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Fracture toughness of polymeric particle nanocomposites: Evaluation of models performance using Bayesian method

Authors
Hamdia, Khader M.Zhuang, XiaoyingHe, PengfeiRabczuk, Timon
Issue Date
1-4월-2016
Publisher
ELSEVIER SCI LTD
Keywords
Nano particles; Fracture toughness; Modelling
Citation
COMPOSITES SCIENCE AND TECHNOLOGY, v.126, pp.122 - 129
Indexed
SCIE
SCOPUS
Journal Title
COMPOSITES SCIENCE AND TECHNOLOGY
Volume
126
Start Page
122
End Page
129
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/88948
DOI
10.1016/j.compscitech.2016.02.012
ISSN
0266-3538
Abstract
This study presents a methodology to evaluate the performance of different models used in predicting the fracture toughness of polymeric particles nanocomposites. Three analytical models are considered: the model of Huang and Kinloch, the model of Williams, and the model of Quaresimin et al. The purpose behind this study is not to recommend which of the three models to be adopted, but to evaluate their performance with respect to experimental data. The Bayesian method is exploited for this purpose based on different reference measurements gained from the literature. The models' performance is compared and evaluated comprehensively accounting for the parameter and model uncertainties. Based on the approximated optimal parameter sets, the coefficients of variation of the model predictions to the measurements are compared for the three models. Finally, the model selection probability is obtained with respect to the different reference data. (C) 2016 Elsevier Ltd. All rights reserved.
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