Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review
Autor: | B. W. Chong, Marcin Nabiałek, Rokiah Othman, Andrei Victor Sandu, Bartłomiej Jeż, Mohd Rosli Mohd Hasan, Mohd Mustafa Al Bakri Abdullah, Paweł Pietrusiewicz, D. Kwiatkowski, Przemysław Postawa, Ramadhansyah Putra Jaya |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Computer science
0211 other engineering and technologies design of experiment review 02 engineering and technology lcsh:Technology Article response surface methodology Taguchi methods 021105 building & construction General Materials Science Response surface methodology lcsh:Microscopy lcsh:QC120-168.85 Data collection lcsh:QH201-278.5 Artificial neural network lcsh:T Design of experiments 021001 nanoscience & nanotechnology Expression (mathematics) Reliability engineering Engineering studies lcsh:TA1-2040 lcsh:Descriptive and experimental mechanics regression lcsh:Electrical engineering. Electronics. Nuclear engineering Experimental methods lcsh:Engineering (General). Civil engineering (General) 0210 nano-technology concrete properties lcsh:TK1-9971 artificial neural network |
Zdroj: | Materials Volume 14 Issue 8 Materials, Vol 14, Iss 1866, p 1866 (2021) |
ISSN: | 1996-1944 |
DOI: | 10.3390/ma14081866 |
Popis: | 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. |
Databáze: | OpenAIRE |
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