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Assessment of integral models for non-Boussinesq lazy plumes using numerical simulations

Published online by Cambridge University Press:  15 December 2025

Michael Meehan*
Affiliation:
Sandia National Laboratories, PO Box 5800, Albuquerque, NM 87185, USA
Pierre Carlotti
Affiliation:
Artelia, 47 avenue de Lugo, Choisy le Roi 94600, France
John Hewson
Affiliation:
Sandia National Laboratories, PO Box 5800, Albuquerque, NM 87185, USA
*
Corresponding author: Michael Meehan, mameeha@sandia.gov

Abstract

Integral modelling of turbulent buoyant plumes is crucial for rapid predictions of plume characteristics. While the governing equations are typically derived using self-similarity and a Boussinesq approximation, these assumptions may not hold for plumes originating from finite-area sources with large density ratios. This work evaluates the accuracy of integral-scale models for non-Boussinesq lazy plumes using high-fidelity numerical simulations of turbulent helium plumes. We analyse the plume kinematics by computing vertical fluxes, plume radius and radial profiles, establishing some disparities between common practice and physical accuracy. We identify how the definition of the plume radius changes the perception of the plume structure when the flow is not self-similar and derive a relationship between the flux-based and threshold-based definitions without requiring self-similarity. We then examine the plume dynamics by evaluating the source terms from the governing plume equations. Our results support neglecting diffusive and viscous effects but emphasise the importance of the mean pressure gradient, even in the self-similar regime. Two coefficients need to be modelled: the well-known entrainment coefficient and the lesser-known momentum correction coefficient, which is a correction required for the momentum equation to account for self-similar and slender approximations. The momentum correction coefficient is found to be approximately constant and slightly greater than the assumed value of 1. The standard entrainment coefficient models perform well up to a local Richardson number three times the asymptotic value but overpredict entrainment for larger Richardson numbers. We propose a correction using the known finite limit of entrainment at infinite Richardson number.

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Type
JFM Papers
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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