Predictive Modeling of Metal-Catalyzed Polyolefin Processes

This dissertation describes the essential modeling components and techniques for building comprehensive polymer process models for metal-catalyzed polyolefin processes. The significance of this work is that it presents a comprehensive approach to polymer process modeling applied to large-scale commercial processes. Most researchers focus only on polymerization mechanisms and reaction kinetics, and neglect physical properties and phase equilibrium. Both physical properties and phase equilibrium play key roles in the accuracy and robustness of a model.

This work presents the fundamental principles and practical guidelines used to develop and validate both steady-state and dynamic simulation models for two large-scale commercial processes involving the Ziegler-Natta polymerization to produce high-density polyethylene (HDPE) and polypropylene (PP). It also provides a model for the solution polymerization of ethylene using a metallocene catalyst. Existing modeling efforts do not include physical properties or phase equilibrium in their calculations. These omissions undermine the accuracy and predictive power of the models.

The forward chapters of the dissertation discuss the fundamental concepts we consider in polymer process modeling. These include physical and thermodynamic properties, phase equilibrium, and polymerization kinetics. The later chapters provide the modeling applications described above.