논문 상세보기
pp.63-70
Bellows expansion joints enhance the displacement performance of piping systems owing to their unique geometrical features. However, structural uncertainties such as wall thinning in convolutions, a byproduct of the manufacturing process, can impair their structural integrity. This study addresses such issues by conducting a global sensitivity analysis to assess the impact of these uncertainties on the performance of bellows expansion joints under monotonic loading. Global sensitivity analysis, which examines main and nth order interaction effects, is computationally expensive. To mitigate this, we employed a surrogate model-based approach using an artificial neural network. This model demonstrated robust prediction capabilities, as evidenced by metrics such as the coefficient of determination. The sensitivity indices of the main effect for the 2-ply and 3-ply bellows at the sixth convolution were 0.3340 and 0.3233, respectively. The sensitivity index of the sixth convolution was larger than that of other convolutions because the maximum deformation of the bellows expansion joint under monotonic bending load occurs around it. Interestingly, the sensitivity index for the interaction effect was negligible (0.01%) compared to the main effect, suggesting minimal activity between uncertainty factors across convolutions. Notably, bellows expansion joints under repetitive loading exhibit more complex behaviors, with the initial leakage typically occurring at the convolution. Therefore, future studies should focus on the structural uncertainties of bellows expansion joints under cyclic loading and employ a surrogate model for comprehensive global sensitivity analysis.
2. 다중적층 벨로우즈 신축이음관의 유한요소모델
2.1 단조 휨 하중 실험
2.2 유한요소 모델 구축 및 검증
3. 대리모델 기반 전역 민감도 분석 기법
3.1 전역 민감도 분석 기법
3.2 대리모델 구축 및 검증
4. 구조적 불확실성에 의한 전역 민감도 분석
4.1 2Ply 벨로우즈 신축이음관의 전역 민감도
4.2 3Ply 벨로우즈의 전역 민감도
5. 결 론
감사의 글
REFERENCES
