INVESTIGADORES
STEGMAYER Georgina Silvia
congresos y reuniones científicas
Título:
Industrial SBR Process. Computer Simulation Study for On-line Estimation of Polymer Process Variables Using Neural Networks
Autor/es:
R. MINARI, L. GUGLIOTTA, J. VEGA, G. STEGMAYER, O. CHIOTTI
Lugar:
Mendoza
Reunión:
Jornada; Jornadas de Informática Industrial (JII-JAIIO); 2006
Institución organizadora:
SADIO
Resumen:
An industrial emulsion copolymerization of
styrene (S) and butadiene (B) carried out in a train of 7 continuous reactors
operated under steady-state conditions is investigated. From on-line
measurements of the reaction heat rate taken in all reactors of the train, a
neural network (NN) model was developed for estimating several process
variables, such as conversion, solids content, polymer production, particle
diameter, and average copolymer composition. The NN model was trained and validated
with a large set of simulation data generated through an available
polymerization first-principles (FP) model, that was previously adjusted to
several (steady-state and transient) experiments carried out in an industrial
S-B rubber (SBR) process. Except for the copolymer composition, all variables
can accurately be estimated through the proposed NN model. Due to the
simplicity of the model and its reduced response time, the proposed NN is
suitable for on-line estimation and closed-loop control purposes.