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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Materials |
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| Online Access: | https://www.mdpi.com/1996-1944/14/8/1866 |
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| author | Beng Wei Chong Rokiah Othman Ramadhansyah Putra Jaya Mohd Rosli Mohd Hasan Andrei Victor Sandu Marcin Nabiałek Bartłomiej Jeż Paweł Pietrusiewicz Dariusz Kwiatkowski Przemysław Postawa Mohd Mustafa Al Bakri Abdullah |
| author_facet | Beng Wei Chong Rokiah Othman Ramadhansyah Putra Jaya Mohd Rosli Mohd Hasan Andrei Victor Sandu Marcin Nabiałek Bartłomiej Jeż Paweł Pietrusiewicz Dariusz Kwiatkowski Przemysław Postawa Mohd Mustafa Al Bakri Abdullah |
| author_sort | Beng Wei Chong |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T12:28:09Z |
| format | Article |
| id | doaj.art-8f808213ce6544958aded53b1774dda9 |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-10T12:28:09Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Materials |
| spelling | doaj.art-8f808213ce6544958aded53b1774dda92023-11-21T14:51:55ZengMDPI AGMaterials1996-19442021-04-01148186610.3390/ma14081866Design of Experiment on Concrete Mechanical Properties Prediction: A Critical ReviewBeng Wei Chong0Rokiah Othman1Ramadhansyah Putra Jaya2Mohd Rosli Mohd Hasan3Andrei Victor Sandu4Marcin Nabiałek5Bartłomiej Jeż6Paweł Pietrusiewicz7Dariusz Kwiatkowski8Przemysław Postawa9Mohd Mustafa Al Bakri Abdullah10Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Kuantan 26300, MalaysiaFaculty of Civil Engineering Technology, Universiti Malaysia Pahang, Kuantan 26300, MalaysiaDepartment of Civil Engineering, College of Engineering, Universiti Malaysia Pahang, Kuantan 26300, MalaysiaSchool of Civil Engineering, Universiti Sains Malaysia (Engineering Campus), Nibong Tebal 14300, MalaysiaCenter of Excellence Geopolymer and Green Technology, Universiti Malaysia Perlis, Kangar 01000, MalaysiaDepartment of Physics, Częstochowa University of Technology, 42214 Częstochowa, PolandDepartment of Physics, Częstochowa University of Technology, 42214 Częstochowa, PolandDepartment of Physics, Częstochowa University of Technology, 42214 Częstochowa, PolandFaculty of Mechanical Engineering and Computer Science, Częstochowa University of Technology, 42214 Częstochowa, PolandFaculty of Mechanical Engineering and Computer Science, Częstochowa University of Technology, 42214 Częstochowa, PolandCenter of Excellence Geopolymer and Green Technology, Universiti Malaysia Perlis, Kangar 01000, MalaysiaConcrete 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.https://www.mdpi.com/1996-1944/14/8/1866design of experimentconcrete propertiesreviewregressionresponse surface methodologyartificial neural network |
| spellingShingle | Beng Wei Chong Rokiah Othman Ramadhansyah Putra Jaya Mohd Rosli Mohd Hasan Andrei Victor Sandu Marcin Nabiałek Bartłomiej Jeż Paweł Pietrusiewicz Dariusz Kwiatkowski Przemysław Postawa Mohd Mustafa Al Bakri Abdullah Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review Materials design of experiment concrete properties review regression response surface methodology artificial neural network |
| 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 | design of experiment concrete properties review regression response surface methodology artificial neural network |
| url | https://www.mdpi.com/1996-1944/14/8/1866 |
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