FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
| contributor author | Mahesh, S. | |
| contributor author | Anil Chandra, A. R. | |
| contributor author | Ravikumar, L. | |
| contributor author | Manjunatha, C. M. | |
| date accessioned | 2025-08-20T09:24:38Z | |
| date available | 2025-08-20T09:24:38Z | |
| date copyright | 5/13/2025 12:00:00 AM | |
| date issued | 2025 | |
| identifier issn | 0094-4289 | |
| identifier other | mats-24-1240.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4308233 | |
| description abstract | - | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning | |
| type | Journal Paper | |
| journal volume | 147 | |
| journal issue | 4 | |
| journal title | Journal of Engineering Materials and Technology | |
| identifier doi | 10.1115/1.4068534 | |
| journal fristpage | 41004-1 | |
| journal lastpage | 41004-12 | |
| page | 12 | |
| tree | Journal of Engineering Materials and Technology:;2025:;volume( 147 ):;issue: 004 | |
| contenttype | Fulltext |
