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A comparative study of manhole hydraulics using stereoscopic PIV and different RANS models

  • Md Nazmul Azim Beg*
  • , Rita F. Carvalho
  • , Simon Tait
  • , Werner Brevis
  • , Matteo Rubinato
  • , Alma Schellart
  • , Jorge Leandro
  • *Corresponding author for this work
  • University of Sheffield
  • University of Coimbra
  • Pontifical Catholic University of Chile
  • Technische Universität München

Research output: Contribution to journalArticlepeer-review

Abstract

Flows in manholes are complex and may include swirling and recirculation flow with significant turbulence and vorticity. However, how these complex 3D flow patterns could generate different energy losses and so affect flow quantity in the wider sewer network is unknown. In this work, 2D3C stereo Particle Image Velocimetry measurements are made in a surcharged scaled circular manhole. A computational fluid dynamics (CFD) model in OpenFOAM® with four different Reynolds Averaged Navier Stokes (RANS) turbulence model is constructed using a volume of fluid model, to represent flows in this manhole. Velocity profiles and pressure distributions from the models are compared with the experimental data in view of finding the best modelling approach. It was found among four different RANS models that the re-normalization group (RNG) k-ɛ and k-ω shear stress transport (SST) gave a better approximation for velocity and pressure.
Original languageEnglish
Pages (from-to)87-98
JournalWater Science and Technology
Volume2017
Issue number1
Early online date28 Feb 2018
DOIs
Publication statusPublished - 26 Apr 2018

Funding

The work presented is part of the QUICS (Quantifying Uncertainty in Integrated Catchment Studies) project. This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 607000. The laboratory facility was made possible through EPSRC, project EP/K040405/1. All the numerical results here showed were performed on the Centaurus Cluster of the Laboratory for Advanced Computing of University of Coimbra, Portugal.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

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