Assessment of advanced RANS models ability to predict a turbulent swept liquid metal flow over a wire in a channel

Byung Hyun You, Yong Hoon Jeong, Yacine Addad

    Research output: Contribution to journalArticlepeer-review

    5 Scopus citations

    Abstract

    This paper presents the assessment of different Reynolds-averaged Navier-Stokes (RANS) based turbulence models against the direct numerical simulation (DNS) reference data of turbulent swept flow over a wire in a channel which is topologically equivalent to a wire-wrapped sub-channel assembly in the liquid metal reactor. Computational grids were generated to archive the low y+ wall treatment approach condition. All the candidate turbulence models were compared to the DNS results both qualitatively and quantitatively under three different crossflow conditions. RANS based CFD results were compared to time-averaged DNS results regarding the flow structure, turbulent kinetic energy, and wall shear stress at each particular location defined by a flow structure along the cross-flow direction. Computation times were measured between each model with appropriate solution convergence strategy. In terms of the flow structure, two-equation and four-equation models were found to over-predict the size of the primary recirculation bubble. The seven-equation model is also over-predicting the recirculation zone as a result of the inclusion of SSG formulations for the pressure-strain term, but this model is clearly outperforming the other models' predictions in terms of local velocity profiles, turbulent kinetic energy distributions, and the shear stress alignments within reasonable computation time.

    Original languageBritish English
    Article number110206
    JournalNuclear Engineering and Design
    Volume353
    DOIs
    StatePublished - Nov 2019

    Keywords

    • Core thermal-hydraulics
    • k-Epsilon
    • k-Omega SST
    • RANS simulation
    • Reynolds stress transport
    • Wire-wrapped fuel pin

    Fingerprint

    Dive into the research topics of 'Assessment of advanced RANS models ability to predict a turbulent swept liquid metal flow over a wire in a channel'. Together they form a unique fingerprint.

    Cite this