We present the development of both steady-state and dynamic models for a slurry HDPE process using fundamental chemical engineering principles and advanced software tools, Polymers Plus and Aspen Dynamics. The discussion includes thermodynamic properties, phase equilibrium, reaction kinetics, polymer properties, and other modeling issues. We characterize a Ziegler−Natta catalyst by assuming the existence of multiple catalyst site types and deconvoluting data from gel permeation chromatography to determine the most probable chain-length distributions and relative amounts of polymer produced at each site type. We validate the model using plant data from two large-scale commercial slurry HDPE processes. Significantly, the model contains a single set of kinetic and thermodynamic parameters that accurately predicts the polymer production rate, molecular weight, polydispersity index, and composition for several product grades. We illustrate the utility of the dynamic model by simulating a grade change. Finally, we propose a process retrofit that permits an increase in the HDPE production rate of up to 20% while maintaining the product quality.

This paper describes the development of a comprehensive model for the continuous gas-phase synthesis of polypropylene using stirred-bed reactors. The model considers the important issues of physical property and thermodynamic model selections, polymer properties, catalyst characterization, and reactor residence time, in addition to the traditional Ziegler−Natta polymerization kinetics. Model development involves fundamental chemical engineering principles and advanced software tools, Polymers Plus and Aspen Dynamics. We characterize a Ziegler−Natta catalyst by assuming the existence of multiple catalyst site types. The model contains a single set of kinetic and thermodynamic parameters that accurately predicts the polymer production rate, molecular weight, polydispersity index, and composition for both homopolymer and impact copolymer product grades from a large-scale commercial process. We demonstrate the application of our dynamic model and process control by comparing grade-transition strategies.

A model is developed for hydrolytic copolymerization of caprolactam with hexamethylene diamine (HMD) and adipic acid (ADA) in a batch reactor to produce nylon 6/6,6 copolymer. The reaction mechanism includes hydrolysis of caprolactam and cyclic dimer, polycondensation, polyaddition, transamidation, and ring formation via end biting and back biting. The catalyzing effect of carboxyl groups is accounted for using kinetic parameters from the literature. Model predictions are compared with low‐temperature literature data before simulating reactor conditions of industrial interest. The model predicts a higher degree of polymerization (DP) for nylon 6/6,6 copolymer compared to nylon 6 and 6,6 homopolymers produced using the same reactor conditions. Dynamic changes in concentrations of water, caprolactam, HMD, ADA, and end groups are tracked and used to explain the positive influence of comonomers on reaction rates and DP. Insights gained from this model will form a useful basis to build future models of continuous industrial reactors.

This paper presents a thermodynamically consistent model for the phase equilibrium of water/ caprolactam/nylon-6 mixtures, based on the POLYNRTL (polymer nonrandom two-liquid) activity-coefficient model. Our model predicts phase equilibrium for any binary or ternary mixture containing water, -caprolactam, and nylon-6 at industrially relevant temperatures and pressures with an average error of 1%. This paper also demonstrates its application to simulate a melt train and a bubble-gas kettle train for industrial production of nylon-6. Prior literature makes simplifying assumptions about liquid-phase (molten polymer) activities of water and -caprolactam; these assumptions are shown to be unrealistic.

This paper presents methodologies to quantify the relationships among the molecular weight distribution (MWD), steady-shear non-Newtonian viscosity (i.e., flow curve), and melt index (MI) of three linear low-density polyethylenes manufactured using the same technology. With the aid of computer-aided process simulation tools (such as POLYMERS PLUS), polymer producers can predict accurately the MWD from manufacturing conditions. Our methodologies help the polymer producers to extend their simulation model to predict flow curves and MI from the MWD. To do this, this paper employs (1) a modified Carreau-Yasuda (CY) model or Bersted's partition model to relate the MWDs and flow curves, (2) Bremner and Rudin's model to relate the weight-average molecular weight (MWW) and MI, and (3) Rohlfing and Janzen's model to relate the flow curve and MI. We show that the Carreau-Yasuda, Bersted, and Bremner and Rudin models work very well for correlating our data, predicting flow curves that average 3-7% error and MI values that average 2% error. In addition, for the case in which we lack MI data, we use the CY or Bersted model predictions of the flow curve to generate MI values through Rohlfing and Janzen's model. These predictions are very good, averaging only 0.5-3% error. We also show how to use the CY or Bersted model and Rohlfing and Janzen's melt-indexer model to estimate closely the low shear rate region of the flow curve using MWD/MI data alone. This case corresponds to one in which we lack flow curve data. Last, we provide practical guidelines for polymer manufacturers who want to predict the flow curve and MI using the MWD.