Dataset Information

Data on mixing and curing methods effects on the compressive strength of concrete.

ABSTRACT: Curing, though important is sometimes underrated in concrete production. This dataset provided shows the effects of four (4) different methods of curing on two distinct mix ratios. The data provided in this article are for a study that was conducted on one hundred and sixty (160) cube samples of mix ratios 1:2:4 and 1:1.5:3 while employing four (4) different methods of curing. The data given in the article displays the finding of the study. The findings can aid in prediction and optimization of concrete behavior and compressive strength when any of the curing methods are utilized.

SUBMITTER: Omuh IO

PROVIDER: S-EPMC5996499 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Data on mixing and curing methods effects on the compressive strength of concrete.

Omuh Ignatius O IO Mosaku Timothy O TO Joshua Opeyemi O Ojelabi Rapheal A RA Amusan Lekan M LM Afolabi Adedeji O AO Arowolo Adeoluwa O AO

Data in brief 20180327

Curing, though important is sometimes underrated in concrete production. This dataset provided shows the effects of four (4) different methods of curing on two distinct mix ratios. The data provided in this article are for a study that was conducted on one hundred and sixty (160) cube samples of mix ratios 1:2:4 and 1:1.5:3 while employing four (4) different methods of curing. The data given in the article displays the finding of the study. The findings can aid in prediction and optimization of ...[more]

PMID: 29900253

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Project description:Geopolymer concrete is an inorganic concrete that uses industrial or agro by-product ashes as the main binder instead of ordinary Portland cement; this leads to the geopolymer concrete being an eco-efficient and environmentally friendly construction material. A variety of ashes used as the binder in geopolymer concrete such as fly ash, ground granulated blast furnace slag, rice husk ash, metakaolin ash, and Palm oil fuel ash, fly ash was commonly consumed to prepare geopolymer concrete composites. The most important mechanical property for all types of concrete composites, including geopolymer concrete, is the compressive strength. However, in the structural design and construction field, the compressive strength of the concrete at 28 days is essential. Therefore, achieving an authoritative model for predicting the compressive strength of geopolymer concrete is necessary regarding saving time, energy, and cost-effectiveness. It gives guidance regarding scheduling the construction process and removal of formworks. In this study, Linear (LR), Non-Linear (NLR), and Multi-logistic (MLR) regression models were used to develop the predictive models for estimating the compressive strength of fly ash-based geopolymer concrete (FA-GPC). In this regard, a comprehensive dataset consists of 510 samples were collected in several academic research studies and analyzed to develop the models. In the modeling process, for the first time, twelve effective variable parameters on the compressive strength of the FA-GPC, including SiO2/Al2O3 (Si/Al) of fly ash binder, alkaline liquid to binder ratio (l/b), fly ash (FA) content, fine aggregate (F) content, coarse aggregate (C) content, sodium hydroxide (SH)content, sodium silicate (SS) content, (SS/SH), molarity (M), curing temperature (T), curing duration inside ovens (CD) and specimen ages (A) were considered as the modeling input parameters. Various statistical assessments such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Scatter Index (SI), OBJ value, and the Coefficient of determination (R2) were used to evaluate the efficiency of the developed models. The results indicated that the NLR model performed better for predicting the compressive strength of FA-GPC mixtures compared to the other models. Moreover, the sensitivity analysis demonstrated that the curing temperature, alkaline liquid to binder ratio, and sodium silicate content are the most affecting parameter for estimating the compressive strength of the FA-GPC.

Dataset Information

Data on mixing and curing methods effects on the compressive strength of concrete.

Publications

Data on mixing and curing methods effects on the compressive strength of concrete.

Similar Datasets

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