Wednesday, April 30 - CDT
Please join us for a poster session and reception featuring the research of junior scientists from academe (graduate students, post doctoral researchers, and untenured faculty). The posters to be presented are listed below:
Electrostatic Charging and Entrainment Behaviors of Binary and Quaternary Particulate Systems in Fluidized Beds
Xiaozhou Zhou, PhD Candidate, Lenfest Center for Sustainable Energy, Columbia University
A number of commercial fluidization processes involve binary or quaternary particulate systems with different particle sizes and densities. During the operation of multiphase systems such as fluidized beds, electrostatic charges are generated primarily via triboelectric or frictional charging due to the dielectric nature of the materials. The accumulation of electrostatic charge within the system can impact the fluidization behavior and in some cases can be operationally hazardous. In this study, the electrostatic charge generation and accumulation are investigated for binary and quaternary particulate systems using a faraday cup system and an on-line electrostatic probe system. Specifically, the effect of addition of two different fine iron ores (i.e., hematite and magnetite) in fluidized beds is studied in terms of particle-particle interactions and entrainment rates. The behaviors of different particulate systems are found to highly depend on the chemical and physical properties of particles such as size, density, hydrophobicity, surface roughness and even magnetism. The results suggest that the enhanced electrostatic forces between fine and coarse particles due to significant electrostatic charging phenomenon during fluidized bed operation can retain the fines to some extent.
Mark R. Kanner, Levich Institute and Physics Department at City College and CUNY Graduate Center. Carl Schreck, Lawrence Berkeley National Laboratory. Corey O'Hern, Yale University. Mark D. Shattuck, Levich Institute and Physics Department at City College
We use simulations of bidisperse disks that interact via purely repulsive linear springs to determine properties of contact networks during vibration at various energies and pressures. From a set of initially existing contacts in a mechanically stable reference state the contact probability during vibration can be predicted by measuring the inter-particle potential before vibration. We explore the energy regions below particle rearrangement where our prediction is valid and discuss a physical mechanism for this behavior based on the exchange of potential and kinetic energy between particles.
Peiyuan Liu, University of Colorado Boulder
Fine particles exhibit complex flow patterns due to the strong interparticle cohesion and a reliable method to predict the fluidization behaviors for fine particles remains absent. The Discrete Element Method (DEM) based simulations, which help bridge the experimental and theoretical approaches, may aid in formulating a general continuum theory for fluidization of fine particles. Cohesion can be easily incorporated in DEM in order to simulate fine particles. However, the providing a correct form of a cohesion model is more difficult. Though it is well known that cohesion is affected by surface roughness, input parameters in cohesion models were often ad hoc selected and validation of simulations results via experiments is rarely conducted. In this work, DEM simulations were performed to study the fine particles in a gas-fluidized bed. A stochastic approach was developed to incorporate the surface coverage of asperities in DEM. Using the size and coverage of asperities measured from the analysis of Scanning Electron Microscopy (SEM) images of particle surface, DEM with a cohesion model based on the Rumpf model, successfully reproduced the experimental results in terms of fluidization curves. Assuming a smooth surface of particles would otherwise lead to considerable overestimation of minimum fluidization velocity. Simulations of fine particles in a periodic riser were also conducted with the properties of particle agglomerates collected. It is found that agglomerates reduced with increasing coverage of asperity. The results highlight the necessity of incorporating surface asperities in DEM to obtain consistent results with experiments.
Carl Schreck, Lawrence Berkeley National Laboratory
Granular media has complex vibrational properties. Contact breaking and Hertzian interactions between grains can both give rise to nonlinear vibrational response of static granular packings. Through molecular dynamics simulations in model granular packings that interact via Hertzian spring potentials, we show that while Hertzian interactions lead to weak nonlinearities in the vibrational behavior (e.g. the generation of harmonics of the eigenfrequencies of the dynamical matrix), the vibrational response of static packings with Hertzian contact interactions is dominated by contact breaking as found for systems with repulsive linear spring interactions.
