Liquid metals (such as sodium Na, lead Pb, lead-bismuth eutectic) are widely used for heat removal from fast breeding nuclear reactors cores [1]. Liquid metals tend to conduct heat more rapidly than momentum via molecular diffusion compared to non-metallic liquids as they have higher thermal diffusivity, higher thermal conductivity, and low heat capacity. This results in a large scale-gap in momentum and thermal turbulent diffusion and dissipation and poses turbulence modeling challenges for computational fluid dynamics simulations. In a previous study, Bhushan et al. [2,3] assessed the predictive capability of RANS, hybrid RANS-LES (PANS model) and LES turbulence models for plane and vertical channel flows at Re =150 and 640 for Pr = 0.025 and 0.71, and for vertical backward facing step flow for Pr = 8.8×10 at Ri = 0 and 0.338. The channel flow simulation revealed that buoyancy plays a major role in altering the mean flow gradients, which in turn influences turbulence production. Buoyancy depends on the mean temperature distribution, and since low-Pr flows result in higher temperature gradients away from the wall, the buoyancy effects are enhanced for these cases. RANS models perform reasonably well for flows without buoyancy, but for flows involving buoyancy they significantly under predict the turbulent temperature diffusion from the aiding to the opposing flow side. The PANS model shows an improvement in the turbulence predictions but shows limitations similar to those of RANS. Among the LES models, the WALE model performs the best, and is the only model that predicts the sharp temperature gradients towards the mid-channel for the buoyancy driven flows due to improved turbulence predictions. For the backward facing step simulations, all the models perform very well for Ri = 0.338, as the flow is primarily dominated by the buoyant forces. However, they showed some differences for the Ri = 0 case. For the latter, both PANS and LES outperformed RANS models. Nonetheless, RANS results were found to be encouraging considering low computational cost and reasonable accuracy. In this study, the RANS, PANS and LES turbulence models will be applied for turbulent heat transfer in a bare rod bundle with low pitch–to-diameter ratio at Re= 22600, and Pr = 0.02 and0.002, and the predictions will be validated against published DNS data [4]. The study will also synthesize the results from all the three cases to provide assessment of the advantages and limitations of the different classes of turbulence model.&nbsp;[1] Murray, RL. Nuclear Energy: an Introduction to the Concepts, Systems, and Applications ofNuclear Processes. (Butterworth-Heinemann, 2009).[2] Bhushan, S., ElFajri, O., Jock, W.D., Walters, D.K., Lai, J.K., Hassan, Y.A., Jackson, R.B.,Obabko, A., &amp; Merzari, E., 2018. Assessment of RANS, LES, and Hybrid RANS/LES Models for thePrediction of Low-Pr Turbulent Flows. Proceedings of the ASME 2018 5th Joint US-European FluidsEngineering Summer Conference FEDSM2018, July 15-20, Montreal, Quebec, Canada.[3] Bhushan, S., Elmellouki, M., Jock, W. D., Walters, D. K., Lai, J. K., Hassan, Y. A., Obabko, A.,and Merzari, E. "Numerical Investigation of Flow and Heat Transfer Characteristics for Attachedand Separated Low-Pr Flows." Proceedings of the ASME-JSME-KSME 2019 8th Joint FluidsEngineering Conference. Volume 2: Computational Fluid Dynamics. San Francisco, California, USA.July 28–August 1, 2019. V002T02A054. ASME[4] Lai, J. K., Busco, G., Merzari, E., &amp; Hassan, Y. A. (2019). Direct Numerical Simulation of theFlow in a Bare Rod Bundle at Different Prandtl Numbers. Journal of Heat Transfer, 141(12). τ-3h

Assessment of Low and High-Fidelity Turbulence Models for Liquid Metal Flow Predictions

Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2021/volume/85543

ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021)

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