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<article-meta><doi>463</doi>
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<article-title>Artificial Neural Network Model for Prediction of Mechanical Properties of Ground Rubber Tire Incorporated Concrete</article-title>
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<author>Salabh Goyal<sup>a</sup>, Smitha Gopinath<sup>b</sup>, A. Ramachandra Murthy<sup>c</sup> and Nagesh R. Iyer<sup>d</sup>  </author>

<aff>CSIR - Structural Engineering Research Centre, Chennai, India. </aff>

<email><a href="mailto:goyalsalabh@gmail.com"><sup>a</sup>goyalsalabh@gmail.com</a></email>

<email><a href="mailto:smithag@serc.res.in"><sup>b</sup>smithag@serc.res.in</a></email>

<email><a href="mailto:murthyarc@serc.res.in"><sup>c</sup>murthyarc@serc.res.in</a></email>

<email><a href="mailto:nriyer@serc.res.in "><sup>d</sup>nriyer@serc.res.in </a></email>

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<title>ABSTRACT</title>
<p>Polymer modified concrete has been used for the repair of concrete structures for over two decades. Rubber tires are one type of non-degradable polymeric material and its powdered form is found to be compatible in a concrete mix recently. Ground rubber recycled from waste tire has notable environmental and mechanical advantage over the conventional substitutes in concrete. The recycling of rubber tire is an environmental concern and the use of ground rubber tire in concrete will provide an effective solution. Present study aims at investigating the use of ground rubber powder as a partial replacement for cement in concrete mix. Different proportions of ground rubber powder are incorporated and mechanical properties are determined. Further, an artificial neural network (ANN) model is developed to predict the mechanical properties of rubber tire incorporated concrete.  </p>
<p><i>Keywords: </i>Artificial neural network, Concrete, Ground rubber, Compressive strength, Repair. </p>
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