风雪绕流数值模拟的积雪预测模型研究

刘多特, 李永乐, 汪斌

刘多特, 李永乐, 汪斌. 风雪绕流数值模拟的积雪预测模型研究[J]. 工程力学, 2016, 33(8): 122-131. DOI: 10.6052/j.issn.1000-4750.2015.01.0019
引用本文: 刘多特, 李永乐, 汪斌. 风雪绕流数值模拟的积雪预测模型研究[J]. 工程力学, 2016, 33(8): 122-131. DOI: 10.6052/j.issn.1000-4750.2015.01.0019
LIU Duo-te, LI Yong-le, WANG Bin. A NUMERICAL PREDICTION MODEL FOR SNOW ACCUMULATION CAUSED BY AMBIENT SNOWDRIFT[J]. Engineering Mechanics, 2016, 33(8): 122-131. DOI: 10.6052/j.issn.1000-4750.2015.01.0019
Citation: LIU Duo-te, LI Yong-le, WANG Bin. A NUMERICAL PREDICTION MODEL FOR SNOW ACCUMULATION CAUSED BY AMBIENT SNOWDRIFT[J]. Engineering Mechanics, 2016, 33(8): 122-131. DOI: 10.6052/j.issn.1000-4750.2015.01.0019

风雪绕流数值模拟的积雪预测模型研究

基金项目: 国家自然科学基金项目(U1334201);四川省青年科技创新研究团队项目(15CXTD0005)
详细信息
    作者简介:

    刘多特(1984-),男,四川人,博士生,主要从事大跨度桥梁风致振动研究(E-mail:liuduote@my.swjtu.edu.cn);汪斌(1983-),男,湖南人,讲师,博士,主要从事大跨度桥梁风致振动及风车桥耦合振动研究(E-mail:wangbinwvb@swjtu.edu.cn).

    通讯作者:

    李永乐(1972-),男,河南人,教授,博士,博导,主要从事大跨度桥梁风致振动及风车桥耦合振动研究(E-mail:lele@swjtu.edu.cn).

  • 中图分类号: TU312.1

A NUMERICAL PREDICTION MODEL FOR SNOW ACCUMULATION CAUSED BY AMBIENT SNOWDRIFT

More Information
    Corresponding author:

    LI Yong-le: 10.6052/j.issn.1000-4750.2015.01.0019

  • 摘要: 为研究钝体风雪绕流效应下的地表积雪现象,根据壁面剪切机制及空间混合理论共同确立了积雪预测模型,采用欧拉框架单流体方法对1 m高度立方体模型周边的风雪两相流动情况及空间雪相浓度进行了求解。通过对比不同积雪模型下沉积预测指标在绕流区域的分布情况,及以此得到的积雪预测形态与实测结果的差异发现:该文采用的积雪模型不完全依赖于当地摩阻风速与临界起动风速的相对关系,一定程度上避免了模型参数的取值局限,对沉积现象的反映更为直观;由于综合了两套理论并引入沉积量估计的双重动态指标,该文对于雪面侵蚀及沉积区域的界定划分较为清晰,对积雪形态的预测包括雪面极值位置的捕捉、坡面起伏规律的再现,都较已有数值计算结果更为合理。模型方法可用于其他外形地物绕流下的地表积雪现象模拟。
    Abstract: This paper presents a numerical investigation on snow accumulation caused by ambient snowdrift. According to the wall shear mechanism and spatial mixture theory, a numerical prediction model for snow accumulation has been developed, and the results obtained from the prediction model are compared with the measured results. The comparison indicates that the prediction model adopted in this paper can reflect the deposition phenomenon more directly and expand the value range of the model parameter. Due to the adoption of double dynamic model indicators, the prediction results are more reasonable than the results obtained by the other numerical methods. The prediction model adopted in this paper can be used to simulate the snow accumulation around other ground objects with different shapes.
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出版历程
  • 收稿日期:  2015-01-06
  • 修回日期:  2015-07-29
  • 刊出日期:  2016-08-24

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