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1. Improved Discrete Random Walk Stochastic Model for Simulating Particle Dispersion and Deposition in Inhomogeneous Turbulent Flows

   https://doi.org/10.1115/1.4047538  

   Mofakham, Amir A. ; Ahmadi, Goodarz ( October 2020 , Journal of Fluids Engineering)

   null (Ed.)

   Abstract The performance of different versions of the discrete random walk models in turbulent flows with nonuniform normal root-mean-square (RMS) velocity fluctuations and turbulence time scales were carefully investigated. The OpenFOAM v2−f low Reynolds number turbulence model was used for evaluating the fully developed streamwise velocity and the wall-normal RMS velocity fluctuations profiles in a turbulent channel flow. The results were then used in an in-house matlab particle tracking code, including the drag and Brownian forces, and the trajectories of randomly injected point-particles with diameters ranging from 10 nm to 30 μm were evaluated under the one-way coupling assumption. The distributions and deposition velocities of fluid-tracer and finite-size particles were evaluated using the conventional-discrete random walk (DRW) model, the modified-DRW model including the velocity gradient drift correction, and the new improved-DRW model including the velocity and time gradient drift terms. It was shown that the conventional-DRW model leads to superfluous migration of fluid-point particles toward the wall and erroneous particle deposition rate. The concentration profiles of tracer particles obtained by using the modified-DRW model still are not uniform. However, it was shown that the new improved-DRW model with the velocity and time scale drift corrections leads to uniform distributions for fluid-point particles and reasonable concentration profiles for finite-size heavy particles. In addition, good agreement was found between the estimated deposition velocities of different size particles by the new improved-DRW model with the available data. 

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2. Flow Regimes and Types of Solid Obstacle Surface Roughness in Turbulent Heat Transfer Inside Periodic Porous Media

   https://doi.org/10.1007/s11242-023-01978-6  

   Srikanth, Vishal ; Peverall, Dylan ; Kuznetsov, Andrey V. ( September 2023 , Transport in Porous Media)

   The role of solid obstacle surface roughness in turbulent convection in porous media is not well understood, even though it is frequently used for heat transfer enhancement in many applications. The focus of this paper is to systematically study the influence of solid obstacle surface roughness in porous media on the microscale flow physics and report its effect on macroscale drag and Nusselt number. The Reynolds-averaged flow field is numerically simulated using the realizable k-ε model for a flow through a periodic porous medium consisting of an in-line arrangement of square cylinders with square roughness particles on the cylinder surface. Two flow regimes are identified with respect to the surface roughness particle height—fine and coarse roughness regimes. The effect of the roughness particles in the fine roughness regime is limited to the near-wall boundary layer around the solid obstacle surface. In the coarse roughness regime, the roughness particles modify the microscale flow field in the entire pore space of the porous medium. In the fine roughness regime, the heat transfer from the rough solid obstacles to the fluid inside the porous medium is less than that from a smooth solid obstacle. In the coarse roughness regime, there is an enhancement in the heat transfer from the rough solid obstacle to the fluid inside the porous medium. Total drag reduction is also observed in the fine roughness regime for the smallest roughness particle height. The surface roughness particle spacing determines the fractional area of the solid obstacle surface covered by recirculating, reattached, and stagnating flow. As the roughness particle spacing increases, there are two competing factors for the heat transfer rate—increase due to more surface area covered by reattached flow and decrease due to fewer roughness particles on the solid obstacle surface. Decreasing the porosity and increasing the Reynolds number amplify the effect of the surface roughness on the microscale flow. The results suggest that heat transfer in porous media can be enhanced, if the increase in drag can be overcome. The results also show that the fine roughness regime, which is frequently encountered due to corrosion, is detrimental to the heat transfer performance of porous media. 

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3. Virtual Experiments of Particle Mixing Process with the SPH-DEM Model

   https://doi.org/10.3390/ma14092199  

   Zhu, Siyu ; Wu, Chunlin ; Yin, Huiming ( May 2021 , Materials)

   null (Ed.)

   Particle mixing process is critical for the design and quality control of concrete and composite production. This paper develops an algorithm to simulate the high-shear mixing process of a granular flow containing a high proportion of solid particles mixed in a liquid. DEM is employed to simulate solid particle interactions; whereas SPH is implemented to simulate the liquid particles. The two-way coupling force between SPH and DEM particles is used to evaluate the solid-liquid interaction of a multi-phase flow. Using Darcy’s Law, this paper evaluates the coupling force as a function of local mixture porosity. After the model is verified by two benchmark case studies, i.e., a solid particle moving in a liquid and fluid flowing through a porous medium, this method is applied to a high shear mixing problem of two types of solid particles mixed in a viscous liquid by a four-bladed mixer. A homogeneity metric is introduced to characterize the mixing quality of the particulate mixture. The virtual experiments with the present algorithm show that adding more liquid or increasing liquid viscosity slows down the mixing process for a high solid load mix. Although the solid particles can be mixed well eventually, the liquid distribution is not homogeneous, especially when the viscosity of liquid is low. The present SPH-DEM model is versatile and suitable for virtual experiments of particle mixing process with different blades, solid particle densities and sizes, and liquid binders, and thus can expedite the design and development of concrete materials and particulate composites. 

