Graduation Year

2009

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Computer Science and Engineering

Major Professor

Dmitry B. Goldgof, Ph.D.

Committee Member

Sudeep Sarkar, Ph.D.

Committee Member

Grigori Sisoev, Ph.D.

Committee Member

Aydin Sunol, Ph.D.

Keywords

image processing, fluid-flow tracking, wave detection, wave velocity, wave inclination, mathematical modeling

Abstract

The flow of a liquid film over a rapidly rotating horizontal disk has numerous industrial applications including pharmaceuticals, chemical engineering, bioengineering, etc. The analysis and control of complex fluid flows over a rapidly rotating horizontal disk is an important issue in the experimental fluid mechanics. The spinning disk reactor exploits the benefits of centrifugal force, which produces thin highly sheared films due to radial acceleration. The hydrodynamics of the film results in excellent fluid mixing and high heat or mass transfer rates.

This work focuses on developing a novel approach for fluid flow tracking and analysis. Specifically, the developed algorithm is able to detect the moving waves and compute controlling film flow parameters for the fluid flowing over a rotating disk. The input to this algorithm is an easily acquired non-invasive video data. It is shown that under single light illumination it is possible to track specular portion of the reflected light on the moving wave. Hence, the fluid wave motion can be tracked and fluid flow parameters can be computed. The fluid flow parameters include wave velocities, wave inclination angles, and distances between consecutive waves. Once the parameters are computed, their accuracy is analyzed and compared with the solutions of the mathematical fluid dynamics models based on the Navier-Stokes equations for the case of a thin film. The fluid model predicts wave characteristics based on directly measured controlling parameters, such as disk rotation speed and fluid flow rate. It is shown that the calculated parameter values approximately coincide with the predicted ones. The average computed parameters were within 5 − 10% of the predicted values.

In addition, given recovered fluid characteristics and fluid flow controlling parameters, full 3D wave description is obtained. That includes 3D wave location, speed, and distance between waves, as well as approximate wave thickness.

Next, the developed approach is generalized to model-based recovery of fluid flow controlling parameters: the speed of the spinning disk and the initial fluid-flow rate. The search in space for model parameters is performed as to minimize the error between the flow characteristics predicted by the fluid dynamics model (e.g. distance between waves, wave inclination angles) and parameters recovered from video data. Results demonstrate that the speed of a disk and the flow rate are recovered with high accuracy. When compared to the ground truth available from direct observation, we noted that the controlling parameters were estimated with less than 10% error.

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