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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Geometry‑Harmonized Fly‑Ash based Alkali‑Activated Concrete Dataset for Data‑Driven Modelling

Authors: Safhi, Amine el Mahdi; Pilehvar, Shima; Kioumarsi, Mahdi;

Geometry‑Harmonized Fly‑Ash based Alkali‑Activated Concrete Dataset for Data‑Driven Modelling

Abstract

Overview This repository contains a harmonized compilation of about 800 fly‑ash alkali‑activated concrete (FA‑AAC) mix designs extracted from 67 peer-reviewed publications & the open-access parent dataset created by Torres et al. (1 630 mixes, ref. [70-71] in the bibliography). Single precursor & activator: Only fly ash as binder precursor & NaOH(aq) as activator. Geometry-normalized strengths: All compressive strengths have been converted to the equivalent 150 × 300 mm cylinder value using ACI 318‑19 & CEB‑FIP factors; raw values are preserved for traceability. Rich feature set: Binder oxide chemistry, activator properties, mix proportions, fresh & hardened properties, curing regime, & CO₂ footprint, besides a statistical overview. Bibliographic traceability: Complete bibliography of the 67 papers included. Deliverables: Tidy CSV & README—ready for ML modeling, meta‑analysis, & low‑carbon mix benchmarking. Value of the Data Provides the first openly shared, geometry-harmonized collection of FA-AAC mixes, eliminating specimen-geometry bias via size normalization. Serves researchers developing machine‑learning or optimization models by pairing full mix parameters with cylinder‑equivalent compressive strengths. Supply a ready-to-model table of mix designs & properties. Offers industry professionals an objective benchmark for screening low‑carbon, FA‑only AAC formulations. Fulfills FAIR principles by supplying a tidy CSV file & a complete bibliography—facilitating reproducibility, reuse, & future extensions. Data description (#Features) Statistical overview (#7): Number of data, minimum & maximum value, 10th & 90th percentile, average value, & standard deviation. Identification features (3 features): number of the mixture, references, & the mixture code. Fly ash properties (#18): the dosage, specific density, & the chemical composition including the sum of the pozzolanic oxides & the Si/Al ratio. Aggregate properties (#7): Content & density of fine & coarse aggregates, the total aggregate, the fine-to-total-aggregate ratio, & the binder-to-total-aggregate ratio. Alkali-activator content & concentration (#18): Properties of Na₂SiO₃ & NaOH including content, composition, concentration & specific density. Besides, some significant ratios, such as Na₂O/SiO₂ ratio, liquid/solid ratio, activator-to-binder ratio, etc. Workability features (#8): including those related to mix design such as water, superplasticizer, water-to-binder ratio; slump flow, flow-table, & setting time. Curing features (#4): including initial & final curing time, initial & final curing temperature. Hardened properties (#39): This includes the sample dimensions, the original mechanical strengths for different cube & cylinder sizes, then the converted strengths to the equivalent 150 × 300 mm cylinder, the young modulus & porosity. CO2 footprint feature: in kg emission per 1m3 of samples produced & cured based on ref. [68-69] in the bibliography. Limitations Literature coverage stops at December 2023; newer FA‑AAC studies are not yet included. Size-effect factors are derived from OPC concrete; validation for very high‑Ca or ultra‑high‑strength mixes is advised. Non‑strength properties (workability, durability) appear only when reported by the original authors, resulting in sparse coverage. Ethics & competing interests The authors declare no competing financial interests.

Keywords

Machine Learning, Fly ash, Geopolymer, Alkali‑Activated Concrete

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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