Significance of including lid thickness and particle shape factor in numerical modeling for prediction of particle trap efficiency of invert trap  

作　　者：Salman Beg Deo Raj Kaushal 

机构地区：[1]Department of Civil Engineering,Indian Institute of Technology Delhi,New Delhi 110016,India

出　　处：《Water Science and Engineering》2024年第2期166-176,共11页水科学与水工程（英文版）

摘　　要：Sediment accumulation on the bed of open sewers and drains reduces hydraulic efficiency and can cause localized flooding.Slotted invert traps installed underneath the bed of open sewers and drains can eliminate sediment build-up by catching sediment load.Previous three-dimensional(3D)computational studies have examined the particle trapping performance of invert traps of different shapes and depths under varied sediment and flow conditions,considering particles as spheres.For two-dimensional and 3D numerical modeling,researchers assumed the lid geometry to be a thin line and a plane,respectively.In this 3D numerical study,the particle trapping efficiency of a slotted irregular hexagonal invert trap fitted at the flume bottom was examined by incorporating the particle shape factor of non-spherical sewage solid particles and the thicknesses of upstream and downstream lids over the trap in the discrete phase model of the ANSYS Fluent 2020 R1 software.The volume of fluid(VOF)and the realizable k-turbulence models were used to predict the velocity field.The two-dimensional particle image velocimetry(PIV)was used to measure the velocity field inside the invert trap.The results showed that the thicknesses of upstream and downstream lids affected the velocity field and turbulent kinetic energy at all flow depths.The joint impact of the particle shape factor and lid thickness on the trap efficiency was significant.When both the lid thickness and particle shape factor were considered in the numerical modeling,trap efficiencies were underestimated,with relative errors of-8.66%to-0.65%in comparison to the experimental values of Mohsin and Kaushal(2017).They were also lower than the values predicted by Mohsin and Kaushal(2017),which showed an overall overestimation with errors of-2.3%to 17.4%.

关 键 词：Invert trap Lid thickness Particle image velocimetry Particle shape factor Turbulent kinetic energy Scanning electron microscope 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TV697.1[自动化与计算机技术—控制科学与工程]