How nano‐scale roughness impacts the flow of grains influenced by capillary cohesion

LaMarche, Casey Q.; Miller, A. Woodruff; Liu, Peiyuan; Leadley, Stuart R.; Hrenya, Christine M.

doi:10.1002/aic.15830

Cited by 6 publications

(6 citation statements)

References 56 publications

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“…23,24 However, some experiments 5 reported that a liquid bridge may appear when two approaching particles are within a small separation distance before their contact at high liquid loading, and the small-scale particle roughness can initiate an early liquid bridge prior to particle collision. 25 This suggests that a liquid bridge can establish when h is less than a critical value h c . In addition, the experimental study 26 on coordination number of liquid bridge in a static bulk granular system also indicates that each gap between particles might be bridged by liquid as long as it is smaller than the rupture distance (i.e., liquid bridge forms when h < h rup ).…”

Section: Introductionmentioning

confidence: 99%

CFD–DEM simulations of wet particles fluidization with a new evolution model for liquid bridge

2022

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A new model for liquid-bridge evolution with consideration of particle dynamics, is proposed to improve Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) simulations of wet particles fluidization under high liquid loading and viscosity. A liquid bridge is allowed to form and remains stable only when the normal relative velocity of two particles is lower than a critical value v nc . A large v nc leads to an increase of liquid-bridge or cohesive force. The model can be reduced to the conventional liquid-bridge model in literature when v nc = 0 or ∞. With the new model, the prediction of bubble properties including bubble center, aspect ratio, and volume agrees well with the experimental data in literature. In particular, under high liquid loading, bubble disintegration due to particle agglomerating is reasonably captured.The simulations demonstrate the advantage of the new model that can extend the liquid-bridge models and CFD-DEM for high liquid loading and viscosity.

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Section: Introductionmentioning

confidence: 99%

CFD–DEM simulations of wet particles fluidization with a new evolution model for liquid bridge

2022

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“…Note that other forms of dimensionless number were also defined in previous works to describe the dynamics of adhesive particles in fluid flow, which is similar to the expression in Equation . Considering that the fluid velocity cannot be directly attained in this work, Equation appears to be most appropriate in the current application, where the pressure gradient and the channel width are both direct input parameters.…”

Section: Resultsmentioning

confidence: 99%

Migration and agglomeration of adhesive microparticle suspensions in a pressure‐driven duct flow

Liu

2020

AIChE Journal

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Transport of suspensions consisting of monodisperse adhesive microparticles in a pressuredriven duct flow with the Reynolds number in the range of 5.4-108 is analyzed by means of a coupled lattice Boltzmann method with the discrete element method. The influence of the adhesion on migration and agglomeration of particles is investigated. The results show that the suspensions undergo a transition from purely lateral focusing to completely agglomeration as the surface energy is increased. A dimensionless adhesion number, defined as the ratio of the adhesive force to the drag force, is employed to characterize the degree of agglomeration. It is found that all the particles come into agglomerates as the adhesion number reaches a critical value. Moreover, a detailed examination of size evolution and velocity illustrates that the agglomerates mainly grow spherically, and their velocities depend on the lateral positions rather than their sizes, as the Stokes number is far below one.adhesion, agglomeration, discrete element method, duct flow, lattice Boltzmann method 1 | INTRODUCTION Migration of particle suspensions in a confined channel or vessels are ubiquitous in industries and engineering, such as petroleum production, food processing, pharmaceuticals, sewage treatment, as well as microfluids in biological processes. It is first observed by Segré and Silberberg 1 that a spherical particle in a Poiseuille pipe flow migrates across the streamline and focuses at a specific equilibrium position at approximately 0.6 times the radius from the axis. From then on, much effort has been made to uncover the mechanism of this interesting phenomenon both theoretically 2-5 and experimentally. 6-11 A range of novel applications based on the inertial focusing has been developed, especially in micro channels with the rise of microfabrication, including particle filtration, separation, flow cytometry, 12-16 and so on. However, as the particle size goes down to micron or submicron scale, agglomeration is inevitable during the transport of particle suspensions due to the cohesive nature, which in turn produces numerous negative effects in industries. For example, the agglomeration of asphaltenes or gas hydrates causes pipeline blockage 17,18 in the oil and gas exploration and refining industries. Therefore, it is of great importance to gain in-depth knowledge of the agglomeration mechanism.It is generally recognized that the agglomeration is driven by the collisions of particles and the cohesive interaction. The collisions could be induced by shear flow, diffusion or Brownian motion, while the cohesive interaction may be caused by different types of forces, such as electrostatic, van der Waals, and liquid bridge. Moreover, the mechanical properties of the particles, including mass density, elastic modulus, friction coefficient, and so on also play important roles in the interparticle collision and thus can influence the agglomeration. Most of the previous studies focus on the dynamic evolution of the agglomerates, include the size evolu...

