文献类型：期刊文献

英文题名：Mean velocity and suspended sediment concentration profile model of turbulent shear flow with probability density function

作者：Wu, Guanglin[1,2];Zhu, Liangsheng[1];Li, Fangcheng[2]

机构：[1]South China Univ Technol, Coll Civil & Transportat Engn, Guangzhou 510641, Guangdong, Peoples R China;[2]Guangdong Ocean Univ, Coll Ocean Engn, Zhanjiang 524088, Peoples R China

年份：2017

卷号：21

期号：3

起止页码：129

外文期刊名：EARTH SCIENCES RESEARCH JOURNAL

收录：SCI-EXPANDED(收录号：WOS:000430311700004)、、WOS

基金：This work was partially supported by the Guangdong Province Science and Technology Research Project (2010B030600007) and Projects of Enhancing School with Innovation of Guangdong Ocean University (GDOU2016050258 & GDOU2017052503).

语种：英文

外文关键词：Exponential probability density; Mean velocity profile; Concentration profile; River flow; Coastal current

外文摘要：This work purposes a general mean velocity and a suspended sediment concentration (SSC) model to express distribution in every point of the cross section of turbulent shear flow by using a probability density function method. In order to solve turbulent flow and avoid multifarious dynamical mechanics, the probability density function method was used to describe the velocity and concentration profiles interacted on directly by fluid particles in turbulent shear flow. The velocity profile model was obtained by solving for the profile integral with the product of the laminar velocity and probability density, through adopting an exponential probability density function to express probability distribution of velocity alteration of a fluid particle in turbulent shear flow. An SSC profile model was also created following a method similar to the above and based on the Schmidt diffusion equation. Different velocity and SSC profiles were created while changing the parameters of the models. The models were verified by comparing the calculated results with traditional models. It was shown that the probability density function model was superior to log-law in predicting stream-wise velocity profiles in coastal currents; and the probability density function SSC profile model was superior to the Rouse equation for predicting average SSC profiles in rivers and estuaries. Outlooks for precision investigation are stated at the end of this article.