Graduation Year


Document Type




Degree Granting Department

Computer Science and Engineering

Major Professor

Dmitry B. Goldgof, Ph.D.

Co-Major Professor

Sudeep Sarkar, Ph.D.

Committee Member

Grigori Sisoev, Ph.D.

Committee Member

Aydin Sunol, Ph.D.


image processing, uid- ow tracking, wave detection, wave velocity, wave inclination, mathematical modeling


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

This work focuses on developing a novel approach for uid ow tracking and analysis. Speci_cally, the developed algorithm is able to detect the moving waves and compute controlling _lm ow parameters for the uid owing 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 reected light on the moving wave. Hence, the uid wave motion can be tracked and uid ow parameters can be computed. The uid ow 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 uid dynamics models based on the Navier-Stokes equations for the case of a thin _lm. The uid model predicts wave characteristics based on directly measured controlling parameters, such as disk rotation speed and uid ow 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 uid characteristics and uid ow 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 uid ow controlling parameters: the speed of the spinning disk and the initial uid-ow rate. The search in space for model parameters is performed as to minimize the error between the ow characteristics predicted by the uid 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 ow 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.