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“…In this work, estimates for these quantities were based on complex, rigorous force models for van der Waals forces (Equation ()) and humidity effects (Table 2). Such particle cohesion models can take years to develop and validate, 21,35,42 which leads to two practical questions: (i) what is the minimal, yet sufficient, physics needed in such a model? (ii) Can the corresponding model parameters be extracted from a simple bulk experiment?…”

Section: Discussionmentioning

confidence: 99%

“…(ii) Condensed‐capillary cohesion –The condensed‐capillary cohesive force ( F RH ) is determined by solving the system of equations provided in Table 2, where RH is relative humidity, σ is surface tension, and η RH is the product of ambient air temperature, ideal gas constant and molar density of water; the accuracy and assumptions used for calculating F RH are discussed elsewhere 27,42 …”

Section: Methodsmentioning

confidence: 99%

“…Thus, the BB is the (relatively dilute) starting point of our sedimentation system, and it was investigated experimentally 21,53 . The minimum velocity associated with the presence of bubbles U mb , normalized by the non‐cohesive value U NC , 42,53 is the dependent variable of interest. When solids are fully fluidized in the bubbling state, the drag equals bed weight, and thus

{Bo}_{normalG, BB} = F_{\max} / italicmg italic.

…”

Section: Methodsmentioning

confidence: 99%

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Toward general regime maps for cohesive‐particle flows: Force versus energy‐based descriptions and relevant dimensionless groups

et al. 2021

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Much confusion exists on whether force‐ or energy‐based descriptions of cohesive‐particle interactions are more appropriate. We hypothesize a force‐based description is appropriate when enduring‐contacts dominate and an energy‐based description when contacts are brief in nature. Specifically, momentum is transferred through force‐chains when enduring‐contacts dominate and particles need to overcome a cohesive force to induce relative motion, whereas particles experiencing brief contacts transfer momentum through collisions and must overcome cohesion‐enhanced energy losses to avoid agglomeration. This hypothesis is tested via an attempt to collapse the dimensionless, dependent variable characterizing a given system against two dimensionless numbers: A generalized bond number, BoG–ratio of maximum cohesive force to the force driving flow, and a new Agglomerate number, Ag–ratio of critical cohesive energy to the granular energy. A gamut of experimental and simulation systems (fluidized bed, hopper, etc.), and cohesion sources (van der Waals, humidity, etc.), are considered. For enduring‐contact systems, collapse occurs with BoG but not Ag, and vice versa for brief‐contact systems, thereby providing support for the hypothesis. An apparent discrepancy with past work is resolved, and new insight into Geldart's classification is gleaned.

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How nano‐scale roughness impacts the flow of grains influenced by capillary cohesion

Cited by 6 publications

References 56 publications

CFD–DEM simulations of wet particles fluidization with a new evolution model for liquid bridge

CFD–DEM simulations of wet particles fluidization with a new evolution model for liquid bridge

Migration and agglomeration of adhesive microparticle suspensions in a pressure‐driven duct flow

Toward general regime maps for cohesive‐particle flows: Force versus energy‐based descriptions and relevant dimensionless groups

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