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Prediction of rubber stability by accelerated aging test modeling
Author(s) -
Rodionova Oxana Y.,
Pomerantsev Alexey L.
Publication year - 2005
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/app.21347
Subject(s) - extrapolation , accelerated aging , stability (learning theory) , natural rubber , computer science , bayesian probability , biological system , materials science , mathematics , statistics , artificial intelligence , composite material , machine learning , biology
This study was devoted to the prediction of polymer material aging. The prediction of the shelf time of tire rubber is used as an example in this article. The main steps of the whole procedure are described. They are the design of the experiment, accelerated aging testing, the construction of a multiresponse mathematical model and parameter estimation, and the extrapolation of the model in real‐life settings. The main pitfalls were deduced, and techniques to overcome these pitfalls are described. Novel methods of data modeling, such as evolutionary design of experiment and successive Bayesian estimation, were used. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 95: 1275–1284, 2005