Polymerization Model Predictive Control via Catalyst Site Segmentation
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Solution Overview
Problem
Current polymerization reactor control methods lack detailed kinetic considerations, limiting their ability to predict polymer microstructure and resulting properties such as molecular weight distribution, comonomer content, and rheological behavior, which hinders property-oriented control and monitoring.
Innovation Solution
A computer-implemented method for polymerization process monitoring and model predictive control that models the reaction performance of a catalyst using a reaction network with multiple site types, predicting reactive concentrations, polymerization rates, and polymer microstructure, and incorporates a rheology model for complex viscosity prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed kinetic modeling with multiple site types is implemented, then polymer microstructure prediction capability is improved, but device complexity increases
Solution Approach 1:
The catalyst is segmented into multiple discrete site types (e.g., 5-10 different sites), each with its own kinetic parameters and reaction characteristics. This segmentation allows the model to capture the heterogeneity of catalyst sites and predict different polymer microstructure components (such as different molecular weight distributions or comonomer contents) from each site type, thereby improving prediction capability while maintaining manageable model complexity through modular structure.
2Manufacturing precision
If comprehensive reaction network modeling is used, then product quality performance is improved, but computational requirements and processing time increase
Solution Approach 1:
Kinetic parameters for each site type are determined and stored in advance through separate calibration procedures using experimental data. The reaction network structure and kinetic expressions are pre-defined and validated before actual process control applications. This preliminary action allows the comprehensive model to be executed efficiently during real-time or near-real-time control operations, reducing computational processing time while maintaining high product quality prediction accuracy.
Data Source
AI summary
The present invention is related to a computer-implemented method for polymerization process monitoring and model predictive control, the method comprising the steps of: providing (S1) at least one set of parameters comprising catalyst information, kinetic modelling information, and calculated polymer property information; and modeling (S2) a reaction performance of a catalyst used for a polymerization process using a reaction network, the reaction network comprising multiple reactions of the catalyst, wherein reactions of the catalyst are modelled by a discrete number of multiple site types of the catalyst, wherein the catalyst is modelled as a sum of contributions of the multiple site types.