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

Read more

Summary

Introduction

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.

Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call