Modelling and Simulation of High Pressure Industrial Autoclave Polyethylene Reactor



Similar documents
Modeling and simulation of high-pressure industrial autoclave polyethylene reactor

Simulation and Nonlinear Analysis of the Stagnant Polymer Layer in a LDPE Tubular Reactor

Dynamic Process Modeling. Process Dynamics and Control

Introduction to the course Chemical Reaction Engineering I

The Material Balance for Chemical Reactors. Copyright c 2016 by Nob Hill Publishing, LLC

Lecture 3 Fluid Dynamics and Balance Equa6ons for Reac6ng Flows

AN EFFECT OF GRID QUALITY ON THE RESULTS OF NUMERICAL SIMULATIONS OF THE FLUID FLOW FIELD IN AN AGITATED VESSEL

STEADY STATE MODELING AND SIMULATION OF HYDROCRACKING REACTOR

Mixing in the process industry: Chemicals Food Pharmaceuticals Paper Polymers Minerals Environmental. Chemical Industry:

k 2f, k 2r C 2 H 5 + H C 2 H 6

HEAT UNIT 1.1 KINETIC THEORY OF GASES Introduction Postulates of Kinetic Theory of Gases

STUDY OF MIXING BEHAVIOR OF CSTR USING CFD

Chapter 12 IVP Practice Problems

Problem Set 4 Solutions

Molar Mass of Polyvinyl Alcohol by Viscosity

Heat Transfer and Energy

Compressible Fluids. Faith A. Morrison Associate Professor of Chemical Engineering Michigan Technological University November 4, 2004

Design of heat exchangers

CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER

Dynamic Models Towards Operator and Engineer Training: Virtual Environment

The Age of Computer Aided Modeling

Numerical Analysis of the Resin Transfer Molding Process via PAM- RTM Software

ADVANCED COMPUTATIONAL TOOLS FOR EDUCATION IN CHEMICAL AND BIOMEDICAL ENGINEERING ANALYSIS

Exergy Analysis of a Water Heat Storage Tank

Decaffeination of Raw, Green Coffee Beans Using Supercritical CO 2

ChE 344 Chemical Reaction Engineering Winter 1999 Exam I Part 1 (80%) Solution

Polymers: Introduction

PROCESS DESIGN AND CONTROL. Consistent Inventory Control. Elvira Marie B. Aske and Sigurd Skogestad*

CFD modelling of continuous precipitation of barium sulphate in a stirred tank

Saeid Rahimi. Effect of Different Parameters on Depressuring Calculation Results. 01-Nov Introduction. Depressuring parameters

Theory of turbo machinery / Turbomaskinernas teori. Chapter 4

CBE 6333, R. Levicky 1 Differential Balance Equations

1. Fluids Mechanics and Fluid Properties. 1.1 Objectives of this section. 1.2 Fluids

Heat Exchangers - Introduction

Gas Laws. The kinetic theory of matter states that particles which make up all types of matter are in constant motion.

Application of Artificial Intelligence Techniques for Temperature Prediction in a Polymerization Process

Chapter 28 Fluid Dynamics

Determination of Thermal Conductivity of Coarse and Fine Sand Soils

Effect of Aspect Ratio on Laminar Natural Convection in Partially Heated Enclosure

Heating & Cooling in Molecular Clouds

4. Introduction to Heat & Mass Transfer

5.2. Vaporizers - Types and Usage

ENERGY TRANSFER SYSTEMS AND THEIR DYNAMIC ANALYSIS

High Flux Steam Reforming

Energy Transport. Focus on heat transfer. Heat Transfer Mechanisms: Conduction Radiation Convection (mass movement of fluids)

Production of R-134a

Review - After School Matter Name: Review - After School Matter Tuesday, April 29, 2008

Laminar Flow and Heat Transfer of Herschel-Bulkley Fluids in a Rectangular Duct; Finite-Element Analysis

The Effect Of Implementing Thermally Coupled Distillation Sequences On Snowball Effects For Reaction-Separation-Recycle Systems

Define the notations you are using properly. Present your arguments in details. Good luck!

Thermodynamics - Example Problems Problems and Solutions

A subgrid-scale model for the scalar dissipation rate in nonpremixed combustion

Water hammering in fire fighting installation

Design, Simulation and Optimization of Polymerization Processes Using Advanced Open Architecture Software Tools

cmn_lecture.2 CAD OF DOUBLE PIPE HEAT EXCHANGERS

Turbulent Mixing and Chemical Reaction in Stirred Tanks

Module 1 : Conduction. Lecture 5 : 1D conduction example problems. 2D conduction

Basic Equations, Boundary Conditions and Dimensionless Parameters

At the moment no alternative polymers with comparable characteristics are available.

