A Data Science Framework for Predicting the Creep Rupture Life of 1.25Cr- 0.5Mo Steel for Elevated Temperature Applications

Computers, materials & continua/Computers, materials & continua (Print) 2026 Open access

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Authors: Muhammad Ishtiaq, Yeonwoo Kim, Sung-Gyu Kang, Nagireddy Gari Subba Reddy
DOI: 10.32604/cmc.2026.077416
Cited by: 0
References: 32

Abstract

The long-term reliability of 1.25Cr-0.5Mo steels in high-temperature service critically depends on their creep rupture behavior, which is strongly influenced by alloy composition, microstructural characteristics, and testing ... | Find, read and cite all the research you need on Tech Science Press

Fields of Study & Subjects

High Temperature Alloys and Creep Machine Learning in Materials Science Fatigue and fracture mechanics

Publication details

Journal / source
Computers, materials & continua/Computers, materials & continua (Print)
Volume
87
Issue
3
Pages
1–10
Publication date
1 January 2026
Language
EN