CFD-DEM predictions of heat transfer in packed beds using commercial and open source codes

Arpit Singhal, Schalk Cloete, Stefan Radl, Rosa Quinta Ferreira, Shahriar Amini

Research output: Contribution to journalArticle

Abstract

Gas-particle heat transfer rates are investigated using particle-resolved direct numerical simulation (PR-DNS). We utilize a discrete element method (DEM) approach to first obtain a realistic packing of the particles, and then build a computational mesh based on these particle positions for running PR-DNS. A common challenge in such investigations is the overlap between particles, which can result in highly skewed cells. In this work, this problem is dealt with by shrinking the particles. Simulation results showed that changing the packing porosity by shrinking the particles by different amounts does not match recently proposed correlations. Particle arrangements produced in this way will over predict the heat transfer rate. When a random particle arrangement was simulated, however, results matched well with correlations. In addition, we find that DNS results using the commercial CFD code ANSYS FLUENT and the open-source code OpenFOAM® return very similar results. The computational performance was similar, with (i) OpenFOAM being faster for a fixed number of iterations, and (ii) ANSYS FLUENT requiring a smaller number of iterations to find convergence.
Original languageEnglish
Pages (from-to)1-17
JournalMAYFEB Journal of Chemical Engineering
Volume1
Issue number1
DOIs
Publication statusPublished - 12 Sep 2016

Keywords

  • direct numerical simulation
  • heat and mass transfer

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes

Fields of Expertise

  • Information, Communication & Computing

Fingerprint Dive into the research topics of 'CFD-DEM predictions of heat transfer in packed beds using commercial and open source codes'. Together they form a unique fingerprint.

Cite this