𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Use of neural networks for modeling of olefin polymerization in high pressure tubular reactors

✍ Scribed by Wai-Man Chan; Cláudio A. O. Nascimento

Publisher
John Wiley and Sons
Year
1994
Tongue
English
Weight
815 KB
Volume
53
Category
Article
ISSN
0021-8995

No coin nor oath required. For personal study only.

✦ Synopsis

Neural network computing is one of the fastest growing fields of artificial intelligence due to its ability to "learn" nonlinear relationships. This article presents the approach of back propagation neural networks for modeling of free radical polymerization in high pressure tubular reactors. Industrial data were used to train the network for prediction of the temperature profile along the reactor, as well as polymer properties such as density, melt flow index, and molecular weight averages. Comparisons were made between the neural network and mechanistic model predictions published in the literature. Results showed the promising capability of a neural network as an alternative approach to model polymeric systems.

📜 SIMILAR VOLUMES

Continuous polymerization in tubular rea
Continuous polymerization in tubular reactors with prepolymerization: Analysis using two-dimensional phenomenological model and hybrid model with neural networks
✍ André L. Nogueira; Liliane M. F. Lona; Ricardo A. F. Machado 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 509 KB

## Abstract Continuous polymerization processes have advantages when large amounts of product are required; moreover, higher quality can be obtained because of the elimination of variability between batches. Tubular reactors are economically attractive because of their simple geometry and high heat

New Approach in Modeling of Metallocene-
New Approach in Modeling of Metallocene-Catalyzed Olefin Polymerization Using Artificial Neural Networks
✍ Mostafa Ahmadi; Mehdi Nekoomanesh; Hassan Arabi 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 266 KB

## Abstract A new approach for the estimation of kinetic rate constants in olefin polymerization using metallocene catalysts is presented. The polymerization rate has been modeled using the method of moments. An ANN has been used and trained to behave like the mathematical model developed before, s

Modeling of industrial nylon-6,6 polymer
Modeling of industrial nylon-6,6 polymerization process in a twin-screw extruder reactor. II. Neural networks and hybrid models
✍ Claudio Augusto Oller Nascimento; Reinaldo Giudici; Natália Scherbakoff 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 174 KB 👁 2 views

This article describes the application of neural networks and hybrid models to the finishing stage of nylon-6,6 polycondensation in a twin-screw extruder reactor. A planned experiment in the industrial and in the pilot plant was employed to build the neural network and the hybrid model. The hybrid m

A Multi-Scale Modeling Approach for the
A Multi-Scale Modeling Approach for the Prediction of Molecular and Morphological Properties in Multi-Site Catalyst, Olefin Polymerization Reactors
✍ Georgios Dompazis; Vassileios Kanellopoulos; Costas Kiparissides 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 360 KB 👁 1 views

## Abstract **Summary:** In the present study, a comprehensive, multi‐scale, mathematical model is developed for the calculation of the distributed properties of polymer particles in a gas phase, catalytic, olefin polymerization, fluidized bed reactor (FBR). At the molecular level, a generalized mu