Premium
Flow instabilities in rheotens experiments: Analysis of the impacts of the process conditions through neural network modeling
Author(s) -
Tronci Stefania,
Coppola Salvatore,
Bacchelli Fabio,
Grosso Massimiliano
Publication year - 2013
Publication title -
polymer engineering and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.503
H-Index - 111
eISSN - 1548-2634
pISSN - 0032-3888
DOI - 10.1002/pen.23387
Subject(s) - materials science , rheometer , spinning , drawdown (hydrology) , artificial neural network , flow (mathematics) , fiber , composite material , mechanics , rheology , computer science , engineering , artificial intelligence , geotechnical engineering , physics , aquifer , groundwater
Fiber spinning experiments are conducted with a capillary rheometer and a Rheotens tester on linear styrene‐isoprene‐styrene copolymer samples by varying extrusion temperature and drawdown velocity in a wide range of values, also covering the occurrence of instability phenomena. Tensile stress is measured during the experiences, and the experimental time series are then analyzed by means of a new methodology. The proposed approach is based on Neural Network modeling of the time series, coupled with Principal Component Analysis postprocessing of the results. The methodology is able to identify and quantify the effects of process condition on the dynamical behavior of the system. POLYM. ENG. SCI., 2013. © 2012 Society of Plastics Engineers