Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength
The concrete workability and the compressive strength are the principal properties of the fresh and hardened concrete, respectively. When self-compacting properties are required, scientific knowledge is important and appropriate models applied to achieve optimized compositions. Here, experimental da...
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2021
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oai:doaj.org-article:333a0295fef1432e8ba2e81b17c4a93e2021-11-20T05:06:55ZExperimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength2352-340910.1016/j.dib.2021.107563https://doaj.org/article/333a0295fef1432e8ba2e81b17c4a93e2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352340921008398https://doaj.org/toc/2352-3409The concrete workability and the compressive strength are the principal properties of the fresh and hardened concrete, respectively. When self-compacting properties are required, scientific knowledge is important and appropriate models applied to achieve optimized compositions. Here, experimental data regarding to the mortars is presented. The dataset regards to a design of experiments carried out in mortars with commercial materials through a central composite design with five independent variables: Waterv/Cementv, Superplasticyzerm/Powderv, Waterv/Powderv, Sandv/Mortarv, FineSandv/Sandv. In total 64 mortar composition were done: 25 factorial design consisting on 32 treatment combinations augmented by 10 axial runs plus 8 central runs, resulting in a central composite design with 50 mortar trial mix composition. Beside 14 extra mixes were done to allow comparing and validating results for the response models to be applied. Four dependent variables were measured: the D-flow and the t-funnel to measure the workability and the tensile strength and the compressive at the age of 24 h to assess the mechanical properties. Since the experiments were run based in a central composite design and extra mixes were prepared, response models can be applied to the dataset in order to find optimized mix compositions.Lino MaiaElsevierarticleCementCommercial sandDesign of experimentsMortarResponse modelComputer applications to medicine. Medical informaticsR858-859.7Science (General)Q1-390ENData in Brief, Vol 39, Iss , Pp 107563- (2021) |
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Cement Commercial sand Design of experiments Mortar Response model Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390 |
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Cement Commercial sand Design of experiments Mortar Response model Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390 Lino Maia Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| description |
The concrete workability and the compressive strength are the principal properties of the fresh and hardened concrete, respectively. When self-compacting properties are required, scientific knowledge is important and appropriate models applied to achieve optimized compositions. Here, experimental data regarding to the mortars is presented. The dataset regards to a design of experiments carried out in mortars with commercial materials through a central composite design with five independent variables: Waterv/Cementv, Superplasticyzerm/Powderv, Waterv/Powderv, Sandv/Mortarv, FineSandv/Sandv. In total 64 mortar composition were done: 25 factorial design consisting on 32 treatment combinations augmented by 10 axial runs plus 8 central runs, resulting in a central composite design with 50 mortar trial mix composition. Beside 14 extra mixes were done to allow comparing and validating results for the response models to be applied. Four dependent variables were measured: the D-flow and the t-funnel to measure the workability and the tensile strength and the compressive at the age of 24 h to assess the mechanical properties. Since the experiments were run based in a central composite design and extra mixes were prepared, response models can be applied to the dataset in order to find optimized mix compositions. |
| format |
article |
| author |
Lino Maia |
| author_facet |
Lino Maia |
| author_sort |
Lino Maia |
| title |
Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| title_short |
Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| title_full |
Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| title_fullStr |
Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| title_full_unstemmed |
Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| title_sort |
experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength |
| publisher |
Elsevier |
| publishDate |
2021 |
| url |
https://doaj.org/article/333a0295fef1432e8ba2e81b17c4a93e |
| work_keys_str_mv |
AT linomaia experimentaldatasetfromacentralcompositedesigntodevelopmortarswithselfcompactingpropertiesandhighearlyagestrength |
| _version_ |
1718419533946945536 |