Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models

Drying shrinkage in concrete can be attributed to loss of moisture, variations in temperature, and the chemical reactions of cement with water and carbon dioxide, is one of the most important parameters which affects the durability and service life of the concrete structures. Recently, the lightweig...

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Main Authors: Aslam, Muhammad, Shafigh, Payam, Jumaat, Mohd Zamin
Format: Article
Published: Springer Verlag (Germany) 2018
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Online Access:http://eprints.um.edu.my/22436/
https://doi.org/10.1007/s12205-017-0630-x
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Institution: Universiti Malaya
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spelling my.um.eprints.224362019-09-19T07:02:29Z http://eprints.um.edu.my/22436/ Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models Aslam, Muhammad Shafigh, Payam Jumaat, Mohd Zamin TA Engineering (General). Civil engineering (General) TH Building construction Drying shrinkage in concrete can be attributed to loss of moisture, variations in temperature, and the chemical reactions of cement with water and carbon dioxide, is one of the most important parameters which affects the durability and service life of the concrete structures. Recently, the lightweight concrete has got a considerable attention to be used in structural applications. Although, this concrete has very high drying shrinkage compared to conventional concrete. Therefore, the design engineers need an accurate and precise estimation of the concrete shrinkage, so that the safe and durable structure can be produced. The main objective of this research is to compare the development of drying shrinkage strain of three concrete mixes made of by-product aggregate namely oil pam shell and oil-palm-boiler clinker from the palm oil industry with the prediction models. For that purpose, ten (ACI209R, EN1992, MC2010, CEB/FIP1990, AASHTO-LRFD, GL2000, AS3600, JSCE, SAK and B3) prediction models of drying shrinkage have been selected from the standards, codes and researchers. All suggested parameters for the prediction models were considered in the estimation of shrinkage strain for the by-product concretes. In addition, the error percentage and coefficient of variation methods have been used to compute the accuracy of prediction models. The results showed that in early ages, almost all the prediction models estimated similar results with the experimental curves. However, at later ages, only few models for each concrete predicted similar results to the experimental values. Springer Verlag (Germany) 2018 Article PeerReviewed Aslam, Muhammad and Shafigh, Payam and Jumaat, Mohd Zamin (2018) Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models. KSCE Journal of Civil Engineering, 22 (12). pp. 4997-5008. ISSN 1226-7988 https://doi.org/10.1007/s12205-017-0630-x doi:10.1007/s12205-017-0630-x
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
TH Building construction
spellingShingle TA Engineering (General). Civil engineering (General)
TH Building construction
Aslam, Muhammad
Shafigh, Payam
Jumaat, Mohd Zamin
Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
description Drying shrinkage in concrete can be attributed to loss of moisture, variations in temperature, and the chemical reactions of cement with water and carbon dioxide, is one of the most important parameters which affects the durability and service life of the concrete structures. Recently, the lightweight concrete has got a considerable attention to be used in structural applications. Although, this concrete has very high drying shrinkage compared to conventional concrete. Therefore, the design engineers need an accurate and precise estimation of the concrete shrinkage, so that the safe and durable structure can be produced. The main objective of this research is to compare the development of drying shrinkage strain of three concrete mixes made of by-product aggregate namely oil pam shell and oil-palm-boiler clinker from the palm oil industry with the prediction models. For that purpose, ten (ACI209R, EN1992, MC2010, CEB/FIP1990, AASHTO-LRFD, GL2000, AS3600, JSCE, SAK and B3) prediction models of drying shrinkage have been selected from the standards, codes and researchers. All suggested parameters for the prediction models were considered in the estimation of shrinkage strain for the by-product concretes. In addition, the error percentage and coefficient of variation methods have been used to compute the accuracy of prediction models. The results showed that in early ages, almost all the prediction models estimated similar results with the experimental curves. However, at later ages, only few models for each concrete predicted similar results to the experimental values.
format Article
author Aslam, Muhammad
Shafigh, Payam
Jumaat, Mohd Zamin
author_facet Aslam, Muhammad
Shafigh, Payam
Jumaat, Mohd Zamin
author_sort Aslam, Muhammad
title Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
title_short Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
title_full Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
title_fullStr Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
title_full_unstemmed Drying Shrinkage Strain of Palm-oil by-products Lightweight Concrete: A Comparison between Experimental and Prediction Models
title_sort drying shrinkage strain of palm-oil by-products lightweight concrete: a comparison between experimental and prediction models
publisher Springer Verlag (Germany)
publishDate 2018
url http://eprints.um.edu.my/22436/
https://doi.org/10.1007/s12205-017-0630-x
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