Advances in Mathematical Modeling of Gas-Phase Olefin Polymerization

Mathematical modeling of olefin polymerization processes has advanced significantly, driven by factors such as the need for higher-quality end products and more environmentally-friendly processes. The modeling studies have had a wide scope, from reactant and catalyst characterization and polymer synthesis to model validation with plant data. This article reviews mathematical models developed for olefin polymerization processes. Coordination and free-radical mechanisms occurring in different types of reactors, such as fluidized bed reactor (FBR), horizontal-stirred-bed reactor (HSBR), vertical-stirred-bed reactor (VSBR), and tubular reactor are reviewed. A guideline for the development of mathematical models of gas-phase olefin polymerization processes is presented

Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation

YesPolypropylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75 °C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR)

Dynamic modeling and Molecular Weight Distribution of ethylene copolymerization in an industrial gas-phase Fluidized-Bed Reactor

A dynamic model for ethylene copolymerization in an industrial Fluidized-Bed Reactor (FBR) is developed to describe its behavior and calculate the properties of polyethylene. The presented model considers particle entrainment and polymerization reaction in two phases. Two-site kinetic and hydrodynamic models in combination, provide a comprehensive model for the gas phase fluidized-bed polyethylene production reactor. The governing moment and hydrodynamic differential equations were solved simultaneously and the results compared with a similar work, as well as industrial data. The dynamic model showed accurate results for predicting Polydispersity Index (PDI), Molecular Weight Distribution (MWD), reactor temperature and polymer production rate

Dynamic modeling and Molecular Weight Distribution of ethylene copolymerization in an industrial gas-phase Fluidized-Bed Reactor

A dynamic model for ethylene copolymerization in an industrial Fluidized-Bed Reactor (FBR) is developed to describe its behavior and calculate the properties of polyethylene. The presented model considers particle entrainment and polymerization reaction in two phases. Two-site kinetic and hydrodynamic models in combination, provide a comprehensive model for the gas phase fluidized-bed polyethylene production reactor. The governing moment and hydrodynamic differential equations were solved simultaneously and the results compared with a similar work, as well as industrial data. The dynamic model showed accurate results for predicting Polydispersity Index (PDI), Molecular Weight Distribution (MWD), reactor temperature and polymer production rate

Dynamic process modeling and hybrid intelligent control of ethylene copolymerization in gas phase catalytic fluidized bed reactors

BACKGROUND: Polyethylene (PE) is the most extensively consumed plastic in the world, and gas phase‐based processes are widely used for its production owing to their flexibility. The sole type of reactor that can produce PE in the gas phase is the fluidized bed reactor (FBR), and effective modeling and control of FBRs are of great importance for design, scale‐up and simulation studies. This paper discusses these issues and suggests a novel advanced control structure for these systems. RESULTS: A unified process modeling and control approach is introduced for ethylene copolymerization in FBRs. The results show that our previously developed two‐phase model is well confirmed using real industrial data and is exact enough to further develop different control strategies. It is also shown that, owing to high system nonlinearities, conventional controllers are not suitable for this system, so advanced controllers are needed. Melt flow index (MFI) and reactor temperature are chosen as vital variables, and intelligent controllers were able to sufficiently control them. Performance indicators show that advanced controllers have a superior performance in comparison with conventional controllers. CONCLUSION: Based on control performance indicators, the adaptive neuro‐fuzzy inference system (ANFIS) controller for MFI control and the hybrid ANFIS–proportional‐integral‐differential (PID) controller for temperature control perform better regarding disturbance rejection and setpoint tracking in comparison with conventional controllers. © 2019 Society of Chemical Industr

Different hydrodynamic model for gas-phase propylene polymemation in a catalytic fluidized bed reactor

A comparative simulation study was carried out using the improved well-mixed, constant bubble size and well mixed models. These fluidized bed reactor models, combined with comprehensive kinetics for propylene homo-polymerization in the presence of a multiple active site Ziegler-Natta catalyst. In the improved model, the effect of the presence of particles in the bubbles and the excess gas in the emulsion phase was taken into account to improve the quantitative understanding of the actual fluidized bed process. The superficial gas velocity and catalyst feed rate have a strong effect on the hydrodynamics and reaction rate, which results in a greater variation in the polymer production rate and reactor temperature. At typical operating conditions the improved well mixed and well mixed models were in good agreement. While the COO!ICU bubble size model was found to over-predict the emulsion phase temperature and underpredict propylene concentration

