- 신경회로망을 이용한 AI 2024-T3합금의 피로손상예측에 관한 연구
- ㆍ 저자명
- 조석수,장득열,주원식,Cho. Seok-Swoo,Jang. Deuk-Yul,Joo. Won-Sik
- ㆍ 간행물명
- 한국정밀공학회지
- ㆍ 권/호정보
- 1999년|16권 7호|pp.168-177 (10 pages)
- ㆍ 발행정보
- 한국정밀공학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
Fatigue damage is the phenomena which is accumulated gradually with loading cycle in material. It is represented by fatigue crack growth rate da/dN and fatigue life ratio <TEXT>$N/N_{f}$</TEXT>. Fracture mechanical parameters estimating large crack growth behavior can calculate quantitative amount of fatigue crack growth resistance in engineering material. But fatigue damage has influence on various load, material and environment. Therefore, In this study, we propose that artificial intelligent fatigue damage model can predicts fatigue crack growth rate da/dN and fatigue life ratio <TEXT>$N/N_{f}$</TEXT> simultaneously using fracture mechanical and nondestructive parameters.