An experimental study of droplet impact on solid surfaces

The study of fluid spreading dynamics has been playing an important role in many technological and industrial applications, e.g., in the pesticide industries. In this project, the objective is to study the spreading dynamics of impacting fluid droplets on a solid surface. Fluids of varying surface t...

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Bibliographic Details
Main Author: Muhammad Hafiz Baharudin
Other Authors: Tran Anh Tuan
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/64938
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Institution: Nanyang Technological University
Language: English
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Summary:The study of fluid spreading dynamics has been playing an important role in many technological and industrial applications, e.g., in the pesticide industries. In this project, the objective is to study the spreading dynamics of impacting fluid droplets on a solid surface. Fluids of varying surface tension and kinematic viscosity were used in this project. The fluids were then made to impact a solid surface with velocity in the range (0.98 - 4ms^(-1)). This was achieved by changing the releasing heights of the droplets. The spreading process was found to be dependent on both the fluid’s surface tension and viscosity. In general, as the surface tension and viscosity of the fluids increased, the resistance to spreading is high and it requires a longer time to reach equilibrium. In this study, a spread factor, D_max/D_0,was defined. For the capillary regime (non-viscous), the spread factor scaled with We^(1/4), as with previous studies. For the viscous regime, the spread factor scaled with Re1/5. For a more general spreading model, an impact number P = We/Re4/5 was defined (momentum-conversion) following the study reported by Clanet [20]. Using this model, we could distinguish quite clearly the transition between the two regimes at which transition occurs at P=1. The data plots however did not collapse onto a single scaling line. Using the energy-conversion model, P = We/Re2/5 is defined. Using this model, it was found that the data collapsed onto a single scaling curve.