Discrete Element Modeling (DEM) of Agglomeration of Polymer Particles

Kroupa, Martin; Klejch, M.; Vonka, Michal; Košek, Juraj

doi:10.1016/j.proeng.2012.07.395

Cited by 11 publications

(10 citation statements)

References 10 publications

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“…However, during the experiment, some bonds may break but new bonds may also be created at new contact points. The concept of bond formation between particles and its implementation in DEM is still open [ Kroupa et al , ]. Hence, many different bonding models currently exist and we have chosen the following simple bond formation criterion that allows us to study the competing effects of fragmentation and aggregation of bonds:

\sqrt{N_{ij}^{2} + S_{ij}^{2}} F_{a}

…”

Section: Methodsmentioning

confidence: 99%

Granulation of snow: From tumbler experiments to discrete element simulations

Steinkogler

Gaume²,

Löwe³

et al. 2015

J. Geophys. Res. Earth Surf.

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It is well known that snow avalanches exhibit granulation phenomena, i.e., the formation of large and apparently stable snow granules during the flow. The size distribution of the granules has an influence on flow behavior which, in turn, affects runout distances and avalanche velocities. The underlying mechanisms of granule formation are notoriously difficult to investigate within large-scale field experiments, due to limitations in the scope for measuring temperatures, velocities, and size distributions. To address this issue we present experiments with a concrete tumbler, which provide an appropriate means to investigate granule formation of snow. In a set of experiments at constant rotation velocity with varying temperatures and water content, we demonstrate that temperature has a major impact on the formation of granules. The experiments showed that granules only formed when the snow temperature exceeded −1 ∘ C. No evolution in the granule size was observed at colder temperatures. Depending on the conditions, different granulation regimes are obtained, which are qualitatively classified according to their persistence and size distribution. The potential of granulation of snow in a tumbler is further demonstrated by showing that generic features of the experiments can be reproduced by cohesive discrete element simulations. The proposed discrete element model mimics the competition between cohesive forces, which promote aggregation, and impact forces, which induce fragmentation, and supports the interpretation of the granule regime classification obtained from the tumbler experiments. Generalizations, implications for flow dynamics, and experimental and model limitations as well as suggestions for future work are discussed.

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\sqrt{N_{ij}^{2} + S_{ij}^{2}} F_{a}

…”

Section: Methodsmentioning

confidence: 99%

Granulation of snow: From tumbler experiments to discrete element simulations

Steinkogler

Gaume²,

Löwe³

et al. 2015

J. Geophys. Res. Earth Surf.

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“…They are important in the simulation of a myriad of systems such as (but not limited to) colloids (Bolintineanu et al, 2014), crystals (Tan et al, 2009), polymers (Kroupa et al, 2012), powders (David et al, 2007), particulate flows (Kamrin and Koval, 2014) and granular materials (Xu and Chen, 2013). Packs of "hard" particles are defined as arrangements of particles within a given bulk volume wherein no two particles overlap.…”

Section: Introductionmentioning

confidence: 99%

Rapid Generation of Particle Packs at High Packing Ratios for DEM Simulations of Granular Compacts

Campello

Cassares

2016

Lat. Am. j. solids struct.

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In this work we present a simple, fast technique for generating particle packs at high packing ratios aiming at the simulation of granular compacts via the discrete element method (DEM). We start from a random sequence addition particle generation algorithm to generate a "layer" of non-overlapping spherical particles that are let to evolve dynamically in time under the action of "compacting" or "jamming" pseudo forces. A "layer-by-layer" approach is then followed to generate multiple layers on top of each other. In the end, very dense packs with pre-defined bulk shapes and sizes (e.g. rectangles in two dimensions and prisms in three dimensions) are achieved. The influence of rolling motion (with particle rotation and spin) along with inter-particle friction on the density and ordering of the generated packs is assessed. Both congruent and inhomogeneous packs (with respect to particle sizes) are created and their packing properties evaluated. We believe that simple techniques for fast generation of particle packs at high packing ratios are essential tools for the DEM simulation of granular compacts.

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“…Several works using CFD tools in the study of heterogeneous reactors gas‐phase polymerization can be found in the literature, such as those used Eulerian–Eulerian modeling, Lagrangian–Eulerian modeling, and population balance . A good review of the use of CFD tools in olefin polymerization reactors can be found in Khan et al However, most of the authors conducted a research macroscopic level, i.e., studied the reactor dynamics as a whole, and this work is focused on the investigation of the heat transfer phenomena at the level of the particle.…”

Section: Introductionmentioning

confidence: 99%

CFD Analysis of Gas-Particle Heat Transfer in Gas-Phase Olefin Polymerizations

Guidolini

Fontes

Lage

et al. 2016

Macromol. React. Eng.

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importance for obtainment of high rates of monomer consumption. However, if particle fragmentation takes place in an uncontrolled way, undesirable production of polymer particles with poor morphological properties and small diameter (fi nes) can occur, leading to operational problems and production of off-spec materials. [1][2][3] Polyolefi ns can be produced commercially in slurry, solution, bulk, and gas-phase processes. One of the main advantages of gas-phase processes is the possibility to operate the process continuously in agitated tank reactors. However, temperature control is normally less efficient in gas-phase than in liquid-phase processes, due to the combination of high rates of reaction, reduced heat capacity of the gas and higher mass and heat transfer resistances between the continuous gas phase and the polymer particles. This characteristic property of gasphase reactors may impose the use of lower specifi c heat generation capacity, higher residence times, and longer grade transition periods, when compared to liquid-phase processes. Despite that, gas-phase polymerization reactors can be very effi cient and present high operational fl exibility, justifying the signifi cant industrial interest in these processes. It is particularly important to note that the solid polymer material can be easily separated Computational fl uid dynamics (CFD) is used to study the gas-particle heat transfer in gasphase olefi n polymerizations. Particularly, the effects of particle rotation on the gas-particle heat transfer coeffi cient and internal particle temperatures are evaluated, showing that particle rotation can exert a signifi cant impact on observed temperature profi les, so that this effect should not be neglected during detailed CFD process simulations. As a consequence, particle rotation can lead to particle cooling and development of spherical gradient symmetry, validating the use of simpler modeling schemes that are based on reaction-diffusion in symmetrical spherical geometry.

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Discrete Element Modeling (DEM) of Agglomeration of Polymer Particles

Cited by 11 publications

References 10 publications

Granulation of snow: From tumbler experiments to discrete element simulations

Granulation of snow: From tumbler experiments to discrete element simulations

Rapid Generation of Particle Packs at High Packing Ratios for DEM Simulations of Granular Compacts

CFD Analysis of Gas-Particle Heat Transfer in Gas-Phase Olefin Polymerizations

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