Work

FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning

Year: 2025

Type: article

Source: Journal of Engineering Materials and Technology

DOI: 10.1115/1.4068534

Authors: S. Mahesh, A. R. Anil Chandra, L. Ravikumar, C. M. Manjunatha

Institutions: B.M.S. College of Engineering, Council of Scientific and Industrial Research

Language: English

Topic: Fatigue and fracture mechanics

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4409785547

FWCI: 2.254

Cites: 45

Cited by: 7

Related to: 10