Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system

Abstract The practice of using different non-biddable wastes in place of conventional filler is successively extended nowadays, leading it hard to predict the properties of modified bituminous mixes. The present work aims to explore the effect of using rice husk ash (RHA) and fly ash (FA) as an alte...

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Autores principales:	Mistry,Raja, Roy,Tapas Kumar
Lenguaje:	English
Publicado:	Escuela de Construcción Civil, Pontificia Universidad Católica de Chile 2020
Materias:	Rice Husk Ash Fly Ash Marshall mix design ANFIS Sensitivity analysis
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2020000200209
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spelling	oai:scielo:S0718-915X20200002002092020-10-04Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference systemMistry,RajaRoy,Tapas Kumar Rice Husk Ash Fly Ash Marshall mix design ANFIS Sensitivity analysis Abstract The practice of using different non-biddable wastes in place of conventional filler is successively extended nowadays, leading it hard to predict the properties of modified bituminous mixes. The present work aims to explore the effect of using rice husk ash (RHA) and fly ash (FA) as an alternative filler in place of conventional filler like hydrated lime (HL) on Marshall stability and flow of bituminous mix by adaptive neuro-fuzzy inference system (ANFIS). This study involves the preparation of samples having seven different bitumen content varying from 3.5% to 6.5% with a 0.5% increment. Mixtures containing 2%, 4%, 6%, and 8% of HL, RHA, and FA separately as filler were fabricated and compared with the control mix (i.e. mix containing 2% hydrated lime as filler). Further, the Marshall mix design procedure was followed to determine the optimum bitumen content (OBC) of each mix. Experimental results showed that the replacement of conventional filler with RHA and FA improved the Marshall properties and decreased the OBC values of the modified mix when added with 4% filler ratio Further, to analyze parameters that are the most influential in the prediction of Marshall stability and flow, a sensitivity analysis using ANFIS network was carried out considering all the input variables. As per the results obtained, the filler types, percentage filler, and percentage bitumen have the most effect on modeling the Marshall stability and flow. Then by utilizing the selected input parameters, the Marshall stability and flow were modeled with Sugeno type ANFIS. In comparison, it is realized that predicted values are closely relevant to the actual one and the prediction ability of the ANFIS is suitable for getting the said values by avoiding the expensive, time consuming, and repetitive laboratory tests.info:eu-repo/semantics/openAccessEscuela de Construcción Civil, Pontificia Universidad Católica de ChileRevista de la construcción v.19 n.2 20202020-09-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2020000200209en10.7764/rdlc.19.2.209
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Rice Husk Ash Fly Ash Marshall mix design ANFIS Sensitivity analysis
spellingShingle	Rice Husk Ash Fly Ash Marshall mix design ANFIS Sensitivity analysis Mistry,Raja Roy,Tapas Kumar Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
description	Abstract The practice of using different non-biddable wastes in place of conventional filler is successively extended nowadays, leading it hard to predict the properties of modified bituminous mixes. The present work aims to explore the effect of using rice husk ash (RHA) and fly ash (FA) as an alternative filler in place of conventional filler like hydrated lime (HL) on Marshall stability and flow of bituminous mix by adaptive neuro-fuzzy inference system (ANFIS). This study involves the preparation of samples having seven different bitumen content varying from 3.5% to 6.5% with a 0.5% increment. Mixtures containing 2%, 4%, 6%, and 8% of HL, RHA, and FA separately as filler were fabricated and compared with the control mix (i.e. mix containing 2% hydrated lime as filler). Further, the Marshall mix design procedure was followed to determine the optimum bitumen content (OBC) of each mix. Experimental results showed that the replacement of conventional filler with RHA and FA improved the Marshall properties and decreased the OBC values of the modified mix when added with 4% filler ratio Further, to analyze parameters that are the most influential in the prediction of Marshall stability and flow, a sensitivity analysis using ANFIS network was carried out considering all the input variables. As per the results obtained, the filler types, percentage filler, and percentage bitumen have the most effect on modeling the Marshall stability and flow. Then by utilizing the selected input parameters, the Marshall stability and flow were modeled with Sugeno type ANFIS. In comparison, it is realized that predicted values are closely relevant to the actual one and the prediction ability of the ANFIS is suitable for getting the said values by avoiding the expensive, time consuming, and repetitive laboratory tests.
author	Mistry,Raja Roy,Tapas Kumar
author_facet	Mistry,Raja Roy,Tapas Kumar
author_sort	Mistry,Raja
title	Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
title_short	Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
title_full	Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
title_fullStr	Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
title_full_unstemmed	Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
title_sort	predicting marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system
publisher	Escuela de Construcción Civil, Pontificia Universidad Católica de Chile
publishDate	2020
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2020000200209
work_keys_str_mv	AT mistryraja predictingmarshallstabilityandflowofbituminousmixcontainingwastefillersbytheadaptiveneurofuzzyinferencesystem AT roytapaskumar predictingmarshallstabilityandflowofbituminousmixcontainingwastefillersbytheadaptiveneurofuzzyinferencesystem
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Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system

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