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Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties

Fresh and hardening properties of cement-based materials are key factors for correctly choosing the constituent materials and their mix proportions. To optimize design-based mortar compositions for specific applications, response models are frequently applied to data collected from scientific approa...

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Autor principal: Maia, Lino
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717463/
https://www.ncbi.nlm.nih.gov/pubmed/35005136
http://dx.doi.org/10.1016/j.dib.2021.107738
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author Maia, Lino
author_facet Maia, Lino
author_sort Maia, Lino
collection PubMed
description Fresh and hardening properties of cement-based materials are key factors for correctly choosing the constituent materials and their mix proportions. To optimize design-based mortar compositions for specific applications, response models are frequently applied to data collected from scientific approaches. Here, experimental dataset regarding to a design of experiments carried out in mortars through a central composite design with five independent variables is presented. Among the five independent variables, four were quantitative ones: Water(v)/Cement(v), Superplasticyzer(m)/Powder(v), Water(v)/Powder(v), Sand(v)/Mortar(v). The other independent variable was a qualitative one: Superplasticiser A or Superplasticiser B. In total 60 mortar compositions were done: for each qualitative variable a 2(4) factorial design comprising of 16 treatment combinations enlarged by 8 axial runs plus 6 central runs, resulting in a central composite design with 30 mortar trial mix compositions. The following dependent variables were tested: the D-flow and the t-funnel to evaluate the fresh properties and the compressive at the age of 24 h and at the age of 28 days to evaluate the hardened properties. Based on this dataset, response models can be applied to find optimized mix compositions, with the effect of the two qualitative variables being determined.
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spelling pubmed-87174632022-01-06 Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties Maia, Lino Data Brief Data Article Fresh and hardening properties of cement-based materials are key factors for correctly choosing the constituent materials and their mix proportions. To optimize design-based mortar compositions for specific applications, response models are frequently applied to data collected from scientific approaches. Here, experimental dataset regarding to a design of experiments carried out in mortars through a central composite design with five independent variables is presented. Among the five independent variables, four were quantitative ones: Water(v)/Cement(v), Superplasticyzer(m)/Powder(v), Water(v)/Powder(v), Sand(v)/Mortar(v). The other independent variable was a qualitative one: Superplasticiser A or Superplasticiser B. In total 60 mortar compositions were done: for each qualitative variable a 2(4) factorial design comprising of 16 treatment combinations enlarged by 8 axial runs plus 6 central runs, resulting in a central composite design with 30 mortar trial mix compositions. The following dependent variables were tested: the D-flow and the t-funnel to evaluate the fresh properties and the compressive at the age of 24 h and at the age of 28 days to evaluate the hardened properties. Based on this dataset, response models can be applied to find optimized mix compositions, with the effect of the two qualitative variables being determined. Elsevier 2021-12-21 /pmc/articles/PMC8717463/ /pubmed/35005136 http://dx.doi.org/10.1016/j.dib.2021.107738 Text en © 2021 Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Maia, Lino
Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title_full Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title_fullStr Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title_full_unstemmed Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title_short Experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
title_sort experimental dataset from a central composite design with two qualitative independent variables to develop high strength mortars with self-compacting properties
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717463/
https://www.ncbi.nlm.nih.gov/pubmed/35005136
http://dx.doi.org/10.1016/j.dib.2021.107738
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