Material Parameters for Concrete-Filled Steel Tubes Under Axial Tension

Ten parametric models investigate the tensile performance of square concrete-filled steel tubular members. The dataset includes results from finite element simulations validated against six experimental specimens, with code comparisons and machine learning predictions. It was authored by Hongtao Zhang and last updated on June 1, 2026.

Use Cases

• Predicting ultimate tensile load based on confinement coefficient and slenderness ratio.
• Comparing finite element simulation results against experimental data and building code predictions.
• Training machine learning models like Random Forest on GAN-augmented structural performance data.

Strengths

• Finite element simulations were validated against six experimental specimens, with simulation-to-test ratios all below 0.95.
• Parametric analysis shows a clear relationship, with maximum load rising from 182 kN to 895 kN as the confinement coefficient increases from 0 to 0.99.
• Machine learning models trained on GAN-augmented data achieved high predictive accuracy, with R² scores of 0.997 and 0.9855 for ultimate load and displacement.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating a limited scope focused on a specific parametric study.

Provenance

Source

figshare

Collection Method

Data was generated from a three-dimensional mesoscopic finite element model based on experimental results, followed by parametric studies and machine learning predictions.

Freshness

Last updated 2026-06-01 17:33:26; freshness should be verified.