Kinematic and Dynamic Pair Collision Statistics of Sedimenting Inertial Particles Relevant to Warm Rain Initiation

In recent years, direct numerical simulation (DNS) approach has become a reliable tool for studying turbulent collision-coalescence of cloud droplets relevant to warm rain development. It has been shown that small-scale turbulent motion can enhance the collision rate of droplets by either enhancing the relative velocity and collision efficiency or by inertia-induced droplet clustering. A hybrid DNS approach incorporating DNS of air turbulence, disturbance flows due to droplets, and droplet equation of motion has been developed to quantify these effects of air turbulence. Due to the computational complexity of the approach, a major challenge is to increase the range of scales or size of the computation domain so that all scales affecting droplet pair statistics are simulated. Here we discuss our on-going work in this direction by improving the parallel scalability of the code, and by studying the effect of large-scale forcing on pair statistics relevant to turbulent collision. New results at higher grid resolutions show a saturation of pair and collision statistics with increasing flow Reynolds number, for given Kolmogorov scales and small droplet sizes. Furthermore, we examine the orientation dependence of pair statistics which reflects an interesting coupling of gravity and droplet clustering

Effect of fractal dimension of agglomerate structure on particle-particle interactions in turbulent flow

A systematic approach to simulate particle-particle interactions considering agglomerate breakup is developed using large eddy and discrete particle simulations, with the technique applied to solid-liquid flows in a vertical turbulent channel. The results indicate that the fractal dimension and size of the agglomerate are key parameters that control shear-induced breakup dynamics which becomes slower as the fractal dimension increases from df = 2.0 to df = 3.0, and ultimately to no breakup. Breakup processes reduce the number of agglomerates in the system as well as populating the system with particles of smaller size, thereby promoting more collisions and collisions leading to agglomeration. These results are encouraging and are consistent with expected physical behaviour

Large Eddy Simulation of Particle Agglomeration with Shear Breakup in Turbulent Channel Flow

A systematic technique is developed for studying particle dynamics as induced by a turbulent liquid flow, in which transport, agglomeration, and breakup are considered. An Eulerian description of the carrier phase obtained using large eddy simulation is adopted and fully coupled to a Lagrangian definition of the particle phase using a pointwise discrete particle simulation. An efficient hard-sphere interaction model with deterministic collision detection enhanced with an energy-balance agglomeration model was implemented in an existing computational fluid dynamic code for turbulent multiphase flow. The breakup model adopted allows instantaneous breakup to occur once the transmitted hydrodynamic stress within an agglomerate exceeds a critical value, characterised by a fractal dimension and the size of the agglomerate. The results from the developed technique support the conclusion that the local turbulence kinetic energy, its dissipation rate, and the agglomerate fractal dimension control the kinetics of the agglomeration and de-agglomeration processes, and as well as defining with time the morphology of the particles and their resultant transport. Overall, the results are credible and consistent with the expected physical behavior and with known theories

Parallel Implementation of Particle Tracking and Collision in a Turbulent Flow

Abstract. Parallel algorithms for particle tracking are central to the modeling of a wide range of physical processes including cloud formation, spray combustion, flows of ash from wildfires and reactions in nuclear sys-tems. Here we focus on tracking the motion of cloud droplets with radii in the range from 10 to 60 µm that are suspended in a turbulent flow field. The gravity and droplet inertia are simultaneously considered. Our codes for turbulent flow and droplet motion are fully parallelized in MPI (message passing interface), allowing efficient computation of dynamic and kinematic properties of a polydisperse suspension with more than 107 droplets. Previous direct numerical simulations (DNS) of turbulent collision, due to their numerical complexity, are typically limited to small Taylor microscale flow Reynolds numbers ( ∼ 100), or equivalently to a small physical domain size at a given flow dissipation rate in a turbulent cloud. The difficulty lies in the necessity to treat simultaneously a field representation of the turbulent flow and free movement of particles. We demonstrate here how the particle tracking and collision can be handled within the framework of a specific domain decomposition. Our newly developed MPI code can be run on computers with distributed memory and as such can take full advantage of available computational resources. We discuss scalability of five major computational tasks in our code: col-lision detection, advancing particle position, fluid velocity interpolation at particle location, implementation of the periodic boundary condition, using up to 128 CPUs. In most tested cases we achieved parallel efficiency above 100 %, due to a reduction in effective memory usage. Finally, our MPI results of pair statistics are validated against a previous OpenMP implementation.