Kieran Murphy, Universiy of Chicago. Heinrich Jaeger, University of Chicago
One of the aims of granular physics is to understand how local interactions between macro-particles can give rise to large scale properties of the aggregate. We investigate such local interactions when external mechanical stresses are applied. X-ray computed tomography is used to monitor and track local (re-)configurations inside three-dimensional aggregates of 3D-printed particles of various shapes. By comparing aggregate reconstructions at various strain values, from no applied stress to just after the yield point where the granular packing transitions into the plastic regime, we examine the dependence on particle shape of the local particle reconfigurations that are responsible for yielding or occur as precursors to failure.
Ali Ozel, Department of Chemical and Bological Engineering, Princeton University. Yile Gu, Department of Chemical and Bological Engineering, Princeton University. Stefan Radl, Institute for Process and Particle Engineering, Graz Univeristy of Technology. Sankaran Sundaresan, Department of Chemical and Bological Engineering, Princeton University
Euler-Lagrange simulations of fluidized beds, where the locally-averaged equations of motion for the fluid phase is solved in an Eulerian framework and the particles are tracked in a Lagrangian fashion, have found widespread use in the study of fluidization [1-4]. This approach is commonly referred to as CFD (computational fluid dynamics)-DEM (discrete element method) when all the particles are followed and as CFD-DPM (discrete parcel method) or MP-PIC (multiphase particle-in-cell) when only a small number of representative particles (a.k.a. “parcels”) are simulated [3,4]. Many research groups are currently investigating the effects of cohesion and size distribution on fluidization characteristics via CFD-DEM simulations [for example, see ref. 1, 2].
We have performed CFD-DEM simulations of gas-fluidization of Geldart Group A particles in small periodic domains in order to probe the fluidization characteristics of gas-fluidized suspensions at volume fractions typically observed in circulating fluidized beds and turbulent fluidized beds. In this poster, we will present results related to the following three questions: (a) How does the inclusion of cohesion alter the fluidization of monodisperse particles? (b) How does the addition of fines affect fluidization when cohesion is not considered? (c) What is the combined effect of fines and cohesion?
We also ask how one should systematically coarse-grain the results of such detailed CFD-DEM simulations to obtain effective constitutive models (for example, for the fluid-particle interaction force) that are needed for affordable simulations of industrial scale beds, which entails coarse fluid grids as well simulation of only a small number of representative particles. As shown previously [5,6], when such coarse-graining is done, the drag coefficients must be corrected. We will demonstrate in this poster that both coarsening the fluid grid and switching from DEM to DPM lead to lower effective drag coefficients.
Anastasia Krasovsky, Department of Chemical and Biological Engineering, Colorado School of Mines
Numerous YouTube videos show people walking on "water". This "water" is a mixture of cornstarch and water that exhibits a phenomenon known as shear thickening. The viscosity of shear thickening fluids dramatically increases upon reaching a critical stress (e.g., when a human foot contacts the fluid), but behaves like a liquid below the thickening threshold. Chemical mechanical polishing (CMP) slurries also exhibit shear thickening. CMP is a fundamental technology used in the semiconductor manufacturing industry to polish and planarize a wide range of materials for the fabrication of microelectronic devices (i.e., computer chips). During the high shear polishing process, it is hypothesized that individual slurry particles (~100 nm) collide with one another to form large agglomerates (>500 nm) that cause the slurry to shear thicken. These agglomerates tend to dig into the material surface triggering defects such as scratches or gouges during polishing (costing the semiconductor industry billions of dollars annually). The project's goal is to understand the high shear rheological behavior of CMP slurries and to link changes in particle structure, both temporary and permanent, to the observed shear thickening response through the use of high shear (>10,000 s-1) rheology. Small-angle light scattering was employed in situ with rheological characterization (rheo-SALS) to identify the formation, shape, and size of agglomerates generated under shear. Current work is transitioning from studying fractal shaped fumed silica (currently used by industry) to spherical colloidal silica nanoparticles.
