Details

Autor(en) / Beteiligte

• Patel, R M

Titel

Modeling of Fiber Spinning and Crystallization Kinetics During Polymer Processing

Erscheinungsjahr

1992

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• A multitude of process and resin variables affect the melt spinning process. Hence, a mathematical model of the process is quite valuable for developing an understanding of the process and for predicting spinline behavior under a variety of process conditions. It was the basic purpose of the present research to develop an improved process model for melt spinning of fibers with a better understanding of polymer rheology and polymer physics underlying the spinline dynamics and structure development. The spinline model developed by Zieminski using the CSMP package on the IBM mainframe was improved, simplified and implemented on the IBM PC. The inversion procedure used by Bheda was improved, simplified and implemented on the IBM PC. The improved inversion procedure is described and is shown to give better results for the computed apparent elongational viscosity data of the nylon 6 resins and heat transfer coefficient data. The model predictions compared well with the experimental on-spinline measurements on two nylon 6 resins carried out by Bheda. The results show that the model describes the major features of the melt spinning process. The applications of the Newtonian spinline model in understanding the role of various process and resin variables in determining spinline behavior are described. An analysis of available methods of dealing with polymer crystallization for process modeling is presented. Problems encountered in using isothermal data to predict nonisothermal results are discussed and illustrated using experimental data for two nylon 6 resins. A half-time analysis is used to evaluate and extrapolate the isothermal crystallization rates. It is concluded that none of the available models are entirely satisfactory for computing nonisothermal crystallization from isothermal data, though the Nakamura model is shown to be more satisfactory for process modeling than other models discussed in the literature. A nonlinear regression method is presented for directly fitting nonisothermal crystallinity data using the Nakamura model to obtain crystallization rate equation parameters. Two empirical methods for including amorphous orientation effects are also considered and evaluated by comparing predicted results to online experimental data for melt spinning of nylon 6. (DA9212785).