A global similarity correction for the RANS modeling of natural convection in unstably stratified flows
Da-Sol Joo

TL;DR
This paper introduces a global similarity correction to RANS models for buoyancy-driven flows, improving their accuracy in predicting natural convection phenomena by incorporating potential energy effects.
Contribution
A novel algebraic correction function is proposed for RANS models, capturing similarity laws in natural convection that traditional models overlook.
Findings
Enhanced agreement with experimental data for Nusselt number dependencies.
Accurate reproduction of similarity relations in natural convection flows.
Compatibility with standard RANS frameworks and negligible impact on shear-driven flows.
Abstract
This study proposes a global similarity correction for Reynolds-averaged Navier--Stokes (RANS) modeling of buoyancy effects in unstably stratified flows. Conventional two-equation RANS models (e.g., the - model) lack a clear criterion for incorporating unstable buoyancy effects in their scale-determining equations (e.g., -equation). To address this gap, a global correction function is introduced, derived from a generalized algebraic formulation that incorporates available potential energy as an additional parameter. This function reproduces a global similarity law commonly observed in natural convection flows--for instance, the correlation among the Nusselt, Rayleigh, and Prandtl numbers, which can be approximately expressed as a single power law over a wide parameter range. A calibration method is proposed in which an approximate analytical solution for…
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Taxonomy
TopicsComputational Physics and Python Applications · Meteorological Phenomena and Simulations
