Title of article :
Artificial neural network based modelling of the Marshall Stability of asphalt concrete
Author/Authors :
Ozgan، نويسنده , , Ercan، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Pages :
6
From page :
6025
To page :
6030
Abstract :
In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modeled by using artificial neural network. In order to investigate the MS based on physical properties, exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30 °C, 40 °C and 50 °C were selected. The results showed that at the environment temperature of 17 °C the stability of the asphalt core samples decreased by 40.16% at 30 °C after 1.5 h and 62.39% after 6 h. At 40 °C, the decrease was 74.31% after 1.5 and 78.10% after 6 h. At 50 °C the stability of the asphalt decreased by 83.22% after 1.5 h, and 88.66% after 6 h. Experiment results and ANN model exhibited good correlation for this reason the ANN method could be used to model the MS.
Keywords :
Asphalt Concrete , Temperature , Artificial neural network , Marshall Stability
Journal title :
Expert Systems with Applications
Serial Year :
2011
Journal title :
Expert Systems with Applications
Record number :
2349285
Link To Document :
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