Steady shear rheology of dilute polystyrene particle gels

Folkersma, Rudy; Diemen, A. J. G. van; Lavèn, Jozua; Stein, H.N.

doi:10.1007/s003970050177

Cited by 14 publications

(11 citation statements)

References 23 publications

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“…(28), (30), and (34) to the friction coefficients for the spherical particle with the mass-equivalent radius are compared in Fig. 3.…”

Section: Resultsmentioning

confidence: 99%

“…A spherical particle is deposited if the distance between its mass center and the fiber surface is R P , while for an aggregate it happens when this distance equals an outer radius of a cluster (the cluster maximum radius), R S . This outer radius is commonly used as the collision radius (e.g., [26][27][28][29]). Mountain et al [30] instead of R S used the radius of gyration but Veerapaneni and Wiesner [26] explain that such approach is incorrect, since the collision radius is a distance within which the aggregate encounter another cluster, particle or an obstacle, thus, it should be equal to the outer radius of the aggregate.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Deposition efficiency of fractal-like aggregates in fibrous filters calculated using Brownian dynamics method

Bałazy

Podgórski

2007

Journal of Colloid and Interface Science

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“…(28), (30), and (34) to the friction coefficients for the spherical particle with the mass-equivalent radius are compared in Fig. 3.…”

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Deposition efficiency of fractal-like aggregates in fibrous filters calculated using Brownian dynamics method

Bałazy

Podgórski

2007

Journal of Colloid and Interface Science

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“…Neglecting the aggregate elastic stretching, assumes a viscous stress response s ¼ h _ g. For the sake of a realistic starting point we use parameters that were obtained earlier 18 by tting the orthokinetic model against rheological data for latex suspensions. 16 In particular k ¼ 1.82, f max ¼ 0.60 in eqn (5) and d F ¼ 2.3, F c ¼ 0.3 nN, r 1 ¼ 1.0 mm. Unless explicitly stated the same values are used throughout the text.…”

Section: Modelmentioning

confidence: 95%

“…Perikinetic aggregation and the related rheology under shear have been studied by many authors. 5,16,17 The perikinetic processes are further complicated by the fact that the aggregation process itself is reversible and the size distribution is dynamically formed in a competition between aggregation and aggregate breakage due to the hydrodynamic stresses induced by shear. 5,18 In general, particles under shear ow can experience both, peri-and orthokinetic aggregation.…”

Section: Introductionmentioning

confidence: 99%

Rheology dynamics of aggregating colloidal suspensions

et al. 2014

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We study a colloidal model based on population balances in the context of complex fluid rheology. Two typical particle microstructure kinetics, orthokinetic, collisions due to shear, and perikinetic, collisions due to Brownian motion, are found to appear at continuum as different flow behaviors - those having monotonic and non-monotonic flow curves, respectively. Solving the colloidal model together with the 1D Stokes equation for laminar, incompressible flow with Couette boundary conditions, allows bridging the gap between the rheological experiments and the microstructural modeling. The analysis of such a model reveals that orthokinetic particle suspensions have a uniquely defined, continuous steady state shear profile, whereas suspensions in which also perikinetic collisions are present, the steady state can be shear banded and non-unique. Thus, the shear banded configurations at a steady state are found to depend on the initial conditions and the collision kinetics of the system. At high shear rates all the studied cases show continuous shear profiles.

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“…A shear flow is created by exerting a torque on one of the cylinders. Apparent viscosity is deduced from the shear rate and the torque (see for example [1]). Such experiments are still out of range of direct simulations, because the number of bodies (solid spheres in a polymer solution, red cells in the blood, ...) is huge in real situations.…”

Section: Introductionmentioning

confidence: 99%

Fluid–particle shear flows

Maury¹

2003

ESAIM: M2AN

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Abstract. Our purpose is to estimate numerically the influence of particles on the global viscosity of fluid-particle mixtures. Particles are supposed to rigid, and the surrounding fluid is newtonian. The motion of the mixture is computed directly, i.e. all the particle motions are computed explicitly. Apparent viscosity, based on the force exerted by the fluid on the sliding walls, is computed at each time step of the simulation. In order to perform long-time simulations and still control the solid fraction, we assume periodicity of the flow in the shear direction. Direct simulations are based on the so-called Arbitrary Lagrangian Eulerian approach, which we adapted to make it suitable to periodic domains. As a first step toward modelling of interacting red cells in the blood, we propose a simple model of circular particles submitted to an attractive force which tends to form aggregates.Mathematics Subject Classification. 76T20, 65M60, 92-08.

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Steady shear rheology of dilute polystyrene particle gels

Cited by 14 publications

References 23 publications

Deposition efficiency of fractal-like aggregates in fibrous filters calculated using Brownian dynamics method

Deposition efficiency of fractal-like aggregates in fibrous filters calculated using Brownian dynamics method

Rheology dynamics of aggregating colloidal suspensions

Fluid–particle shear flows

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