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Author

R. Hawileh

4 papers indexed here

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Sep 2026

MACHINE LEARNING PREDICTION OF TENSILE PROPERTIES OF ENGINEERED CEMENTITIOUS COMPOSITES

Engineered Cementitious Composites (ECC) exhibit exceptional strain-hardening behavior, yet predicting their tensile properties remains challenging due to complex nonlinear interactions among mix constituents and fiber characteristics. This study presents a comprehensive machine learning framework for predicting both t...

Amro A. Seifelnasr, M. A. Alhaj-Hussein, Jamal A. Abdalla et al. · 0 citations
Sep 2026

MACHINE LEARNING-BASED INVERSE DESIGN OF ECCENTRICALLY LOADED RECTANGULAR CONCRETE-FILLED STEEL TUBE (R-CFST) COLUMNS

Concrete-filled steel tubes (CFST) have been used in structural engineering due to the advantages of the ductility of steel and strength of concrete. While a large number of research studies are available for estimating the ultimate load capacity of the CFST cross-sections, the inverse problem of designing the optimum...

Hadia E. M. Ahmed, Jamal A. Abdalla, R. Hawileh · 0 citations
Open access Sep 2026

Machine learning and SHAP for predicting the shear contribution of FRP strengthening in beams

To address the identified research gaps, this study offers a strategy for forecasting the FRP shear contribution using seven supervised ML algorithms and Shapley Additive exPlainations (SHAP)—a novel black-box interpretation approach—was used to explain the predictions.

Zahira Sadoun, A. Elnemr, Farid Bouziadi et al. · 0 citations
Open access Sep 2026

Crack-Width Threshold-Guided Design of Self-Healing Polyethylene Fiber-Reinforced Engineered Cementitious Composites (ECCs)

Polyethylene (PE) fibers enable engineered cementitious composites (ECCs) to achieve tensile strain-hardening and multiple-cracking behavior through fiber bridging; however, the relatively large crack widths that can develop in PE fiber-reinforced high-strength ECC (HS-ECC) may limit its autogenous self-healing capabil...

Zhi-Gang Zhang, Xiang-Wen Lei, Jamal A. Abdalla et al. · 0 citations

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