Fracture toughness of polymeric particle nanocomposites: Evaluation of models performance using Bayesian method
- Authors
- Hamdia, Khader M.; Zhuang, Xiaoying; He, Pengfei; Rabczuk, 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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