Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach

Modelling polymerization processes involves considerable uncertainties due to the intricate polymerization reaction mechanism involved. The complex reaction kinetics results in highly nonlinear process dynamics. Available conventional models are limited in applicability and cannot describe accurately the actual physico-chemical characteristics of the reactor dynamics. The usual practice for operating polymerization reactors is to optimize the reactor temperature profile because the end use properties of the product polymer depend highly on temperature. However, to obtain accurate models in order to optimize the temperature profile, the kinetic parameters (i.e. frequency factors and activation energies) for a specific reactor must be determined accurately. Kinetic parameters vary considerably in batch reactors because of its high sensitivity to other reactor design and operational variables such as agitator geometry and speed, gel effects, heating systems, etc. In this work, the kinetic parameters were estimated for a styrene-free radical polymerization conducted in an experimental batch reactor system using a nonlinear least squares optimization algorithm. The estimated kinetic parameters were correlated with respect to reactor operating variables including initial reactor temperature (T o), initial initiator concentration (I o) and heat duty (Q) using artificial neural network (ANN) techniques. The ANN kinetic model was then utilized in combination with the conventional mechanistic model. The experimental validation of the model revealed that the new model has high prediction capabilities compared withother reported models

The effect of temperature on kinetics and diffusion coefficients of metallocene derivatives in polyol-based deep eutectic solvents

The temperature dependence of the density, dynamic viscosity and ionic conductivity of several deep eutectic solvents (DESs) containing ammonium-based salts and hydrogen bond donvnors (polyol type) are investigated. The temperature-dependent electrolyte viscosity as a function of molar conductivity is correlated by means of Walden's rule. The oxidation of ferrocene (Fc/Fc+) and reduction of cobaltocenium (Cc+/Cc) at different temperatures are studied by cyclic voltammetry and potential-step chronoamperometry in DESs. For most DESs, chronoamperometric transients are demonstrated to fit an Arrhenius-type relation to give activation energies for the diffusion of redox couples at different temperatures. The temperature dependence of the measured conductivities of DES1 and DES2 are better correlated with the Vogel-Tamman-Fulcher equation. The kinetics of the Fc/Fc+ and Cc+/Cc electrochemical systems have been investigated over a temperature range from 298 to 338 K. The heterogeneous electron transfer rate constant is then calculated at different temperatures by means of a logarithmic analysis. The glycerol-based DES (DES5) appears suitable for further testing in electrochemical energy storage devices

Performance analysis of three advanced controllers for polymerization batch reactor: an experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC. © 2013 The Institution of Chemical Engineers