Statistical modeling of lightweight concrete mixtures

This paper employed a statistical technique for modeling of lightweight concrete mixtures using palm oil clinker (POC) as aggregate. POC is obtained from by-product of palm oil milling. The material is still new and accurate determination of its properties is very difficult. This makes the mix desig...

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Main Authors: Abdullahi M., Al-Mattarneh H.M.A., Mohammed B.S.
Other Authors: 57211016458
Format: Article
Published: EuroJournals, Inc. 2023
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spelling my.uniten.dspace-309242023-12-29T15:55:59Z Statistical modeling of lightweight concrete mixtures Abdullahi M. Al-Mattarneh H.M.A. Mohammed B.S. 57211016458 26666458600 57203590522 Aggregate Airdry density Compressive strength Concrete Mix design Model Slump This paper employed a statistical technique for modeling of lightweight concrete mixtures using palm oil clinker (POC) as aggregate. POC is obtained from by-product of palm oil milling. The material is still new and accurate determination of its properties is very difficult. This makes the mix design of POC concrete a difficult task. Aggregate characterisation was conducted to determine the properties of palm oil clinker required for mix design. A central composite design (CCD) was used for the factor settings and mix design was conducted using absolute volume method. An experimental work was conducted involving 20 trial mixes at different factor and level combinations. Statistical modeling was done at 95% confidence interval. Test result shows that a polynomial model is adequate to predict the slump, air-dry density and compressive strength of POC concrete. The terms considered in the models were significant with p-values less than 0.05. The analysis of variance (ANOVA) shows that the developed models adequately fit the experimental data with a p-value for the regression less than 0.05. These statistics assures reasonable response prediction. Statistical approach has proved to be a useful tool for modeling of lightweight concrete mixture. � EuroJournals Publishing, Inc. 2009. Final 2023-12-29T07:55:59Z 2023-12-29T07:55:59Z 2009 Article 2-s2.0-67649766734 https://www.scopus.com/inward/record.uri?eid=2-s2.0-67649766734&partnerID=40&md5=8d017125cf675a0e58da5b781f016572 https://irepository.uniten.edu.my/handle/123456789/30924 31 1 124 131 EuroJournals, Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Aggregate
Airdry density
Compressive strength
Concrete
Mix design
Model
Slump
spellingShingle Aggregate
Airdry density
Compressive strength
Concrete
Mix design
Model
Slump
Abdullahi M.
Al-Mattarneh H.M.A.
Mohammed B.S.
Statistical modeling of lightweight concrete mixtures
description This paper employed a statistical technique for modeling of lightweight concrete mixtures using palm oil clinker (POC) as aggregate. POC is obtained from by-product of palm oil milling. The material is still new and accurate determination of its properties is very difficult. This makes the mix design of POC concrete a difficult task. Aggregate characterisation was conducted to determine the properties of palm oil clinker required for mix design. A central composite design (CCD) was used for the factor settings and mix design was conducted using absolute volume method. An experimental work was conducted involving 20 trial mixes at different factor and level combinations. Statistical modeling was done at 95% confidence interval. Test result shows that a polynomial model is adequate to predict the slump, air-dry density and compressive strength of POC concrete. The terms considered in the models were significant with p-values less than 0.05. The analysis of variance (ANOVA) shows that the developed models adequately fit the experimental data with a p-value for the regression less than 0.05. These statistics assures reasonable response prediction. Statistical approach has proved to be a useful tool for modeling of lightweight concrete mixture. � EuroJournals Publishing, Inc. 2009.
author2 57211016458
author_facet 57211016458
Abdullahi M.
Al-Mattarneh H.M.A.
Mohammed B.S.
format Article
author Abdullahi M.
Al-Mattarneh H.M.A.
Mohammed B.S.
author_sort Abdullahi M.
title Statistical modeling of lightweight concrete mixtures
title_short Statistical modeling of lightweight concrete mixtures
title_full Statistical modeling of lightweight concrete mixtures
title_fullStr Statistical modeling of lightweight concrete mixtures
title_full_unstemmed Statistical modeling of lightweight concrete mixtures
title_sort statistical modeling of lightweight concrete mixtures
publisher EuroJournals, Inc.
publishDate 2023
_version_ 1806424528685891584
score 13.18916