Abstract
We develop a generalised unsteady plume theory and compare it with a new direct numerical simulation (DNS) dataset for an ensemble of statistically unsteady turbulent plumes. The theoretical framework described in this paper generalises previous models and exposes several fundamental aspects of the physics of unsteady plumes. The framework allows one to understand how the structure of the governing integral equations depends on the assumptions one makes about the radial dependence of the longitudinal velocity, turbulence and pressure. Consequently, the ill-posed models identified by Scase & Hewitt (J. Fluid Mech., vol. 697, 2012, pp. 455–480) are shown to be the result of a non-physical assumption regarding the velocity profile. The framework reveals that these ill-posed unsteady plume models are degenerate cases amongst a comparatively large set of well-posed models that can be derived from the generalised unsteady plume equations that we obtain. Drawing on the results of DNS of a plume subjected to an instantaneous step change in its source buoyancy flux, we use the framework in a diagnostic capacity to investigate the properties of the resulting travelling wave. In general, the governing integral equations are hyperbolic, becoming parabolic in the limiting case of a ‘top-hat’ model, and the travelling wave can be classified as lazy, pure or forced according to the particular assumptions that are invoked to close the integral equations. Guided by observations from the DNS data, we use the framework in a prognostic capacity to develop a relatively simple, accurate and well-posed model of unsteady plumes that is based on the assumption of a Gaussian velocity profile. An analytical solution is presented for a pure straight-sided plume that is consistent with the key features observed from the DNS.
Highlights
A number of models for statistically unsteady plumes have been developed as extensions of the popular steady-state plume model of Morton, Taylor & Turner (1956)
Perhaps the most rigorous and comprehensively investigated unsteady plume model is that of Scase et al (2006b, referred to hereafter as top-hat plume model (TPM) for Top-hat Plume Model), which was based on a ‘top-hat’ description of the variables within the plume
In Scase, Aspden & Caulfield (2009) TPM was used to predict the behaviour of a plume whose source buoyancy flux undergoes a rapid increase, a comparison with an implicit large eddy simulation revealing that TPM correctly predicted the scaling associated with the longitudinal position of a self-similar pulse structure in the plume
Summary
A number of models for statistically unsteady plumes have been developed (see e.g. Turner 1962; Middleton 1975; Delichatsios 1979; Yu 1990; Vul’fson & Borodin 2001; Scase et al 2006b) as extensions of the popular steady-state plume model of Morton, Taylor & Turner (1956). There, the equations were ostensibly based on the assumption of Gaussian velocity profiles and the starting plume models of Turner (1962) and Middleton (1975), a derivation of the equations was not provided. In conjunction with the leading-order contribution from the shape of the underlying velocity profile, Craske & van Reeuwijk (2015b) proposed a model for unsteady jets that incorporated longitudinal energy dispersion. At its foundation is a framework that clarifies the connection between the Navier–Stokes equations and the integral equations that are used to model unsteady plumes
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