Modeling snowdrift on roofs using Immersed Boundary Method and wind tunnel test

Wang, Jianshuo; Liu, Hongbo; Xu, Dong; Chen, Zhihua; Ma, Kejian

doi:10.1016/j.buildenv.2019.106208

Cited by 23 publications

(6 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the uninhabited railroad line during the snowfall period and the lack of meteorological information, it is difficult to conduct a study on the snow damage prevention and control for the Altay-Zhundong Railway. Based on the erosion-accumulation model (Wang et al, 2019) and the multi-phase turbulent flow theory (Cheng et al, 2016;Zhang et al, 2021), in this study, we used global atmospheric reanalysis (ERA5, where ERA5 is the fifth generation ECMWF (The European Center for Medium-Range Weather Forecasts) atmospheric reanalysis of the global climate covering the period from January 1950 to present) climate data to validate and parameterize the wind speed, wind frequency, snow density, snow thickness, and other data acquired from field surveys, thereby supporting laboratory simulation tests. On this basis, we analyzed the collaborative prevention and control effect of snow fences and subgrade along the Altay-Zhundong Railway from the perspectives of porosity, fence height, and arrangement distance and designed orthogonal tests to explore the sensitivity of each factor to different areas and related prevention and control effects.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences

Lei,

Cheng,

Gao

et al. 2023

J. Arid Land

View full text Add to dashboard Cite

Railways built in cold, snowy, and lightly populated areas are subjected to wind and snow disasters. In this study, we selected a snow hazard prevention and control section of the Altay-Zhundong Railway in Xinjiang Uygur Autonomous Region of China as the research object. We investigated the deposited snowfall variation characteristics on the two sides and in the embankment pavement area of snow fences with different porosities, fence heights, and arrangement distances using single-factor tests and orthogonal tests based on global atmospheric reanalysis climate data, field survey data, and a multi-phase flow analysis model. The results showed significant differences in the characteristics of snow cover distribution and snow cover thickness between the embankment and the cutting in the absence of snow protection measures. The maximum snow cover thickness of the embankment pavement decreased by 12.6% relative to the cutting pavement. The snow cover thickness of the embankment exhibited an increasing trend from windward shoulder to leeward shoulder, whereas the snow cover thickness of the cutting presented a declining trend from windward shoulder to leeward toe. In the collaborative prevention and control of snow fences and embankments, the three factors can be ranked in terms of their sensitivity to deposited snowfall within the influence scope of snow fences as follows: fence height>arrangement distance>porosity. At the same time, fence height yielded a significant relationship for the influence scope of snow fences (P<0.05). The three factors can also be ranked in terms of their sensitivity to deposited snowfall on the pavement as follows: porosity>fence height>arrangement distance. For the embankment protection of the Altay-Zhundong Railway against wind and snow, snow fence with a porosity of 75%, a fence height of 4.8 m, and an arrangement distance from the embankment of 60 m produced the best snow control effect. By revealing the characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences, this study provides valuable references for the engineering applications of railway construction in areas prone to wind and snow disasters.

show abstract

Section: Introductionmentioning

confidence: 99%

Characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences

Lei,

Cheng,

Gao

et al. 2023

J. Arid Land

View full text Add to dashboard Cite

show abstract

“…For snowdrift related to buildings, the Steady-RANS CFD simulation based on the Eulerian approach was proven to provide sufficiently accurate results with a low computational cost (Uematsu et al, 1991;Tominaga et al, 2011b;Tominaga et al, 2011a;Zhou et al, 2016a;Zhu et al, 2017;Wang et al, 2019;Zhou et al, 2020), which ensures that relevant disaster prediction can be carried out in the shortest possible time. However, snow drifting will generally last hours or even days; during this, meteorological conditions and snow distribution may have significant changes.…”

Section: Introductionmentioning

confidence: 99%

“…Zhou et al (2016a) developed this method to predict the snow distribution on a roof, in which a multistage numerical model is proposed to consider the feedback of the snow distribution to the airflow. Related methods have been expanded in Zhu et al (2017) and Wang et al (2019): the former aims to introduce the RBF-based dynamic mesh method into the roof snow distribution, and the latter uses the immersion boundary method to obtain a more robust simulation process. However, the previous research studies are more inclined to use commercial CFD software (e.g., Ansys Fluent), which is unfavorable for researchers who want to reproduce or improve this method.…”

Section: Introductionmentioning

confidence: 99%

DriftScalarDyFoam: An OpenFOAM-Based Multistage Solver for Drifting Snow and Its Distribution Around Buildings

Chen

2022

Front. Earth Sci.

View full text Add to dashboard Cite

There is a complex coupling relationship between the airflow and snow cover. In a period of hours or even days, the airflow will cause the redistribution of snow, and the redistribution of snow will cause the airflow to change. This study develops a dynamic mesh technology applied in snow drifting simulation through a real-time dynamic mesh update to depict the snow surface evolution process under long-period snow drifting, and a solver application named driftScalarDyFoam based on OpenFOAM is implemented. This solver divides the long-period snow drifting process into several stages, in each of which a snow transport equation is applied to predict the spatial distribution of snow, and finally, the snow surface evolves according to the erosion–deposition model. This method that we have proposed has been validated for several measured cases, including snow distribution on a flat roof and snow distribution around a building.

show abstract

“…Thiis and O'Rourke [18] analyzed the influence of roof slope on the snow depth coefficient based on the observation database in Norway for many years and obtained some relevant empirical formulas. Furthermore, research methods, such as theoretical analysis [19,20], wind or water tunnel experiments [21][22][23], and numerical simulations [22,24,25], are also widely adopted to investigate snow distribution on the roofs of buildings. From the existing research literature, the attention of wind load research is mainly focused on roofs without snowdrifts.…”

Section: Introductionmentioning

confidence: 99%

LES Analysis of the Effect of Snowdrift on Wind Pressure on a Low-Rise Building

Liu

Chen

et al. 2022

Buildings

View full text Add to dashboard Cite

This paper presents a comparative study of the distribution of wind pressure acting on a low-rise building roof with or without snowdrift through the Large-Eddy simulation (LES) method. Firstly, based on previous wind-blowing snow experiments, the stable snowdrift models were obtained by reverse technique. Secondly, the methodology of LES numerical simulation was introduced, where sensitivity analyses were conducted to determine a more reasonable grid configuration and data sampling time. Meanwhile, the numerical validation was also verified by comparing it with the previous PIV database. Finally, the wind pressure acting on the building’s roof with or without snowdrift were systematically compared and analyzed. It was found that the snow cover significantly restrains the size of the separation bubble and makes is lcoated earlier on the roof, which leads to the increasing passing velocity in the region near the roof. Meanwhile, the area-averaged pressure coefficient in the windward region (x/H < 0.5) for the snowdrift roof will be significantly amplified, especially for the fluctuating pressure, the maximum value of the Relative Difference even reaches 40%. Additionally, according to the POD analysis, the snowdrift causes the fluctuating wind energy to concentrate near the windward side of the roof. Therefore, more attention should be paid to the wind pressure in the windward region when the snowdrift is formed on the roof.

show abstract

Modeling snowdrift on roofs using Immersed Boundary Method and wind tunnel test

Cited by 23 publications

References 46 publications

Characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences

Characteristics of snow cover distribution along railway subgrade and the protective effect of snow fences

DriftScalarDyFoam: An OpenFOAM-Based Multistage Solver for Drifting Snow and Its Distribution Around Buildings

LES Analysis of the Effect of Snowdrift on Wind Pressure on a Low-Rise Building

Contact Info

Product

Resources

About