Application of an Artificial Neural Network to Develop Fracture Toughness Predictor of Ferritic Steels Based on Tensile Test Results

Application of an Artificial Neural Network to Develop Fracture Toughness Predictor of Ferritic Steels Based on Tensile Test Results

Analyzing the structural integrity of ferritic steel structures subjected to large temperature variations requires the collection of the fracture toughness (<i>K<sub>J</sub></i><sub>c</sub>) of ferritic steels in the ductile-to-brittle transition region. Consequen...

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Autores principales: Kenichi Ishihara, Hayato Kitagawa, Yoichi Takagishi, Toshiyuki Meshii
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
fracture toughness
machine learning
artificial neural network
predictor
yield stress
tensile strength
Mining engineering. Metallurgy
TN1-997
Acceso en línea:https://doaj.org/article/6877efa5a65d4c2f999a2270a37b7b39
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https://doaj.org/article/6877efa5a65d4c2f999a2270a37b7b39

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