Abstract
Machine Learning Prediction of Creep Rupture Time for Steels
Highlights
It is considered that the information about the microstructure is essential to predict the creep rupture time
We examined how modern machine learning technique can help to predict the creep rupture time in heat-resistant ferrite-type steels without the direct information about the microstructures and the process by using the high-quality experimental data generated in NIMS
The descriptors were here chemical composition expressed by each mass percent of 20 elements including Fe and test conditions such as creep stress and temperature
Summary
Machine Learning Prediction of Creep Rupture Time for Steels Masahiko Demura1,*, Junya Sakurai1,2, Masayoshi Yamazaki1 and Junya Inoue1,2 Abstract: Creep is a complicated and time-dependent phenomenon, which is affected by the initial state and the degradation of microstructures.
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