofs shows more three-dimensional characteristics. Thus, the research on three-dimensional snow distribution is needed. Firstly, four groups of stepped flat roofs are designed, of which the width-height ratio is 3, 4, 5 and 6. Silica sand with average radius of 0.1 mm is used to model the snow particles and then the wind tunnel test of snow drifting on stepped flat roofs is carried out. 3D scanning is used to obtain the snow distribution after the test is finished and the mean mass transport rate is calculated. Next, the wind velocity and duration is determined for numerical simulations based on similarity criteria. The adaptive-mesh method based on radial basis function (RBF) interpolation is used to simulate the dynamic change of snow phase boundary on lower roofs and then a time-marching analysis of steady snow drifting is conducted. The overall trend of numerical results are generally consistent with the wind tunnel tests and field measurements, which validate the accuracy of the numerical simulation. The combination between the wind tunnel test and CFD simulation for three-dimensional typical roofs can provide certain reference to the prediction of the distribution of snow loads on typical roofs.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

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