Abstract
This project implements a dynamic alumina hydrate continuous precipitation and classification model in an alumina refining operation to allow the forecasting of a number of relevant process parameters, such as the particle size distribution of solids across the system and the process productivity, or yield, using a PC. The model uses basic conservation principles and techniques for particle kinetics including simulating particle growth, collision and agglomeration, and nucleation, or the formation of new growth centers, in precipitation vessels with the Advanced Computer Simulation Language development package to calculate stream compositions and solid size distributions throughout the precipitation unit. The model also predicts settling characteristics for a series of gravity classifiers and updates recycled seed properties during simulation. This tool permits engineers to make educated process changes by being able to predict results of changes in operations before transferring the alterations to the actual plant. This simulator allows for the quantitative analysis of the precipitation and classification system including the determination of particle sizes and yields by numerically integrating the unsteady state balance equations for each vessel. This model was tuned for use at Alcoa's Point Comfort Operations for regular smelting grade alumina production but provisions were included in the model for adaptation to other facilities. The model's input and output interfaces have been developed using a graphical user interface to provide a more user friendly tool. The interface also allows engineers to view values as they might appear in lab analyses. This model also includes useful analysis tools such as a head tank specific precipitation rate controller and a perfect product removal scheme for calculating ideal operating parameters. A variety of test simulations were also run on the model to determine the qualitative and quantitative accuracy of the model to the actual process. The resulting model is currently in use by Alcoa's Point Comfort Operations' staff.
Kapraun, Christopher Michael (1996). A predictive model for particle size distribution and yield for Bayer precipitation and classification. Master's thesis, Texas A&M University. Available electronically from
https : / /hdl .handle .net /1969 .1 /ETD -TAMU -1996 -THESIS -K36.