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AIChE Journal
Article . 2024 . Peer-reviewed
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Characterizing binary droplet collisions of power‐law fluids

Authors: Arie H. Huijgen; P. M. Durubal; Cristina García Llamas; Kay A. Buist; J. A. M. (Hans) Kuipers; Maike W. Baltussen;

Characterizing binary droplet collisions of power‐law fluids

Abstract

AbstractThis study focuses on the dynamics of two equal‐sized droplets of non‐Newtonian liquids with simulations using the volume of fluid method and the local front reconstruction method. The non‐Newtonian behavior is implement via a power‐law model. The droplet interactions are performed for Weber numbers ranging from 20 to 300 and impact parameters from 0 to 0.6. Both methods produce similar results at low Weber numbers, while the disintegration of the droplets at high Weber numbers occurs via different mechanisms. Our results demonstrate that the boundaries of the collision maps are highly dependent on the power‐law index. Additionally, the diameter of the ring for head‐on collisions is increased with increasing Weber number and decreasing power‐law index, while the critical ligament length in off‐center collisions increases with Weber number and power‐law index.

Country
Netherlands
Keywords

droplet collisions, local front reconstruction method, volume of fluid, direct numerical simulations, power-law fluids

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
hybrid