| نویسندگان | Ali Nikakhtar,Gholamhossin Zohuri,Ramin falatooni,ّFatemeh Farhan moghaddam |
| نشریه | Iranian Polymer Journal |
| شماره صفحات | 0-0 |
| ضریب تاثیر (IF) | 1.422 |
| نوع مقاله | Full Paper |
| رتبه نشریه | ISI |
| نوع نشریه | چاپی |
| کشور محل چاپ | ایران |
| نمایه نشریه | JCR،isc،Scopus |
| کلید واژه ها | Artificial neural network (ANN) · Vulcanizations process · Modeling · Model parameters · Rubber foam |
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چکیده مقاله
Rubber foam is one of the materials that is being developed due to its unique properties, such as low density, flexibility,
energy absorption ability, etc. Parameters such as compound formulation and vulcanization conditions are affected on
these properties. For this reason, kinetic modeling of the vulcanization process is important. In this study, a new method
for calculating the parameters which are effect on one of the kinetic models (the Qureshi model) is presented. A model of
feed forward back propagation artificial neural network (FF BP ANN) is designed that can predict two model parameters
by taking the normalized degree of cure data. The ANN model was trained with the help of this kinetic model data. The
capability of the trained ANN was investigated with calculating the error in predicting these parameters. It was found
that the parameters were predicted with well accuracy. The experimental data obtained from the rheometer were given as
input to the ANN model and the parameters (n and k, the degree and rate constant respectively) related to these data were
calculated. This work was also done using the conventional curve fitting method. A comparison between the experimental
data reviled that the results obtained from the curve fitting method and the new method presented in this work provides
appropriate results in predicting the parameters.
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