Development of PP Melt Index Inferential Model
The melt index (MI) is an important quality specification in polypropylene (PP) production industries. Accurate online measurement of MI becomes vital in PP quality control. A new MI inferential model is proposed by using macro heat of reaction (MHR) as a key factor in MI correlation. MHR is calculated from a dynamic propylene polymerization model. The proposed MI model is validated by plant data and the prediction error is less than 5%. Simulations are performed by three different MI inferential models. The results show that the proposed model has least errors in various operation conditions. The MI model could be used as online soft sensor model or MI control
Development of polyethylene melt index inferential model
In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a large number of MI estimation and correlation methods have been proposed. In this work, we propose a new MI predicting model in which the reaction heat term in existing prediction models is replaced by temperature. The proposed model is compared with other prediction models as well as operating data to evaluate MI predicting performance. The present model shows least predicting errors compared to existing models.
On a mathematical model for loop reactors—II. Estimation of parameters
Abstract Based on a model of loop reactors with sections of different mixing behaviour and on an approximation formula for its residence time distribution, a procedure is derived to determine the main model parameters, the mean circulation time, the circulation variance and the corresponding values of the individual sections. Finally the results of application of this procedure to RTD-measurements in a laboratory liquid jet loop reactor are presented.