Correlation of Modified Natural Rubber Properties by Artificial Neural Networks


Autoria(s): GIORDANI, D. S.; OLIVEIRA, P. C.; GUIMARAES, A.; GUIMARAES, R. C. O.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

18/10/2012

18/10/2012

2009

Resumo

Natural rubber (NR) is a raw material largely used by the modern industry; however, it is common that chemical modifications must be made to NR in order to improve properties such as hydrophobicity or mechanical resistance. This work deals with the correlation of properties of NR modified with dimethylaminoethylmethacrylate or methylmethacrylate as grafting agents. Dynamic-mechanical behavior and stress/strain relations are very important properties because they furnish essential characteristics of the material such as glass transition temperature and rupture point. These properties are concerned with different physical principles; for this reason, normally they are not related to each other. This work showed that they can be correlated by artificial neural networks (ANN). So, from one type of assay, the properties that as a rule only could be obtained from the other can be extracted by ANN correlation. POLYM. ENG. SCI., 49:499-505, 2009. (c) 2009 Society of Plastics Engineers

Universidade de São Paulo - EEL-USP

FAPESP

CAPES

CNPq

Identificador

POLYMER ENGINEERING AND SCIENCE, v.49, n.3, p.499-505, 2009

0032-3888

http://producao.usp.br/handle/BDPI/17469

10.1002/pen.21311

http://dx.doi.org/10.1002/pen.21311

Idioma(s)

eng

Publicador

JOHN WILEY & SONS INC

Relação

Polymer Engineering and Science

Direitos

restrictedAccess

Copyright JOHN WILEY & SONS INC

Palavras-Chave #PREDICTION #COMPOSITES #Engineering, Chemical #Polymer Science
Tipo

article

original article

publishedVersion