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Effects of spontaneous nanoparticle adsorption on the bubble-liquid and bubble-bubble interactions in multi-dispersed bubbly systems - A review

journal contribution
posted on 2024-11-02, 06:58 authored by Yang Yuan, Xiangdong Li, Jiyuan TuJiyuan Tu
Robust predictive models of dynamic bubbly systems of nanoparticle-liquid mixtures are vital to the design and assessment of relevant industrial systems. Previous attempts to model bubbly flows of dilute nanofluids using the classic two-phase flow models were unsuccessful although the apparent hydrodynamic properties of the dilute nanoparticle-liquid mixtures were only negligibly different to those of their pure base liquids. Emerging studies demonstrated that when bubbles exist in the mixture, nanoparticles tend to spontaneously aggregate at the bubble interface, forming a layer of "colloidal armour" and making the bubble interface partially rigid and less mobile. The colloidal armour also significantly modifies the characteristics of the bubble-liquid and bubble-bubble interactions. Therefore, it was proposed that the key job when developing a predictive model based on classic two-phase flow models is to re-formulate the bubble-liquid and bubble-bubble interactions. However, the adsorption of nanoparticles in dynamic bubbly systems has rarely been studied. The lack of mechanistic understanding has severely hindered the model development. Therefore, this study reviews the common findings yielded from experimental and numerical investigations reported in literature, with the aim to clarify the critical points to address when modelling bubbly flows containing nanoparticles using the classic two-fluid and MUSIG models.

Funding

Fundamental investigation of heat and mass transfer in nanofluids: a mechanistic approach

Australian Research Council

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    ISSN - Is published in 00179310

Journal

International Journal of Heat and Mass Transfer

Volume

120

Start page

552

End page

567

Total pages

16

Publisher

Elsevier

Place published

United Kingdom

Language

English

Copyright

© 2017 Elsevier Ltd. All rights reserved

Former Identifier

2006082405

Esploro creation date

2020-06-22

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