✦ LIBER ✦

Apparent viscosity prediction of alumina–paraffin suspensions using artificial neural networks

✍ Scribed by Drago Torkar; Saša Novak; Franc Novak

Publisher: Elsevier Science
Year: 2008
Tongue: English
Weight: 762 KB
Volume: 203
Category: Article
ISSN: 0924-0136
DOI: 10.1016/j.jmatprotec.2007.09.058

No coin nor oath required. For personal study only.

✦ Synopsis

A neural network model has been developed for the prediction of apparent viscosity of alumina-paraffin suspensions used in low-pressure injection moulding (LPIM) process. The model is based on a three-layer neural network with a backpropagation-learning algorithm.

The training data were collected by the rotational viscometry followed by a nonlinear regression. The network is trained to predict the values of power-law model parameters suitable to describe non-Newtonian fluids. A comparison between experimental values and those predicted by the neural network shows a good coincidence. The approach helps to reduce the amount of experiments required to determine these constants in practice.

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