Table 1 Dataset variables and characteristics.

From: Hybrid machine learning models for predicting the tensile strength of reinforced concrete incorporating nano-engineered and sustainable supplementary cementitious materials

Feature

Description

Unit

Range

Data type

Influence on tensile strength

Cement content

Mass of portland cement per unit volume of concrete

kg/m3

250–450

Continuous

Provides the primary binder; enhances strength

Water-to-cement ratio

Ratio of water to cement by mass

-

0.25–0.60

Continuous

Inversely affects strength and porosity

Fine aggregate

Sand content used in the mix

kg/m3

600–900

Continuous

Influences paste-aggregate bonding

Coarse aggregate

Crushed stone or gravel content

kg/m3

800–1200

Continuous

Affects interfacial transition zone properties

Nano-clay content

Nano-clay as a partial cement replacement

% of binder

0–5

Continuous

Enhances microstructure, reduces porosity

Basalt fiber content

Volume fraction of basalt fibers

%

0–3

Continuous

Improves tensile post-cracking capacity

Carbon nanotube content

CNTs added by weight of binder

%

0–1

Continuous

Increases tensile strength via nano-bridging

Geopolymer binder content

Percentage of geopolymer materials replacing cement (e.g., fly ash, GGBFS)

% of binder

0–30

Continuous

Reduces CO₂ footprint; may improve ductility

Curing duration

Age at which testing is performed

days

7, 14, 28, 56

Categorical

Directly correlated with strength gain over time

Superplasticizer content

Polycarboxylate-based admixture dosage by binder weight

%

0–2

Continuous

Enhances workability and dispersion of additives

Tensile strength

Splitting tensile strength (target output)

MPa

23.88–50.41

Continuous

Dependent on all input factors above

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