A numerical model for the development of the morphology of disperse blends in complex flow

Wong, Wing-Hin B.; Hulsen, Martien A.; Anderson, Patrick Patrick

doi:10.1007/s00397-018-01126-8

Cited by 6 publications

(23 citation statements)

References 38 publications

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“…Consequently, this may lead to negative values for R 0 and β, which is unphysical and makes the numerical simulations stop. We found that using the logarithmic variables v = log(R 0 ) and s = log(β) in the model and find R 0 and β by exponentiation, improved that stability of the model substantially (Wong et al 2019). With the logarithmic variables, the partial differential equations become:…”

Section: Recap Of the Previous Modelmentioning

confidence: 99%

“…In this section, we begin by summarizing the features of our previous blend morphology model (Wong et al 2019). This is followed by three extensions to our original model.…”

Section: Morphology Modelmentioning

confidence: 99%

“…where μ d is the viscosity of the droplet phase. In Wong et al (2019), we took four morphological states into account, namely: coalescence, necking, filament stretching and dynamic filament breakup.…”

Section: Recap Of the Previous Modelmentioning

confidence: 99%

“…Development of a model to describe the morphology of immiscible Newtonian blends undergoing morphological changes from the initial structure to the final structure after deformation, breakup and coalescence has been done by Peters et al (2001) and Almusallam et al (2004). Based on Peters et al (2001), Wong et al (2019) have developed a numerical model to simulate the monodisperse blend morphology development in complex flow geometries.…”

Section: Introductionmentioning

confidence: 99%

“…For the material properties of the solidified polymer blend, it is not only important to know the droplet size, but also the droplet size distribution (polydispersity) (Wu 1988;Premphet and Paecharoenchai 2002;Caserta et al 2004;Diop and Torkelson 2015). The objective of this study is to describe the development of polydisperse droplet size distributions in complex flow geometries using the work from Wong et al (2019). We first introduce a number of extensions to this model and then use the extended model to investigate the shear rate dependence of the polydispersity in simple shear flow and the formation of distinct layers in Poiseuille flow.…”

Section: Introductionmentioning

confidence: 99%

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Numerical simulations of the polydisperse droplet size distribution of disperse blends in complex flow

et al. 2021

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The blend morphology model developed by Wong et al. (Rheologica Acta, 2019), based on Peters et al. (J Rheol 45(3):659–689, 2001), is used to investigate the development of the polydispersity of the disperse polymer blend morphology in complex flow. First, the model is extended with additional morphological states. The extended model is tested for simple shear flow, where it is found that the droplet size distribution does not simply scale with the shear rate, because this scaling does not hold for coalescing droplets. Subsequently, the model is applied to Poiseuille flow, showing formation of distinct layers, which occurs in realistic pressure-driven flows. Finally, the model is applied on an eccentric cylinder flow, where histograms are made of the average droplet size throughout the domain. It is observed that outer cylinder rotation results in narrow distributions where the small droplets are relatively large, whereas inner cylinder rotation results in broad distributions where the small droplets are significantly smaller than in the case of outer cylinder rotation. Eccentricity seems to only have a minor effect if the maximum shear rate is held constant. The flow profile and history in combination with the maximum shear rate strongly determine how the polydisperse droplet size distribution develops.

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Section: Recap Of the Previous Modelmentioning

confidence: 99%

“…In this section, we begin by summarizing the features of our previous blend morphology model (Wong et al 2019). This is followed by three extensions to our original model.…”

Section: Morphology Modelmentioning

confidence: 99%

Section: Recap Of the Previous Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical simulations of the polydisperse droplet size distribution of disperse blends in complex flow

et al. 2021

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Numerical Modeling of the Blend Morphology Evolution in Twin‐Screw Extruders

Wong

Bie

Hulsen

et al. 2022

Macro Theory & Simulations

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The blend morphology model developed by Wong et al., based on Peters et al., is used to investigate the development of the disperse polymer blend morphology in twin-screw extruder flow. First, the model is written in a point-wise form suitable for using in conjunction with particle tracking. Particle tracking methods are used to generate trajectories along the flow field. Macroscopic droplet populations are placed along these trajectories and the velocity gradient tensor is extracted and applied on the point-wise blend morphology model. Very large morphology differences arise between trajectories that pass through the middle gap and those that do not. In the global distribution of (macroscopically averaged, monodisperse) droplet sizes, two distinct peaks appear due to these different trajectories. Given enough number of screw rotations, a droplet population can reach almost every position in the twin-screw extruder and travel along both types of particle trajectories. The effect of varying the gap size is that the largest droplets are unaffected, but the smallest droplets are smaller for a smaller gap size due to the higher maximum shear rate. The effect of varying the viscosity ratio on the global droplet size distribution is found to be nonlinear and is strongly determined by the Grace curve. The effect on polydisperse droplet populations is found to be that trajectories that do not pass through the gap evolve toward a single peak, whereas trajectories that do pass through the gap lead to a split into two peaks that ultimately rejoin as one peak. It is concluded that the initial position of a population in the twin-screw extruder has a very large effect on the developing transient blend morphology, though future work should be done on the importance of the initial position on the steady-state blend morphology after a very large number of screw rotations.

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Numerical Modeling of the Blend Morphology Evolution in Twin‐Screw Extruders

Wong¹,

Bie²,

Hulsen³

et al. 2022

Macro Theory & Simulations

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A numerical model for the development of the morphology of disperse blends in complex flow

Cited by 6 publications

References 38 publications

Numerical simulations of the polydisperse droplet size distribution of disperse blends in complex flow

Numerical simulations of the polydisperse droplet size distribution of disperse blends in complex flow

Numerical Modeling of the Blend Morphology Evolution in Twin‐Screw Extruders

Numerical Modeling of the Blend Morphology Evolution in Twin‐Screw Extruders

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