基于概率统计理论的泥沙起动流速研究

吴彰松, 张根广, 寇 潭, 高 远, 李林林

raybet体育在线 院报 ›› 2017, Vol. 34 ›› Issue (7) : 7-11.

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raybet体育在线 院报 ›› 2017, Vol. 34 ›› Issue (7) : 7-11. DOI: 10.11988/ckyyb.20160402
江湖泥沙与治理

基于概率统计理论的泥沙起动流速研究

  • 吴彰松1,2, 张根广1, 寇 潭3, 高 远1, 李林林1
作者信息 +

Research on Sediment Incipient Velocity Based on Probability Statistics Theory

  • WU Zhang-song1,2, ZHANG Gen-guang1, KOU Tan3, GAO Yuan1, LI Lin-lin1
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文章历史 +

摘要

为充分考虑泥沙起动的随机性,基于相对暴露度概率密度分布,结合瞬时水流流速及床面泥沙颗粒排列的随机特性,并采用泥沙滚动起动模型,建立了适用于散粒体及黏性细沙统一起动流速公式。通过与实测资料及经典的泥沙起动公式比较发现,本文公式计算值与实测资料吻合更好,验证了该公式在预测散粒体及黏性细沙起动流速的可靠性和优越性。

Abstract

In order to fully reflect the randomness of sediment’s incipient movement, we deduced a formula of incipient velocity suitable for both coarse and fine grains by using a sediment rolling initiation model based on the probability density distribution of dimensionless exposure degree of the grains. The stochastic characteristics of instantaneous flow velocity and sediment particle arrangement on a bed surface were also considered in this paper. Then, the incipient velocities calculated by the proposed formula were compared with measured data and those by several classical incipient velocity formulae. The results show that the incipient velocities calculated by the proposed formula are in more agreement with the measured data than those calculated by the classical formulae. Therefore, the proposed formula’s reliability and superiority in predicting incipient movement of coarse and fine sediment are testified.

关键词

泥沙 / 起动流速 / 暴露度 / 瞬时流速 / 概率统计

Key words

sediment / incipient velocity / exposure degree / instantaneous velocity / probability statistics

引用本文

导出引用
吴彰松, 张根广, 寇 潭, 高 远, 李林林. 基于概率统计理论的泥沙起动流速研究[J]. raybet体育在线 院报. 2017, 34(7): 7-11 https://doi.org/10.11988/ckyyb.20160402
WU Zhang-song, ZHANG Gen-guang, KOU Tan, GAO Yuan, LI Lin-lin. Research on Sediment Incipient Velocity Based on Probability Statistics Theory[J]. Journal of Changjiang River Scientific Research Institute. 2017, 34(7): 7-11 https://doi.org/10.11988/ckyyb.20160402
中图分类号: TV143.4   

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基金

国家自然科学基金项目(51279170)

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