Prediction of properties of polymer concrete composite with tire rubber using neural networks
作者： Rodica-Mariana Diaconescu , Marinela Barbuta , Maria Harja
DOI: 10.1016/J.MSEB.2013.01.014
关键词: Composite material 、 Materials science 、 Polymer concrete 、 Natural rubber 、 Ultimate tensile strength 、 Compressive strength 、 Composite number 、 Filler (packaging) 、 Flexural strength 、 Epoxy
摘要: Abstract The neural network method was used to investigate the influence of filler and resin content on mechanical properties polymer concrete with powdered tire waste. strengths 10 experimentally determined combinations using mixed epoxy resin, aggregates powder as were optimized direct modeling inverse modeling, by imposing a minimum cost (content in resin). Direct gave optimum composition for obtaining maximum values compressive strength, flexural strength split tensile strength. Inverse analyzed possibility variations dosages powder. Neural generated mixes lowest has shown that two can be simultaneously investigation domain. From obtained 0.215 (fraction weight) 0.3 Maximum experimental 0.23 0.17 severe reduction noted smaller dosages. dosage 0.24 0.17.
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