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openalexMendeley Data2026-07-23Cited by 0

Curated Dataset of Concrete Mixtures Incorporating Iron Ore Tailings as Fine Aggregate for Systematic Review and Interpretable Data-Driven Modeling

sadra cheraghi

This dataset contains a curated collection of 153 concrete mixtures compiled from 21 peer-reviewed international studies investigating the use of iron ore tailings (IOT) as fine aggregate in concrete. The dataset was developed through a systematic literature review and standardized to ensure consistency across different experimental programs. The dataset includes ten predictor variables: the chemical composition of iron ore tailings (SiO₂, Al₂O₃, Fe₂O₃, and CaO, expressed as mass percentage), the physical fineness modulus (FM) of the tailings, water-to-binder (w/b) ratio, Portland cement content, iron ore tailings content, fine aggregate content, and coarse aggregate content (all expressed in kg/m³). The target variable is the 28-day compressive strength of concrete (MPa). To improve cross-study consistency, all Portland cement types were treated as equivalent, supplementary cementitious materials (SCMs) were incorporated into the total binder content for w/b ratio calculations, fineness modulus values were standardized according to ASTM C33 sieve sizes, and all compressive strength results were converted to the equivalent strength of a 150 mm concrete cube using standardized conversion procedures. Missing numerical data were recovered through figure digitization and direct communication with the original study authors whenever necessary. This dataset supports transparent data-driven modeling, systematic review studies, sensitivity analysis, and the development of interpretable machine learning models for sustainable concrete containing iron ore tailings.

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