Vacuum Technology. Kinetic Theory of Gas. Dr. Philip D. Rack

Temperature. Number of moles. Constant Terms. Pressure. Answers Additional Questions 12.1

ME6130 An introduction to CFD 1-1

Lecture 6 - Boundary Conditions. Applied Computational Fluid Dynamics

= 800 kg/m 3 (note that old units cancel out) J 1000 g = 4184 J/kg o C

CHAPTER 7 THE SECOND LAW OF THERMODYNAMICS. Blank

Chapter 8 Maxwell relations and measurable properties

Notes on Polymer Rheology Outline

Technical Thermodynamics

Problem Set MIT Professor Gerbrand Ceder Fall 2003

CO MPa (abs) 20 C

Continuous Preferential Crystallization in Two Coupled Crystallizers

Experiment 5: Phase diagram for a three-component system (Dated: April 12, 2010)

INLET AND EXAUST NOZZLES Chap. 10 AIAA AIRCRAFT ENGINE DESIGN R01-07/11/2011

High Speed Aerodynamics Prof. K. P. Sinhamahapatra Department of Aerospace Engineering Indian Institute of Technology, Kharagpur

39th International Physics Olympiad - Hanoi - Vietnam Theoretical Problem No. 3

Mean Field Flory Huggins Lattice Theory

Lecture 5 Hemodynamics. Description of fluid flow. The equation of continuity

RESEARCH PROJECTS. For more information about our research projects please contact us at:

Fundamentals of Plasma Physics Waves in plasmas

C. starting positive displacement pumps with the discharge valve closed.

Boyles Law. At constant temperature the volume occupied by a fixed amount of gas is inversely proportional to the pressure on the gas 1 P = P

- momentum conservation equation ρ = ρf. These are equivalent to four scalar equations with four unknowns: - pressure p - velocity components

CHAPTER 12. Gases and the Kinetic-Molecular Theory

TABLE OF CONTENT

A drop forms when liquid is forced out of a small tube. The shape of the drop is determined by a balance of pressure, gravity, and surface tension

PERFORMANCE EVALUATION OF A MICRO GAS TURBINE BASED ON AUTOMOTIVE TURBOCHARGER FUELLED WITH LPG

THERMAL STRATIFICATION IN A HOT WATER TANK ESTABLISHED BY HEAT LOSS FROM THE TANK

CFD SIMULATION OF IPR-R1 TRIGA SUBCHANNELS FLUID FLOW

Heat transfer efficiency improvement in high-pressure metal hydride by modeling approach

Solution for Homework #1

Second Order Systems

Introduction. Chapter The Motivation

O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt,

CHEMISTRY. Matter and Change. Section 13.1 Section 13.2 Section The Gas Laws The Ideal Gas Law Gas Stoichiometry

PROCESS CONTROL SYSTEM DESIGN Process Control System Design. LECTURE 6: SIMO and MISO CONTROL

Natural Convection in Stratified Hot Water Storage Tanks

Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology

Transcription:

Modelling and Simulation of High Pressure Industrial Autoclave Polyethylene Reactor Érico Caliani 1, Marcello Cavalcanti 2, Fabiano A.N. Fernandes 3, Liliane M.F. Lona 1 1 Universidade Estadual de Campinas, Faculdade de Engenharia Química, Caixa Postal 6066, Campinas SP, Brazil 2 Politeno Indústria e Comércio S/A, Camaçari BA, Brazil 3 Universidade Federal do Ceará, Departamento de Engenharia Química, Campus do Pici, Bloco 709, 60455-760 Fortaleza CE, Brazil High-pressure technology for polyethylene production has been widely used by industries around the world. A good model for the reactor fluid dynamics is essential to properly set the operating conditions of the autoclave reactor. The high-pressure autoclave reactor model developed in this work is based on a non-isothermal dynamic model, where PID control equations are used to maintain the operation at the unstable steady state. Kinetic mechanisms to describe the polymerization rate and molecular weight averages are presented. The model is capable of computing temperature, concentration gradients and polymer characteristics. The model was validated using industrial data, presenting good representation of the behavior of the autoclave reactor used in ethylene homopolymerization. 1. Introduction Low density polyethylenes are used in a large variety of applications. Generally they are produced in either autoclave type or tubular reactors. This work develops a mathematical model for the production of low density polyethylene in an industrial high-pressure autoclave reactor. The system modeled in this work consist of a series of two autoclave reactors with a length to diameter ratio of 15.2. Mixing in both reactors is provided by a shaft running down the center of the reactor with several impeller blades. The mixing pattern in the high-pressure reactor makes it behave more like a continuous stirred tank reactor (CSTR) rather than a tubular reactor. In the first reactor a baffle is placed near the end of the reactor as to reduced the backmixing of the product at the last part of reactor 1. Heat transfer through the walls is limited, so that the reactor is essentially adiabatic and cooling is provided by the inflow of cold monomer. The inflow of initiator at several points down the reactor provides control of the temperature which may vary down the length of the reactor. A scheme of the modeled high-pressure reactor is shown in Figure 1. Ethylene free radical polymerization mechanism and kinetics has been outlined by Zabisky et al. (1992) and the outlines of the mixing model for the high-pressure autoclave reactor has been proposed by Chan et al. (1993). The autoclave reactor presents several complications such as nonideal mixing, presence of unstable steady

