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Title: Dynamics of thin liquid films over a spinning disk
Author: Zhao, Kun
ISNI:       0000 0004 9357 1899
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2020
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Thin film dynamics over spinning disks is of central importance to a number of scientific research and industrial applications, such as heat/mass transfer, chemical reactions and chip devices. Although they have received a lot of attention in different applications, the key un- derlying dynamics governing the flow are not thoroughly understood, especially in terms of highly non-linear behaviour in free surface flows, in the presence of other physical forces or chemical reactions. The elucidation of the underlying mechanisms driving the flow is of utmost importance to both scientific research and industrial applications. In this research the dynamics of a thin film flowing over a rapidly spinning, horizontal disk, in presence of first-order chemical reactions is considered. A set of non-axisymmetric evolution equations for the film thickness, radial and azimuthal flow rates is derived using a boundary- layer (IBL) approximation in conjunction with the Karman-Polhausen approximation for the velocity distribution in the film. Numerical solutions of these highly nonlinear partial dif- ferential equations are obtained from finite difference scheme which reveals the formation of large-amplitude waves that travel from the disk inlet to its periphery. The equations with non- axisymmetric condition were investigated where elimination of azimuthal dependence presents different wave regimes across the disk radius, and three dimensional wave structures over the entire disk. Apart from hydrodynamics, the influence of these waves on the concentration and temperature profiles is analysed for a wide range of system parameters. It is shown that these waves lead to significant enhancement of the rates of heat and mass transfer, as well as chemical reaction due to the mixing associated with the flow. Additionally, due to the time-consuming implementation of the IBL model, the Neural Network (NN) technique is applied based on existing Finite Difference (FD) results, in order to predict the wave dynamics after initial times. The NN is trained on a dataset from various data points in space and time from IBL model, and then used to simulate the evolution of any wave characteristics of interest. Overall, the resulting NN model predicts the evolution of waves reasonably well when compared with the time-consuming finite difference scheme, and reduces the computation time significantly.
Supervisor: Matar, Omar Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral