Projects per year
Abstract
The propagation of hydrothermal waves in a differentially heated shallow open cavity filled with a complex fluid (a mixture of an oil with solid spherical metallic particles) is investigated in the framework of a hybrid numerical two-way coupled Eulerian–Lagrangian methodology. We explore the response of this system to the solid mass fraction (mass load) and the particle size (Stokes number). The results show that particles and related (inertial and drag) effects can cause appreciable modifications in the properties of the wave, leading to a shrinkage of its velocity of propagation. Interesting dynamics can also be seen in terms of particle patterning behavior as the Stokes number is increased. Due to the joint action that distinct traveling rolls exert on the dispersed solid mass, related accumulation loops induced by centrifugal effects are progressively distorted and finally broken. Particles simply tend to cluster (as time increases) along the lower periphery of the main Marangoni circulation and, as a result of this mechanism and the different velocities of the return flow and the hydrothermal disturbance, a wavy boundary is formed, which separates the upper particle-rich area from a relatively depleted region next to the bottom wall.
Original language | English |
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Article number | 215 |
Number of pages | 19 |
Journal | Fluids |
Volume | 7 |
Issue number | 7 |
DOIs | |
Publication status | Published - 23 Jun 2022 |
Keywords
- Marangoni convection
- hydrothermal wave
- solid particles
- patterning behavior
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- 1 Finished
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The ESA/JAXA JEREMI (Japanese European Research Experiments on Marangoni Instabilities) - Project
Lappa, M. (Principal Investigator)
EPSRC (Engineering and Physical Sciences Research Council)
10/12/18 → 9/12/20
Project: Research
Datasets
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Supplementary material for: ”On the propagation of hydrothermal waves in a fluid layer with two-way coupled dispersed solid particles”
Lappa, M. (Creator), University of Strathclyde, 27 Jun 2022
DOI: 10.15129/9f4d022e-dfd8-4d58-a2ec-72c322803598
Dataset