states, possibility of gel formation and reaction in two phases (monomer rich phase and polymer rich phase). Figure 1. Industrial high-pressure reactor. 2. Mixing Model The mixing pattern in an autoclave type reactor tends to be of a irculating nature. The effect of mixing on reactor performance is very important, especially since an imperfectly mixed vessel requires more initiator per unit of polymer produced than does a more perfectly mixed reactor under the same conditions (Georgakis & Marini, 1982). The initiator tends to decompose near the feed points, and not in the bulk of the reactor, thus not promoting as much polymerization as if the initiator was uniformly distributed throughout the reaction mixture. The temperature gradients down the reactor also suggest imperfect mixing (Chan et al, 1993). In order to account for the imperfect mixing in the reactor, the autoclave reactor can be subdivided into several sections which can be represented by a series of small reactors consisting of a CSTR segment followed by a plug-flow segment to account for the temperature gradients down the reactor. This plug-flow segment can be transformed into a series of small volume CSTRs in order to avoid solving partial differential equations. To account for the back mixing promoted by the impeller blades, each main CSTR segment of the reactor is allowed to ycle part of its volume back to the previous CSTR main segment (Figure 2). The model developed for the reactor is a dynamic model and includes temperature controller equations to maintain the operation point at the desired steady state. This is needed because the industrial reactor normally operates at an unstable steady state in which the operation can either cause the temperature to rise or cool down the reactor until no polymerization occurs.

Figure 2. Mixing model. The mass balance for a species in a volume segment of the reactor is given by: dn dt i,s feed i,s i,r i,s ( i, S 1) = F + F + F F F + r V (1) i, S 1 i, S The plug-flow segments have no feed streams nor have any stream leaving as ycle to other segments. To investigate the effect of the macromixing parameters on the reactor fluidodynamics, two main parameters are defined: volume fraction of the CSTR segment to the total volume of the section () and the ycle ratio (). VS,CSTR θ = (2) V S,TOTAL QS β = ( S 1) (3) Q + Q S S These parameters have to be estimated for each reactor and for each section in the reactor. Larger denotes the more the section resembles an ideal CSTR, while larger denotes higher axial mixing of contiguous sections. The energy balance for the reactor requires to account for the inflows, outflows, ycles and the reaction in each segment. The reactor was assumed to be adiabatic and cooling is supplied by cold monomer feed. Heat generation is considered to come from the propagation reaction only. dts feed feed feed feed ( ρs Cp S VS ) = ρs QS CpS ( TS ) + ρs 1 QS 1 CpS 1 ( TS 1 ) dt + ρr QR CpR ( TR ) ρs QS CpS( TS ) ρs QS CpS ( TS ) ΔH rs VS Temperature control is done by manipulating the initiator feed based on the actual temperature in some measured segments of the reactor and on the temperature set point. The controller applied to the reactor was a continuous proportional-integral-derivative i, S i, S (4)

