Session M18: Particle-laden Flows: Clustering and Heat Transfer

Quantification of Inertial Particle Clustering and Geometric Confinement Effects in Turbulent Flow Through a Porous Cell

Quantifying how turbulence affects inertial particle clustering, migration,  and deposition within confined geometries of porous beds is of importance in several applications such as hyporheic exchange of river beds, gravel packs in enhanced oil recovery, among others. Direct numerical simulation is performed to investigate effect of turbulent flow in a face centered cubic porous unit cell on the transport of inertial particles at different Stokes numbers (0.01, 0.1, 0.5, 1, and 2) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and collision of particles with pore walls is modeled as perfectly elastic specular reflection. Statistics on Voronoi tessellation volume and its divergence are used to quantify clustering, void formation, and effect of geometric confinement. The general features of cluster and void formation are similar to those in forced, isotropic turbulence, but some very fine scale clusters are developed owing to collisions with wall. Multiscale wavelet analysis also shows signature of the confined geometry on the scale dependent energy spectra of number density.   

Tracking particle clusters in turbulent channel flows via density-based clustering algorithms

The dynamics of clusters of inertial particles in a fully developed turbulent flow are analyzed using a new methodology for cluster identification and temporal tracking. It builds on density-based clustering algorithms DbScan and Optics to identify particle clusters from 3D snapshots of dispersed particles, which are then defined in terms of skeleton markers and boundary particles. Tracking and connectivity of cluster markers in snapshots from sequential time steps provide a computationally efficient tool to study the cluster dynamics. The computational cost of the new methodology is compared to that of conventional Voronoi tessellations. We apply these tools to study the evolution of clusters in a particle-laden turbulent square-duct flow, using data from DNS simulations with point-particle Lagrangian models. By tracking in time information of individual clusters such as their volume and location of constituent markers we analyze the different formation and disintegration processes, i.e. break up and merging of clusters, coagulation or dispersal of particles not assigned to clusters in previous or later times. Spatial information encoded in the cluster labeled markers facilitates the analysis of spatial and temporal correlations between clusters and flow dynamics.   

Preferential alignment and heterogeneous distribution of active non-spherical swimmers near Lagrangian coherent structures

We report the interaction between active non-spherical swimmers and a long-standing flow structure, Lagrangian coherent structures (LCSs), in a weakly turbulent two-dimensional particle-laden flow. Using a hybrid experimental-numerical model, we show that rod-like swimmers have a much stronger and more robust preferential alignment with attracting LCSs than with repelling LCSs. Tracing the swimmers' Lagrangian trajectories, we reveal that the preferential alignment is the consequence of the competition between the intrinsic mobility of the swimmers and the reorientation ability of the strain rate near the attracting LCSs. The strong preferential alignment with attracting LCSs further leads to a strong clustering near the attracting LCSs. Moreover, we show the self-similarity of this clustering, which reduces the intricate interaction to only one control parameter. Our results generically elucidate the interaction between active and non-spherical swimmers with LCSs and, thus, can be widely applied to many natural and engineered fluids.   

Spatial Relationships Between Large Scale Particle Clusters and Momentum Structures

The clustering behavior of inertial particles in a turbulent boundary layer was studied experimentally at the scale of the natural large-scale motions (LSMs) of the momentum field. A new, wavelet-based hierarchy detection tool was employed to identify large-scale coherent clusters of particles, instantaneously. Significant particle clustering at scales of two to three times the boundary layer thickness was observed, with a dominant orientation in the streamwise direction. Conditional averaging was then used to determine the typical coherent motions associated with the large-scale clusters. The influence of LSMs on the size, orientation, and hierarchical organization of particle clusters was explored.    

The Application of a Non-Intrusive Particle Temperature Measurement Methodology for an On-sun Falling Particle Receiver

Falling particle receivers (FPR) such as the one at Sandia National Labs, represent the state-of-the-art Concentrating Solar Power (CSP) technology for energy harvesting. FPR operate by creating a gravity-driven particle curtain which is directly used a transport and storage media for concentrated light. A system paired with an appropriate Brayton power loop is capable of achieving thermal-to-electric conversion efficiencies when operating at temperatures greater than 700 C. However, the FPR presents a unique challenge to the CSP field as the complex coupling of multiple variables, such as particle temperature, wind speed and direction, etc., can impact its thermal performance as advective losses can be strongly present on the system. This work presents the continuation of a series of improvement to a non-intrusive methodology using a high-speed IR camera and a visible-light camera (Nikon D3500) to accomplish this indirect particle temperature measurement, which in turn is used to estimate the heat losses of the receiver. Six variables were considered to study their relative impact towards the receiver efficiency by means of an ANOVA analysis to further understand the importance of mitigating these variable to increase the receiver efficiency.   

