Repository logo
 
Loading...
Thumbnail Image
Publication

Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength

Use this identifier to reference this record.

Authors

Advisor(s)

Abstract(s)

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 ap plied to achieve optimized compositions. Here, experimen tal data regarding to the mortars is presented. The dataset regards to a design of experiments carried out in mor tars with commercial materials through a central compos ite 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 compo sition. 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 me chanical 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.

Description

Keywords

Cement Commercial sand Design of experiments Mortar Response model . Faculdade de Ciências Exatas e da Engenharia

Citation

Maia, L. (2021). Experimental dataset from a central composite design to develop mortars with self-compacting properties and high early age strength. Data in Brief, 39, 107563.

Research Projects

Research ProjectShow more

Organizational Units

Journal Issue

Publisher

Elsevier

CC License

Altmetrics