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Dynamics & Control Processes Modeling and Control of Molecular Weight Distribution in a Liquid-phase Polypropylene Reactor Mohammad Al-haj Ali, Ben Betlem,

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Presentation on theme: "Dynamics & Control Processes Modeling and Control of Molecular Weight Distribution in a Liquid-phase Polypropylene Reactor Mohammad Al-haj Ali, Ben Betlem,"— Presentation transcript:

1 Dynamics & Control Processes Modeling and Control of Molecular Weight Distribution in a Liquid-phase Polypropylene Reactor Mohammad Al-haj Ali, Ben Betlem, Günter Weickert & Brian Roffel Research groups Dynamics & Control Processes -Industrial Polymerization Processes - Faculty of Science and technology University of Twente 11/11/2005

2 Dynamics & Control Processes 2 Project goals Producing tailor-made polypropylenes, including bimodal grades, by using a single reactor

3 Dynamics & Control Processes 3  to improve the understanding of the relationship between polypropylene molecular weight and MWD and hydrogen concentration in liquid propylene as well as model this dependency.  to develop a simple and efficient nonlinear model-based control scheme.  to study the optimal grade change of polypropylene.  to perform a feasibility study of the optimal broadening of MWD.  to build hollow shaft reactor set-up.  to develop a predictive kinetic model for propylene polymerization in liquid pool.

4 Dynamics & Control Processes 4 Experimental set-up 5.0 L batch reactor. Max. operating Pressure = 60 bar. Liquid and gas polymerization reactions. Ziegler-Natta catalyst: MgCl 2 /TiCl 4 /phthalate – AlEt 3 /Silane 6 wt % TiCl 4

5 Dynamics & Control Processes 5 Experimental Results Reproducibility Experimental conditions: T = 70 °C, mass of catalyst = 3.78 mg, mass of cocatalyst = 1000 mg, hydrogen added = 150 mg

6 Dynamics & Control Processes 6 Effect of reactor filling on polymerization kinetics RunT, °C Catalyst, mg Cocatalyst mg Donor, mg H 2, mg Yield, kg/g cat. hr Filling degree 1703.7850030012.6H 2703.78104050015.6T 3703.785003015059.8H 4703.7810405015082.5T

7 Dynamics & Control Processes 7 RunT, °C Catalyst, mg Cocatalyst, mg Donor, mg H 2, mg Yield, kg/g cat. hr Filling degree 3703.785003015059.8H 4703.7810405015082.5T 5801.54104050150119.8T 6801.545003012052.5H Effect of reactor filling on polymerization kinetics

8 Dynamics & Control Processes 8 Kinetics and Molecular weight distribution Experimental recipe: fully-filled  Liquid-pool polymerization in a fully-filled reactor.  Different hydrogen amounts. 0.0 mg - 2500 mg Hydrogen  Different reaction temperatures. 60 °C - 80 °C

9 Dynamics & Control Processes 9 RunH 2, mgX*10 -3 t r, minR po, kg/g cat. hrk d, hr -1 10.006016.10.34 2250.246062.50.80 31501.4447121.61.19 42502.4745145.11.50 510009.9445139.61.93 6250026.730125.92.81 Kinetics: hydrogen and temperature effects T = 70 °C

10 Dynamics & Control Processes 10 Kinetics: hydrogen and temperature effects

11 Dynamics & Control Processes 11 Kinetics: modeling

12 Dynamics & Control Processes 12 Molecular weight distribution

13 Dynamics & Control Processes 13 Process model

14 Dynamics & Control Processes 14 Design of Control Scheme

15 Dynamics & Control Processes 15 Design of ControlScheme Design of Control Scheme Nonlinear Multivariable Controller: Generic model control (GMC)-based controller = 0

16 Dynamics & Control Processes 16 Design of ControlScheme Design of Control Scheme Nonlinear Multivariable Controller: Generic model control (GMC)-based controller

17 Dynamics & Control Processes 17 Design of ControlScheme Design of Control Scheme Nonlinear Multivariable Controller: Generic model control (GMC)-based controller

18 Dynamics & Control Processes 18 Design of ControlScheme Design of Control Scheme

19 Dynamics & Control Processes 19 Design of ControlScheme Design of Control Scheme

20 Dynamics & Control Processes 20 Design of ControlScheme Design of Control Scheme

21 Dynamics & Control Processes 21 Optimal Grade Transition Objective function: Solution methods: 1.Pontryagin’s Minimum Principle 2.Simultaneous method 3.Control Parameterization technique

22 Dynamics & Control Processes 22 Optimal Grade Transition Control Parameterization technique

23 Dynamics & Control Processes 23 Optimal Grade Transition Pontryagin’s Minimum Principle

24 Dynamics & Control Processes 24 Optimal Grade Transition

25 Dynamics & Control Processes 25 Optimal Broadening of MWD Batch mixing of two polypropylene samples

26 Dynamics & Control Processes 26 Optimal Broadening of MWD Broadened polypropylene produced in the continuous reactor Objective function:

27 Dynamics & Control Processes 27 Optimal Broadening of MWD Broadened polypropylene produced in the continuous reactor

28 Dynamics & Control Processes 28 Optimal Broadening of MWD Broadened polypropylene produced in the continuous reactor

29 Dynamics & Control Processes 29 Hollow Shaft Reactor  2.0 L reactor. Max. operating Pressure = 250 bar Max. operating Temperature = 250° C  Minimum dead volume.  Can be modeled as CSTR.

30 Dynamics & Control Processes 30 Monomer supply unit Hollow Shaft Reactor

31 Dynamics & Control Processes 31 Hollow Shaft Reactor Catalyst injection unit

32 Dynamics & Control Processes 32 The reactor Hollow Shaft Reactor

33 Dynamics & Control Processes 33 Experimental results Hollow Shaft Reactor

34 Dynamics & Control Processes 34

35 Dynamics & Control Processes 35 Pressure-drop dilatometry H 2, mg0.0502501000 M1M1 1.851.571.623.10 M2M2 2.011.992.054.80 Experimental conditions: T = 70 °C, mass of catalyst = 3.78 mg, mass of cocatalyst = 1000 mg, H 2 = 150 mg Experimental conditions: T = 70 °C, mass of catalyst = 3.78 mg, mass of cocatalyst = 1000 mg, H 2 = 1000 mg 1000 3.2 4 Extrapolated


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