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What is ML Prediction of Fracture Toughness about?

This study introduces a machine learning model using support vector regression to predict the fracture toughness of large-scale quasi-brittle materials based on small specimen data. The model, trained on 321 unique data points, demonstrates approximately 91% accuracy in predicting fracture toughness for new materials and configurations. The research addresses the limitations of traditional methods by providing a data-driven approach that requires minimal experimental input.

Author

Fahime Abiri

Language

EN