Developed Hybrid Model for Propylene Polymerisation at Optimum Reaction Conditions

YesA statistical model combined with CFD (computational fluid dynamic) method was used to explain the detailed phenomena of the process parameters, and a series of experiments were carried out for propylene polymerisation by varying the feed gas composition, reaction initiation temperature, and system pressure, in a fluidised bed catalytic reactor. The propylene polymerisation rate per pass was considered the response to the analysis. Response surface methodology (RSM), with a full factorial central composite experimental design, was applied to develop the model. In this study, analysis of variance (ANOVA) indicated an acceptable value for the coefficient of determination and a suitable estimation of a second-order regression model. For better justification, results were also described through a three-dimensional (3D) response surface and a related two-dimensional (2D) contour plot. These 3D and 2D response analyses provided significant and easy to understand findings on the effect of all the considered process variables on expected findings. To diagnose the model adequacy, the mathematical relationship between the process variables and the extent of polymer conversion was established through the combination of CFD with statistical tools. All the tests showed that the model is an excellent fit with the experimental validation. The maximum extent of polymer conversion per pass was 5.98% at the set time period and with consistent catalyst and co-catalyst feed rates. The optimum conditions for maximum polymerisation was found at reaction temperature (RT) 75 °C, system pressure (SP) 25 bar, and 75% monomer concentration (MC). The hydrogen percentage was kept fixed at all times. The coefficient of correlation for reaction temperature, system pressure, and monomer concentration ratio, was found to be 0.932. Thus, the experimental results and model predicted values were a reliable fit at optimum process conditions. Detailed and adaptable CFD results were capable of giving a clear idea of the bed dynamics at optimum process conditions

Polypropylene

Polypropylene (PP) is one of the most important thermoplastics widely applied in the fields of automobile, packaging, clothing, and plastic molding. Since J. Paul Hogan and Robert L. Banks accidentally synthesized crystalline PP in 1951, tremendous breakthroughs have been achieved and have successfully transferred PP from a discovery in the laboratory to an indispensable commodity. Along with the commercial success, progress in the “academic community” of PP has expanded our toolbox to tailor tactility and microstructure, improve thermal and mechanical properties, understand and control crystallization behavior, develop efficient functionalization strategies, and explore novel applications. This book provides an overview of progress in PP from the perspectives of synthesis, structure–property relationship, processing, PP composites, and applications

Kinetic Intersections as a Source of Information on Rate Coefficients

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Hydrogen effect modeling on Ziegler-Natta catalyst and final product properties in propylene polymerization

Hydrogen, as chain transfer agent, effects on kinetic of propylene polymerization; consequently variation of hydrogen concentration leads to change final product properties and also activates site of used catalyst. This phenomenon is one of the most important process variables is to adjust the final product properties and optimize the operating conditions. This work has attempted to present a mathematical model that cable to calculate the most important indices of end used product, such as melt flow index, number and weight average molecular weight and poly dispersity index. The model can predict profile polymerization rates determining important kinetic parameters such as the activation energy, lumped deactivation reaction initial reaction rate and deactivation constant. The mathematical model was implemented in Matlab/Simulink environment for slurry polymerization in laboratory scale. The modeling approach is based on polymer moment balance method in the slurry semi-batch reactor. In addition, in this work have provided a model that calculating fraction activated sites catalyst via hydrogen concentration. The model was validated by experimental data from lab scale, reactor. The experimental and model outputs were compared; consequently, the errors were within acceptable range.               KEY WORDS: Mathematical modeling, Propylene polymerization, Kinetics study, Hydrogen response, population balance Bull. Chem. Soc. Ethiop. 2018, 32(2), 371-386.DOI: https://dx.doi.org/10.4314/bcse.v32i2.1