Predicting Significant Characteristics of Concrete Containing Palm Oil Fuel Ash

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Abstract

Palm Oil Fuel Ash (POFA) is used as a supplementary cementitious material in
concrete. Using different percentages of POFA leads to a non-linear variation among the
characteristics of concrete. This study aims at developing an empirical model to predict the
compressive strength of concrete using POFA as a cement replacement material and other
properties of the concrete such as the slump and modulus of elasticity using an artificial
neural network. Mixtures of concrete were selected with water-to-binder ratios of 0.50, 0.55
and 0.60, and 10%, 20%, 30% and 40% of the cement content was POFA. The 28-day
compressive strength was tested, and the experimental results show that 0%–20% of POFA
inclusion in the concrete mixtures has the most positive effects on the compressive strength.
Then, a three-layer feed forward-back propagation ANN model with three inputs and three
outputs was developed. Finally, the best architecture for the model was trained, tested and
validated.
Original languageEnglish
Pages (from-to)85-98
Number of pages14
JournalJournal of Construction in Developing Countries
Volume20
Issue number1
Publication statusPublished - 2015

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Ashes
Palm oil
Fuel oils
Concretes
Cements
Concrete mixtures
Backpropagation
Compressive strength
Binders
Elastic moduli
Water

Cite this

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title = "Predicting Significant Characteristics of Concrete Containing Palm Oil Fuel Ash",
abstract = "Palm Oil Fuel Ash (POFA) is used as a supplementary cementitious material inconcrete. Using different percentages of POFA leads to a non-linear variation among thecharacteristics of concrete. This study aims at developing an empirical model to predict thecompressive strength of concrete using POFA as a cement replacement material and otherproperties of the concrete such as the slump and modulus of elasticity using an artificialneural network. Mixtures of concrete were selected with water-to-binder ratios of 0.50, 0.55and 0.60, and 10{\%}, 20{\%}, 30{\%} and 40{\%} of the cement content was POFA. The 28-daycompressive strength was tested, and the experimental results show that 0{\%}–20{\%} of POFAinclusion in the concrete mixtures has the most positive effects on the compressive strength.Then, a three-layer feed forward-back propagation ANN model with three inputs and threeoutputs was developed. Finally, the best architecture for the model was trained, tested andvalidated.",
keywords = "Mixture proportioning, Blended cement, Compressive strength, ANN",
author = "Hamed Golizadeh and Saeed BANIHASHEMI",
year = "2015",
language = "English",
volume = "20",
pages = "85--98",
journal = "Journal of Construction in Developing Countries",
issn = "1823-6499",
publisher = "Penerbit Universiti Sains Malaysia",
number = "1",

}

TY - JOUR

T1 - Predicting Significant Characteristics of Concrete Containing Palm Oil Fuel Ash

AU - Golizadeh, Hamed

AU - BANIHASHEMI, Saeed

PY - 2015

Y1 - 2015

N2 - Palm Oil Fuel Ash (POFA) is used as a supplementary cementitious material inconcrete. Using different percentages of POFA leads to a non-linear variation among thecharacteristics of concrete. This study aims at developing an empirical model to predict thecompressive strength of concrete using POFA as a cement replacement material and otherproperties of the concrete such as the slump and modulus of elasticity using an artificialneural network. Mixtures of concrete were selected with water-to-binder ratios of 0.50, 0.55and 0.60, and 10%, 20%, 30% and 40% of the cement content was POFA. The 28-daycompressive strength was tested, and the experimental results show that 0%–20% of POFAinclusion in the concrete mixtures has the most positive effects on the compressive strength.Then, a three-layer feed forward-back propagation ANN model with three inputs and threeoutputs was developed. Finally, the best architecture for the model was trained, tested andvalidated.

AB - Palm Oil Fuel Ash (POFA) is used as a supplementary cementitious material inconcrete. Using different percentages of POFA leads to a non-linear variation among thecharacteristics of concrete. This study aims at developing an empirical model to predict thecompressive strength of concrete using POFA as a cement replacement material and otherproperties of the concrete such as the slump and modulus of elasticity using an artificialneural network. Mixtures of concrete were selected with water-to-binder ratios of 0.50, 0.55and 0.60, and 10%, 20%, 30% and 40% of the cement content was POFA. The 28-daycompressive strength was tested, and the experimental results show that 0%–20% of POFAinclusion in the concrete mixtures has the most positive effects on the compressive strength.Then, a three-layer feed forward-back propagation ANN model with three inputs and threeoutputs was developed. Finally, the best architecture for the model was trained, tested andvalidated.

KW - Mixture proportioning

KW - Blended cement

KW - Compressive strength

KW - ANN

M3 - Article

VL - 20

SP - 85

EP - 98

JO - Journal of Construction in Developing Countries

JF - Journal of Construction in Developing Countries

SN - 1823-6499

IS - 1

ER -