Victor Lee, University of Chicago
We report high-speed tracking of freely falling charged grains in the co-moving frame. Elliptical and hyperbolic Keplerian orbits due to electrostatic interaction between oppositely charged grains are observed directly. By using Nelder-Mead optimization method, we are able to reconstruct the Keplerian trajectories in three-dimensional space. We also find that electrostatic force can lead to aggregation in a granular stream.
Austin B. Isner (Speaker), Paul B. Umbanhowar, Julio M. Ottino, and Richard M. Lueptow, Northwestern University
The discrete element method (DEM) is a popular simulation technique that has proven useful in the study of granular flows, particularly their assembly microstructure, interparticle force networks, stress distribution, and flow kinematics. Of practical concern is the simulation of particle systems at industrially relevant length and time scales, which may require simulating tens to hundreds of millions of particles using a variety of flow geometries and contact force models. Although progress has allowed these computationally expensive simulations to run on highly scalable multi-processor systems, this approach may require significant capital investment or access to high performance computing resources. However, general purpose graphics processing unit (GPU) computing approaches have recently become a viable alternative that leverages the built-in parallelism of discrete GPU hardware, which can contain many thousands of parallel processing cores on a single device, as opposed to the four or six cores found in many modern CPU’s. Here, we present a proof-of-concept implementation of DEM on a consumer-grade GPU based on Nvidia’s CUDA Particles SDK, which incorporates a linear spring dashpot normal force model and a sliding and elastic tangential frictional force model. The DEM simulations are validated by comparing particle streamwise concentration profiles in quasi-2D bounded heap flows of bidisperse mixtures to those of experiments. We investigated the dependence of several kinematic parameters including flowing layer depth, diffusivity, and percolation length on various control parameters such as particle size ratio and two-dimensional feed flow rate. In particular, we find that the interparticle percolation length scale normalized by the small particle diameter is approximately proportional to the logarithm of particle size ratio, R, (R = dl / ds, where dl and ds are the diameters of the large and small particle, respectively) for size ratios in the range R = 1.1 to R = 3. An approach to generalize our understanding of shear-driven segregation to polydisperse systems is also tested using GPU-accelerated DEM simulations of polydisperse mixtures. As well as achieving real-time visualization of simulation results, we achieve a performance improvement that is on average one order-of-magnitude greater than an analogous DEM algorithm run on a traditional multi-core processor. The cost-savings (on a TeraFLOPS/$ basis) of GPU-accelerated DEM makes GPU-based DEM a promising platform for sustained scalability in simulations of certain granular systems.
Zafir Zaman, Paul B. Umbanhowar, Julio M. Ottino, and Richard M. Lueptow, Northwestern University
Granular flow and mixing experiments in rotating partially filled tumblers are often limited to visualization along walls or the free surface. To probe the dynamics deep inside the bed, a common approach is to experimentally utilize quasi-two-dimensional (quasi-2D) geometries and infer the three dimensional (3D) behavior by assuming that the flow is primarily 2D with diffusive spanwise particle motion. However, this model can miss subtle effects seen solely in 3D geometries. For example, we demonstrate that an axial drift of monodisperse particles exists in partially filled spherical and double cone tumblers using experiments and discrete element method (DEM) simulations. The drift is small (1-2 particle diameters or 1-3% of the tumbler diameter per flowing layer pass) relative to streamwise displacements, whose speed depends on the flowing layer length.
To further our understanding of 3D flow and mixing in tumblers, we designed and built an X-ray imaging system that provides subsurface imaging of the tumbler during flow. Tracer (X-ray opaque) particles in a bed of X-ray translucent particles are tracked to construct trajectories through the particle bed. Stroboscopic imaging of the tumbler can provide Poincaré sections to determine regions of good mixing and regions of segregation. Current work involves providing experimental support for the existence of persistent segregated regions for a two axis tumbling protocol, as predicted by a dynamical systems theoretical model. Ultimately, the verification of the model will allow for informed design of tumbling protocols. Funded by NSF Grant CMMI-1000469.