Reliability Assessment of Empirical Equations, ANN and MARS Models for Predicting the Mode I Fracture Toughness from Non-destructive Rock Properties

Highlights Mode I fracture toughness is highly imperative in various rock mechanics applications. Machine learning models are proposed for accurate prediction of mode I fracture toughness. The reliability assessment of the empirical equations and proposed models enables the selection of the most sui...

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Bibliographic Details
Published in:Rock mechanics and rock engineering 2023-08, Vol.56 (8), p.6157-6166
Main Authors: Lawal, Abiodun Ismail, Kwon, Sangki
Format: Article
Language:English
Subjects:
Civil Engineering
Datasets
Earth and Environmental Science
Earth Sciences
Empirical equations
Fracture toughness
Geophysics/Geodesy
Heat treating
Laboratories
Machine learning
Mathematical models
Mechanics
Reliability
Reliability analysis
Research methodology
Rock mechanics
Rock properties
Rocks
Technical Note
Toughness
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Summary:Highlights Mode I fracture toughness is highly imperative in various rock mechanics applications. Machine learning models are proposed for accurate prediction of mode I fracture toughness. The reliability assessment of the empirical equations and proposed models enables the selection of the most suitable among them. The reliability analysis revealed that some of the models assessed are unsuitable for fracture toughness prediction.
ISSN:0723-2632
1434-453X
DOI:10.1007/s00603-023-03345-9