• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Numerical and experimental analysis of shallow turbulent flow over complex roughness beds

Zhang, Y., Rubinato, M., Kazemi, E., Pu, Jaan H., Huang, Y., Lin, P. 24 July 2019 (has links)
Yes / A set of shallow-water equations (SWEs) based on a k-epsilon Reynold stress model is established to simulate the turbulent flows over a complex roughness bed. The fundamental equations are discretized by the second-order finite-difference method (FDM), in which spatial and temporal discretization are conducted by staggered-grid and leap-frog schemes, respectively. The turbulent model in this study stems from the standard k-epsilon model, but is enhanced by replacing the conventional vertical production with a more rigorous and precise generation derived from the energy spectrum and turbulence scales. To verify its effectiveness, the model is applied to compute the turbulence in complex flow surroundings (including a rough bed) in an abrupt bend and in a natural waterway. The comparison of the model results against experimental data and other numerical results shows the robustness and accuracy of the present model in describing hydrodynamic characteristics, especially turbulence features on the complex roughness bottom. / National Key Research and Development Program of China (Grant No: 2016YFE0122500, 2013CB036401 and 2013CB036402), China Postdoctoral Science Foundation (Grant No: 2016M591184) and Programme of Introducing Talents of Discipline to Universities (Grant No: BC2018038) / Research Development Fund Publication Prize Award winner, June 2019.

Page generated in 0.0594 seconds