Dataset for SCF Prediction in CFST T- and K-Joints Using ANN

This dataset comprises numerical investigation data for Concrete-Filled Steel Tube (CFST) T- and K-joints, sourced from studies by Zheng et al. (2018) and Zheng et al. (2019). The dataset includes key geometric and material parameters influencing the Stress Concentration Factor (SCF). Additionally, a sample Python script implementing an Artificial Neural Network (ANN) model is provided to predict the SCF at the Brace Saddle (BS) of a CFST T-joint subjected to compressive loading in the brace.

This dataset is useful for researchers conducting numerical and machine learning-based studies on SCF behavior in CFST joints.

Keywords
Concrete Filled Steel Tubular K joints, Concrete Filled Steel Tubular T joint , Stress Concentration Factor, Finite Element Analysis, Artificial Neural Network, Multiple Regression Analysis