Machine learning-based prediction of ductility of strain-hardening fiber-reinforced cementitious composites

Puntos clave

• The prediction focuses on ductility, a key property for performance in structural applications.
• Machine learning algorithms assess the strain-hardening behavior based on various composite parameters.
• A systematic approach was used to evaluate the effectiveness of different composite formulations.
• Findings may enable optimized designs for construction materials improving overall structural integrity.