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Prediction of mechanical properties of polypropylene/waste ground rubber tire powder treated by bitumen composites via uniform design and artificial neural networks
AbstractPolypropylene (PP)/waste ground rubber tire powder (WGRT) composites were studied with respect to the effect of bitumen and maleic anhydride-grafted styrene–ethylene–butylene–styrene (SEBS-g-MA) content by using the design of experiments (DOE) approach, whereby the effect of the four polymers content on the final mechanical properties were predicted. Uniform design method was especially adopted for its advantages. Optimization was done using hybrid artificial neural network–genetic algorithm (ANN–GA) technique. The results indicated that the composites showed fairly good ductibility provided that it had a relatively higher concentration of bitumen and SEBS-g-MA under the studied condition. A quantitative relationship was presented between the material concentration and the mechanical properties as a set of contour plots, which were confirmed experimentally by testing the optimum ratio.
Prediction of mechanical properties of polypropylene/waste ground rubber tire powder treated by bitumen composites via uniform design and artificial neural networks
AbstractPolypropylene (PP)/waste ground rubber tire powder (WGRT) composites were studied with respect to the effect of bitumen and maleic anhydride-grafted styrene–ethylene–butylene–styrene (SEBS-g-MA) content by using the design of experiments (DOE) approach, whereby the effect of the four polymers content on the final mechanical properties were predicted. Uniform design method was especially adopted for its advantages. Optimization was done using hybrid artificial neural network–genetic algorithm (ANN–GA) technique. The results indicated that the composites showed fairly good ductibility provided that it had a relatively higher concentration of bitumen and SEBS-g-MA under the studied condition. A quantitative relationship was presented between the material concentration and the mechanical properties as a set of contour plots, which were confirmed experimentally by testing the optimum ratio.
Prediction of mechanical properties of polypropylene/waste ground rubber tire powder treated by bitumen composites via uniform design and artificial neural networks
Zhang, Shu Ling (author) / Zhang, Zhen Xiu (author) / Xin, Zhen Xiang (author) / Pal, Kaushik (author) / Kim, Jin Kuk (author)
2009-10-28
6 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2010
| British Library Online Contents | 2010
| British Library Online Contents | 2009
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