| Developing a mathematic model of industrial polymerization processes, which can be successfully applied to predict both the process kinetics mechanism and the process industrial performance, is not only helpful to master the inherence of the polymerization process, but also the basis of optimizing the production process and enhancing the process benefit. Due to its complexity of the polymerization kinetics mechanism and the practical industrial polymerization processes, modeling of a polymerization process becomes a major branch of polymer reaction engineering, and it's also an unsolved and challenging problem.In this paper, an industrial bulk polymerization process of styrene was considered. Based on the thoroughly analysis, modeling and optimization of the styrene polymerization on plant scale were carried out with both the mechanism mathematic modeling method and the ASPEN software tools respectively. Based on the practice industrial data, a nonlinear PLS soft sensing model of the styrene polymerization processes was developed with the principal component polynomial between the process variables and the quality variables. The main work was listed as follows:1. Based on the process mechanism analysis, a mechanism mathematic model with the differential equations was derived to describe both the pre-polymerization process and the post-polymerization process, and the model parameters were achieved. The model of polymerization process were developed and simulated with MATALAB code. Verifying of the model validity was then carried out using both the practical industrial data and the data offered by the supplier. It showed that the styrene conversion, average molecular weight and molecular weight distribution predicted by the above mechanism model were in good agreement with the practical industrial data.2. An industrial polymerization model was developed with POLYMER PLUS software, where both RCSTR and RPFR internal standard units were adopted to set up the process model, the pre-polymerization section was considered as two CSTRs, each tower reactor of post-polymerization section was considered as a series of CSTR+PFR+ CSTR+PFR+CSTR. The sensitivity analysis of the kinetic parameters of the above model was presented. And the kinetics parameters were adjusted based on a set ofpractical industrial data. It showed that the predicted results of the above model developed with ASPEN software were consistent with the practical industrial data perfectly, and in general better than those of the mechanism model developed with MATLAB software.3. Analysis of industrial styrene bulk polymerization processes was carried out. The sensitivities of operation parameters (reaction temperature, total input flux, the ratio of side flow to main flow) were studied with the above developed ASPEN model. A correlative dynamic model, which paved the way for the analysis of process dynamic behavior, was built up with DYNAMIC PLUS and its validity was verified. In addition, the dynamic responses of polymerization processes were analyzed with the above developed dynamic model.4. Analysis of abnormal state in industrial styrene bulk polymerization processes was presented. Process simulations of both operation boundary state and urgent accident were carried out. When the process was in the operation boundary, the process yield potential and the maximum Mw of the industrial polymerization processes were achieved, and the scheme of producing high Mw polymer was analyzed in detail. When some urgent accidents, i.e., heater media of plant was broken off, the feed flow was switched to styrene or recycled monomer, were happened, process performances were explored.5. Nonlinear function structure between the process variables (reaction temperature, the ratio of side flow to main flow) and the quality variables (Melt Index, polymerization yield) was achieved. A nonlinear PLS soft sensing model of the styrene polymerization processes with the principal component polynomial between the process variables a...
|
PDF Full Text Request