Not Participating

Recent interest in dense granular suspensions has focused on characterizing their rheology and modeling the viscosity, whereas little is known about other transport properties such as thermal diffusivity. The goal of this study is to understand the role of particle inertia and fluid turbulence on thermal transport in sheared granular suspensions. The study uses a Taylor-Couette cell with a rotating outer cylinder and fixed inner cylinder to create a uniform shear flow. Spherical polystyrene beads of 2 mm were used to make a suspension with propylene glycol -water mixture as the base fluid. Particle volume fractions in the range 5-50 % are studied. By changing the rotation speed, and therefore the shear rate, particle Reynolds numbers are varied from 0-100, going from Stokes flow to turbulence with increasing inertia. We study the thermal diffusivity of the suspension by examining the decay of the inner wall temperature after a sharp thermal pulse has been applied. The thermal diffusivity is extracted from the observed temperature decay using a model for one-dimensional diffusion into the particle suspension. A non-monotonic behavior of thermal diffusivity with volume fraction is observed.   

The effect of particle clustering on the thermal entrance length in moderately dense gas-solid flows

We perform highly-resolved Eulerian--Lagrangian simulations of moderately dense, gas-solid flows to study the thermal entrance length. We show that strong momentum coupling between the phases results in the generation of dense particle clusters that leads to a 2–3 fold increase in the thermal entrance length, as compared to a uniform (perfectly mixed) distribution. The observed increase is found to be primarily due to the covariance between volume fraction and temperature fluctuations, referred to as the fluid drift temperature. Using scaling arguments and Gene Expression Programming, model closure is obtained in the context of a one-dimensional averaged two-fluid equation.   

An Advection-Diffusion-Reaction (ADR) Equation For Correcting The Self-Induced Velocity and Temperature Disturbances in Euler-Lagrange Point-Particle Methods

In two-way coupled particle-laden Euler-Lagrange simulations, the particles are assumed subgrid and their momentum and energy exchange with the surrounding fluid are modeled as point sources. For particles on the order of the grid resolution, this exchange introduces a local disturbance in the fluid flow that can substantially alter their undisturbed values needed for closure models, resulting in significant errors in the particle dynamics. To correct for this disturbance, advection-diffusion-reaction (ADR) equations are derived for the momentum and heat transfer and solved in addition to the standard conservation equations in two-way coupling. An embedded voxel based approach is used in a small region of influence surrounding each particle to solve these equations and to correct for their self-disturbance. Tests are performed to show that the approach is applicable to arbitrary shaped grids, range of Reynolds and Pectlet numbers, different Euler-Lagrange interpolation kernels, and catpturing hydrodynamic effects of neighboring particles in multiple-particle systems. The newly developed approach is accurate, easy to implement in any flow solver, and affordable.   

Determination of aerodynamic and themal correlations for ellipsoidal particles via direct numerical simulation

 

Direct numerical simulations of the flow and temperature field for a fixed prolate ellipsoid at constant surface temperature in uniform flow are performed. The parameter space defined by the Reynolds number 1 ≤ Re ≤ 100, aspect ratio 1 ≤ β ≤ 8, inclination angle 0⁰ ≤ Ø ≤ 90⁰, and temperature ratio 0.35 ≤ T_R ≤ 1.65 is covered by more than 6,600 computations. Flow fields and temperature fields are visualized for selected configurations. The aspect ratio less than 3 is identified to define the transitional geometries to fibers while higher aspect ratios hardly change the flow topology. The onset of flow separation is analyzed in detail. The heat transfer is primarily determined by the Reynolds number and the temperature ratio. The impact of the inclination angle on the heat transfer increases at higher aspect ratios. The data base is used to determine correlations for drag, lift, torque, and wall-heat transfer. The comparison with the DNS data shows that the fluid-particle dynamics is accurately modeled by the novel correlations.    

LBM-DEM-FEM coupling model: an efficient FSI method to investigate convective heat transfer through non-spherical particle suspensions with particle rotations

Motivation: Shear-driven particle rotation influences heat transfer at high Peclet number (Shu et al., 2021). For non-spherical particles, the shear-induced movements are much more complicated including motions like tumbling and kayaking. The calculation of both the fluid-structure interaction and the two-phase heat transfer requires precise and efficient numerical methods. This study presents an approach to simulate particle movement and heat transfer by a combination of the Lattice Boltzmann method (LBM, for mass and heat flow of the fluid), the Discrete Element method (DEM, for movement of the particles), and a Finite-Element approach (FEM, for heat flow inside the particle).

Method: The open-source coupled LBM and DEM code is provided by Seil (Seil and Pirker 2017), where the force/torque coupling between fluid and particle follows the algorithm by Noble (Noble and Torczynski 1998). The Lattice Boltzmann Method computes the advective-diffusive behavior of incompressible fluid and imposes the forces acting on the particle to the Discrete Element Method, which in turn computes the particle movements. The velocities of the particle are given back to the LBM. For calculating the heat flow inside the particle, a coupling of a FEM code is added to the LBM-DEM approach by mapping the heat fluxes at the boundary of the particle from the LBM to the FEM. Back-coupling is achieved by transferring the temperature back to the LBM (Suzuki et al. 2018).

Results: Model validation is performed by computing the rotation speed and the effective thermal conductivity of a spherical particle. Results are compared with simulations utilizing the commercial software COMSOL^®, showing good agreement. For non-spherical particle, the shear-driven rotation speed is compared to an approximated Jeffery analytical solution, showing again good agreement.