relation: https://khub.utp.edu.my/scholars/9174/
title: Application of Response Surface Methodology for mix design optimization of nanocomposite modified asphalt mixtures
creator: Bala, N.
creator: Napiah, M.
creator: Kamaruddin, I.
description: Recently the application of polymer nanocomposite has been increasingly recognized as an alternative to polymer modified binders for durable asphalt mixtures. In this study, the optimization of nanosilica and binder content for nanocomposite modified asphalt mixtures has been examined to obtain optimum quantities for higher volumetric properties. Response Surface Methodology (RSM) based on face centered central composite design (FCCCD) was utilized. Interaction effects of independent variables nanosilica and binder content on nanocomposite volumetric properties namely stability, flow, void in total mix (VTM) and voids in mineral aggregate (VMA) were evaluated. The result indicates that the individual effects of nanosilica and binder content are both important; however, the asphalt binder content had more significance on the volumetric properties. Higher Stability was achieved with the mixtures prepared with 2 nanosilica and binder content range of 5-6. Also, the mean error obtained in all the responses from optimization results are all less than 5, this indicates that predicted values are in agreement with experimental results. Furthermore, it was concluded that asphalt mixture design with high performance properties, optimization using RSM is a very effective approach. © Int. J. of GEOMATE.
publisher: GEOMATE International Society
date: 2017
type: Article
type: PeerReviewed
identifier:   Bala, N. and Napiah, M. and Kamaruddin, I.  (2017) Application of Response Surface Methodology for mix design optimization of nanocomposite modified asphalt mixtures.  International Journal of GEOMATE, 13 (39).  pp. 237-244.  ISSN 21862982     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029907086&doi=10.21660%2f2017.39.98554&partnerID=40&md5=35703c65bef3dcb8d465d667ea35da2d
relation: 10.21660/2017.39.98554
identifier: 10.21660/2017.39.98554