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4. Stochastic theory and direct numerical simulations of the relative motion of high-inertia particle pairs in isotropic turbulence

   https://doi.org/10.1017/jfm.2016.859  

   Dhariwal, Rohit ; Rani, Sarma L. ; Koch, Donald L. ( February 2017 , Journal of Fluid Mechanics)

   The relative velocities and positions of monodisperse high-inertia particle pairs in isotropic turbulence are studied using direct numerical simulations (DNS), as well as Langevin simulations (LS) based on a probability density function (PDF) kinetic model for pair relative motion. In a prior study (Rani et al. , J. Fluid Mech. , vol. 756, 2014, pp. 870–902), the authors developed a stochastic theory that involved deriving closures in the limit of high Stokes number for the diffusivity tensor in the PDF equation for monodisperse particle pairs. The diffusivity contained the time integral of the Eulerian two-time correlation of fluid relative velocities seen by pairs that are nearly stationary. The two-time correlation was analytically resolved through the approximation that the temporal change in the fluid relative velocities seen by a pair occurs principally due to the advection of smaller eddies past the pair by large-scale eddies. Accordingly, two diffusivity expressions were obtained based on whether the pair centre of mass remained fixed during flow time scales, or moved in response to integral-scale eddies. In the current study, a quantitative analysis of the (Rani et al. 2014) stochastic theory is performed through a comparison of the pair statistics obtained using LS with those from DNS. LS consist of evolving the Langevin equations for pair separation and relative velocity, which is statistically equivalent to solving the classical Fokker–Planck form of the pair PDF equation. Langevin simulations of particle-pair dispersion were performed using three closure forms of the diffusivity – i.e. the one containing the time integral of the Eulerian two-time correlation of the seen fluid relative velocities and the two analytical diffusivity expressions. In the first closure form, the two-time correlation was computed using DNS of forced isotropic turbulence laden with stationary particles. The two analytical closure forms have the advantage that they can be evaluated using a model for the turbulence energy spectrum that closely matched the DNS spectrum. The three diffusivities are analysed to quantify the effects of the approximations made in deriving them. Pair relative-motion statistics obtained from the three sets of Langevin simulations are compared with the results from the DNS of (moving) particle-laden forced isotropic turbulence for $St_{\unicode[STIX]{x1D702}}=10,20,40,80$ and $Re_{\unicode[STIX]{x1D706}}=76,131$ . Here, $St_{\unicode[STIX]{x1D702}}$ is the particle Stokes number based on the Kolmogorov time scale and $Re_{\unicode[STIX]{x1D706}}$  is the Taylor micro-scale Reynolds number. Statistics such as the radial distribution function (RDF), the variance and kurtosis of particle-pair relative velocities and the particle collision kernel were computed using both Langevin and DNS runs, and compared. The RDFs from the stochastic runs were in good agreement with those from the DNS. Also computed were the PDFs $\unicode[STIX]{x1D6FA}(U|r)$ and $\unicode[STIX]{x1D6FA}(U_{r}|r)$ of relative velocity $U$ and of the radial component of relative velocity $U_{r}$ respectively, both PDFs conditioned on separation $r$ . The first closure form, involving the Eulerian two-time correlation of fluid relative velocities, showed the best agreement with the DNS results for the PDFs. 

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5. Active hydrodynamic imaging of a rigid spherical particle

   https://doi.org/10.1038/s41598-020-58880-0  

   Takagi, Daisuke ; Strickler, J. Rudi ( February 2020 , Scientific Reports)

   A body with mechanical sensors may remotely detect particles suspended in the surrounding fluid via controlled agitation. Here we propose a sensory mode that relies on generating unsteady flow and sensing particle-induced distortions in the flow field. We demonstrate the basic physical principle in a simple analytical model, which consists of a small spherical particle at some distance from a plate undergoing impulsive or oscillatory motion. The model shows that changes in pressure or shear on the plate can be used to infer the location and size of the sphere. The key ingredient is to produce strong shear or strain around the sphere, which requires careful tuning of the viscous boundary layer on the moving plate. This elucidates how some organisms and devices may control their unsteady dynamics to enhance their range of perception.

    

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