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...
Saved in:
Main Authors: | Kenichi Ishihara, Hayato Kitagawa, Yoichi Takagishi, Toshiyuki Meshii |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/6877efa5a65d4c2f999a2270a37b7b39 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
XFEM Simulation of Tensile and Fracture Behavior of Ultrafine-Grained Al 6061 Alloy
by: Saurabh Gairola, et al.
Published: (2021) -
Preparation of Multiscale α Phase by Heat Treatments and Its Effect on Tensile Properties in Metastable β Titanium Alloy Sheet
by: Hanyu Jiang, et al.
Published: (2021) -
Brittle failure criteria of CNRB specimen for fracture toughness test
by: Manato KANESAKI, et al.
Published: (2020) -
A significant toughness enhancement, and microstructural evolution of an electric resistance welded (ERW) microalloyed steel
by: S.H. Mousavi Anijdan, et al.
Published: (2021) -
Variations of fracture toughness and stress-strain curve of cold worked stainless steel and their influence on failure strength of cracked pipe
by: Masayuki KAMAYA
Published: (2016)