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Addition of particles or droplets to turbulent liquid flows or addition of droplets to turbulent gas flows can lead to modulation of turbulence characteristics. Corresponding observations have been reported for very small particle or droplet volume loadings ${\Phi }_{v} $ and therefore may be important when simulating such flows. In this work, a modelling framework that accounts for preferential concentration and reproduces isotropic and anisotropic turbulence attenuation effects is presented. The framework is outlined for both Reynolds-averaged Navier–Stokes (RANS) and joint probability density function (p.d.f.) methods. Validations are performed involving a range of particle and flow-field parameters and are based on the direct numerical simulation (DNS) study of Boivin, Simonin & Squires (J. Fluid Mech., vol. 375, 1998, pp. 235–263) dealing with heavy particles suspended in homogeneous isotropic turbulence (Stokes number $\mathit{St}= O(1\text{{\ndash}} 10)$, particle/fluid density ratio ${\rho }_{p} / \rho = 2000$, ${\Phi }_{v} = O(1{0}^{\ensuremath{-} 4} )$) and the experimental investigation of Poelma, Westerweel & Ooms (J. Fluid Mech., vol. 589, 2007, pp. 315–351) involving light particles ($\mathit{St}= O(0. 1)$, ${\rho }_{p} / \rho \gtrsim 1$, ${\Phi }_{v} = O(1{0}^{\ensuremath{-} 3} )$) settling in grid turbulence. The development in this work is restricted to volume loadings where particle or droplet collisions are negligible. [ABSTRACT FROM PUBLISHER]

Probability density function (PDF) methods are an established tool applied for the simulation of turbulent mixing and turbulent reactive flows. Mixing models are required to close the molecular diffusion term in the PDF transport equation. From the nature of molecular diffusion, several requirements or design criteria can be derived for mixing models. All current models have certain shortcomings with respect to these requirements. A new mixing model is presented which fully satisfies almost all requirements. It conserves the mean of an inert scalar, reduces its scalar variance, and relaxes closely to a Gaussian scalar PDF. Multiple inert scalars without differential diffusion effects evolve independently and are kept bounded within their allowable region. Mixing is conditional on the velocity and particle scalar trajectories are continuous in time leading to a model that is local in a weak sense. Validation tests show that the model can reproduce differential diffusion effects and mixing rate dependencies due to variable initial scalar length scales or Reynolds and Schmidt number variations. [ABSTRACT FROM AUTHOR]

Stochastic Markov processes are used very frequently to model, for example, processes in turbulence and subsurface flow and transport. Based on the weak Chapman-Kolmogorov equation and the strong Markov condition, we present methods to test the Markov hypothesis that is at the heart of these models. We demonstrate the capabilities of our methodology by testing the Markov hypothesis for fluid and inertial particles in turbulence, and fluid particles in the heterogeneous subsurface. In the context of subsurface macrodispersion, we find that depending on the heterogeneity level, Markov models work well above a certain scale of interest for media with different log-conductivity correlation structures. Moreover, we find surprising similarities in the velocity dynamics of the different media considered. [ABSTRACT FROM AUTHOR]