| Autor: |
Singh RK; Department of Mechanical Engineering, Indian Institute of Technology (ISM), Dhanbad 826 004, India., Mahato LK; Department of Mechanical Engineering, Indian Institute of Technology (ISM), Dhanbad 826 004, India., Mandal DK; Department of Mechanical Engineering, Indian Institute of Technology (ISM), Dhanbad 826 004, India. |
| Jazyk: |
angličtina |
| Zdroj: |
Langmuir : the ACS journal of surfaces and colloids [Langmuir] 2021 Aug 10; Vol. 37 (31), pp. 9504-9517. Date of Electronic Publication: 2021 Jul 28. |
| DOI: |
10.1021/acs.langmuir.1c01367 |
| Abstrakt: |
The role of liquid viscosity on the spreading for an airflow-assisted impact of drops on a surface is investigated. The spreading diameter is found to increase with the Reynolds number of the airflow ( Re air ) for a given viscosity and impact Weber number ( We ) compared to the still air. The increment is higher at a low We for viscous drops, whereas the effect of Re air dominates at the intermediate We as the viscosity decreases. Two extra forces, the normal imposed pressure and shear force of air, act on the drop and influence the spreading along with the viscous dissipation. The drop's curvature decreases depending on the viscosity and impact velocity while spreading. Large-scale eddies near the drop-surface region are observed due to the separation of the incident airflow. The formation of eddies signifies low-pressure zones, which extract the trapped air, causing the spreading diameter of the viscous drop to increase at a low We . With the increase in the We , the lamella thickness of low-viscosity drops decreases and is pushed out by the air shear causing the spreading factor to increase. The boundary layer thickness is estimated using the energy balance method to predict the maximum spreading factor. The prediction compares well with the experimental one for higher viscosities. The accuracy improves when the effect of low pressure is incorporated. To confirm, the experimental spreading is compared with that obtained from three existing models, and one, which considers the influence, is observed to provide a better prediction. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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