Model constants for ECC-strengthened RC beam load capacity prediction
Description
This dataset provides the complete set of model constants (coefficients) of the multivariate regression equation derived in this study (Eq. 3), which was developed to predict the load-carrying capacity (LC) of engineered cementitious composite (ECC)-strengthened reinforced concrete (RC) beams. The constants were obtained through a data-driven modeling framework integrating an experimental database of 271 beam specimens compiled from 32 published sources in the literature. The dataset is organized in Microsoft Excel format and includes the fitted coefficients corresponding to each of the 13 input variables considered in the model, namely: compressive strength (CS), beam width (WB), beam depth (DB), span length (SL), shear span-to-depth ratio (SD), steel reinforcement ratio (RI), ECC tensile strength (TS), ECC ultimate strain (US), ECC strain capacity (SR), steel yield strength (YS), steel cross-sectional area (AS), steel yield strength of longitudinal bars (YB), and ECC layer thickness (TC). These constants enable direct application of Eq. (3) for predicting LC without requiring access to the full machine learning pipeline. This dataset is intended to support reproducibility, transparency, and practical application of the proposed predictive model by researchers and practitioners in structural and materials engineering.