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Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review
Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070172/ https://www.ncbi.nlm.nih.gov/pubmed/33918757 http://dx.doi.org/10.3390/ma14081866 |
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author | Chong, Beng Wei Othman, Rokiah Putra Jaya, Ramadhansyah Mohd Hasan, Mohd Rosli Sandu, Andrei Victor Nabiałek, Marcin Jeż, Bartłomiej Pietrusiewicz, Paweł Kwiatkowski, Dariusz Postawa, Przemysław Abdullah, Mohd Mustafa Al Bakri |
author_facet | Chong, Beng Wei Othman, Rokiah Putra Jaya, Ramadhansyah Mohd Hasan, Mohd Rosli Sandu, Andrei Victor Nabiałek, Marcin Jeż, Bartłomiej Pietrusiewicz, Paweł Kwiatkowski, Dariusz Postawa, Przemysław Abdullah, Mohd Mustafa Al Bakri |
author_sort | Chong, Beng Wei |
collection | PubMed |
description | Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance. |
format | Online Article Text |
id | pubmed-8070172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80701722021-04-26 Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review Chong, Beng Wei Othman, Rokiah Putra Jaya, Ramadhansyah Mohd Hasan, Mohd Rosli Sandu, Andrei Victor Nabiałek, Marcin Jeż, Bartłomiej Pietrusiewicz, Paweł Kwiatkowski, Dariusz Postawa, Przemysław Abdullah, Mohd Mustafa Al Bakri Materials (Basel) Article Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance. MDPI 2021-04-09 /pmc/articles/PMC8070172/ /pubmed/33918757 http://dx.doi.org/10.3390/ma14081866 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chong, Beng Wei Othman, Rokiah Putra Jaya, Ramadhansyah Mohd Hasan, Mohd Rosli Sandu, Andrei Victor Nabiałek, Marcin Jeż, Bartłomiej Pietrusiewicz, Paweł Kwiatkowski, Dariusz Postawa, Przemysław Abdullah, Mohd Mustafa Al Bakri Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title | Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title_full | Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title_fullStr | Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title_full_unstemmed | Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title_short | Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review |
title_sort | design of experiment on concrete mechanical properties prediction: a critical review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070172/ https://www.ncbi.nlm.nih.gov/pubmed/33918757 http://dx.doi.org/10.3390/ma14081866 |
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