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

Description

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.

Steps to reproduce

The dataset was developed through a systematic literature review following the PRISMA methodology. A comprehensive literature search was conducted in early April 2025 using the Boolean query (“iron ore tailing” OR “iron ore processing” OR “iron tailing”) AND (concrete) across Scopus, Web of Science, ScienceDirect, and MDPI, with supplementary searches in Google Scholar (title-only) and Google (PDF files only) to identify grey literature. No restrictions were applied on publication date, language, or document type during the database search. All retrieved records were imported into EndNote 21 for deduplication and screening. After applying predefined inclusion and exclusion criteria, 21 eligible studies comprising 153 concrete mixtures were retained. Experimental data were manually extracted, while numerical values reported only in graphical form were digitized using GetData Graph Digitizer and cross-validated against tabulated data. Missing critical information was recovered, where possible, through direct communication with the original authors. The compiled data were organized and cleaned in Microsoft Excel and standardized following the procedures described in the accompanying manuscript, including normalization of fineness modulus, binder definition, and conversion of compressive strength values to the equivalent 150 mm concrete cube before final quality control.

Institutions

• University of Tehran

  Tehran, Tehran

Categories

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