type and 5 controllers were used to control the initiator feed into the segments 2, 3, 4, 6 and 8. Δt τd ΔF I = K c (E n E n 1 ) + E n + ( E n 2 E n 1 + E n 2 ) (5) τi Δt Ethylene free radical polymerization mechanism and kinetics has been outlined by Zabisky et al. (1992) and Chan et al. (1993) for a two phase kinetic mechanism where a monomer and a polymer rich phase exist in the reaction mixture. Herein, a homopolymer that presents only one phase in the reactor (monomer rich phase) was studied and therefore the momentum equations to account for the molecular weight of the polymer were adapted from Zabisky et al. (1992) for a one phase kinetic mechanism. The kinetic mechanism considers the initiation of radical by thermal decomposition of the initiator, chain propagation, termination by combination and disproportionation, transfer to monomer and to polymer, -scission of terminal radicals and backbiting. The transfer to polymer reaction leads to polymer moment equations that are not closed, where the i th moment depends on the (i+1) th moment. To solve this problem, the closure technique of Hulburt and Katz (1964) was used in the model to calculate the third moment of the polymer distribution, as ommended by Zabisky et al. (1992). The kinetic parameters used in the simulations are based on the data published by Zabisky et al. (1992) and Chan et al. (1993). The full dynamic mathematical model was comprised of 308 ordinary differential equations to calculate the material balance of all components, the energy balance and the population balance (via method of moments). The model was solved using a 5 th order Runge-Kutta integration method with variable integration step. 3. Results Industrial production ipes from Politeno (Brazil) were used for simulation. Validation of the model were done by comparing the values predicted by the model with observed industrial steady-state values for monomer profile, initiator flow rates, temperature profile and final product characteristics. The industrial reactor was divided into eight sections to be simulated. The volumes of the reaction sections were 16.8, 13.7, 12.8, 13.3, 16.8, 8.3, 15.3 and 3.0% of the total volume of the reactor. The monomer feed distribution assumed that 12.5, 25.0, 50.0 and 12.5% of the total monomer feed entered the first segment of sections 1, 2, 3 and 5 respectively. The initiator was fed into the first segment of sections 2, 3, 4, 6 and 8. The reactor operated at pressure of 1600 atm and the temperature of the ethylene feed was of 353 K. The temperature at the third segment of sections 2, 3, 4 and 6 and 8 were controlled at 513, 513, 537, 513 and 531 K, respectively. Temperature control is a key factor for the operation of the autoclave reactor and it is very important that the controller manages to control the temperature within a short time spam. The PID controller implemented in the model and the control parameters found were able to control the temperature within a few residence time showing the efficiency of the model and it control system.

The mixing parameters, and, are a second key factor for the model and must be throughly studied. Several simulations were done as to find the best set of mixing parameters for the industrial autoclave reactor that is being simulated. Figure 3 shows the effect of the ycle ratio on the reactor behaviour. Comparing the profiles obtained in Figure 4 to actual reactor profiles have showed that none of the profiles obtained with simulations that were carried out with constant ycle ratios (all sections using the same ycle ratio) have displayed a satisfactory fit to the actual reactor data. Analyzing the configuration of the reactor and the fraction of ethylene feed in each section, we could establish that not all sections would display the same ycle ratio and that this parameter has to carefully set for each reactor design. For the design shown in Figure 1, the ycle ratio of section 4 (towards section 3) was set to zero since the baffle between sections 3 and 4 minimizes the ycle and backmixing of the reaction mixture. The ycle ratio of section 3 (towards section 2) was increased since the flow rate of ethylene fed into section 3 is larger and as such a better mixing can occur near this feeding point. The best configuration found for the mixing parameters of the model was: volume fraction of the CSTR segment to the total volume of the section () of 0.70 for all sections; and ycle ratio () of 0.15, 0.30, 0.15, 0.15 and 0.05 for the sections 2, 3, 6, 7 and 8, respectively. A comparison with industrial data is shown in Figure 4. The results found in Figure 4 are quite good and the largest relative error of the predicted values was less then 5% and as such we can state that the model truly represents the industrial reactor behavior. 4. Conclusions A comprehensive model describing the high-pressure autoclave reactor for polyethylene production was developed, accounting for the mixing pattern in the reactor, the mechanistic polymerization reaction and temperature control. The model was proven satisfactory and has fitted homopolymer ipes for initiator flow rates, temperature profiles and final polymer characteristics. Figure 4. Effect of the ycle ratio on the monomer concentration (a) and the temperature profiles (b) for the first segment (CSTR segment) of each section of the reactor ( = 0.70; each section comprised of 1 CSTR segment and 2 PFR segments).

Figure 5. Comparison of temperature profiles between the proposed model and actual industrial data for polyethylene homopolymerization. Acknowledgments The authors wish to acknowledge Politeno and Finep for the financial support for this project. References Chan, W.M., Gloor, P.E. and Hamielec, A.E., 1993, AIChE J., 39, 111. Georgakis, C. and Marini, L., 1982, ACS Symp.Ser., 196, 591. Hulburt, H. M., Katz, S., 1964, Chem. Eng. Sci., 19, 555. Zabisky, R.C.M., Chan, W.M., Gloor, P.E. and Hamielec, A.E. 1992, Polymer, 33, 2243.