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.

본 논문에서는 Russell (1980)의 감정차원 모델(Circumplex Model)을 확장하여 새로운 감정차원 모델링 방식을 제안한다. 기존의 감정차원 중 가장 대표적인 Russell의 모델은 각성(Arousal), 정서가(Valence)의 2개의 축을 이용하여 감정을 나타낸다. 하지만 기존의 연구에서는 Russell의 감정차원은 감정을 하나의 점으로만 표현하기 때문에 정확한 위치라고 할 수 없으며 감성과학, HCI, Ergonomics 등의 공학 분야에서 사용하기 어렵다고 주장하였다. 따라서 본 논문에서는 Russell의 감정차원 위에 감정들을 하나의 점으로 표현하지 않고, 데이터 분포를 가정하여 영역으로 표현하 는 방법을 제안한다. 실제 설문을 진행하여 자료를 수집하였고, 타원의 방정식을 이용하여 영역을 수식화하였다. 또한, 마지막 장에서 실제 많은 연구에서 사용되는 ANEW와 IAPS 데이터를 패턴인식 알고리즘을 통해 본 논문에서 제안한 모델에 적용해 보았다. 본 논문에서는 새로운 모델링 방법을 통해 기존의 연구자들에게 지적된 Russell 모델의 문제점을 보완하고, 이 모델을 공학 분야에서도 쉽게 적용할 수 있었다.

This paper addresses capacity expansion planning model of distribution center under usability of public distribution center. For discrete and finite time periods, demands for distribution center increase dynamically. The capacity expansion planning is to

Distribution centers in a distribution system that consists of the distribution centers and retailers supplies products to retailers. At the present, although total capacity of the distribution centers are enough to supply total demand of retailers, capac

We amplified D1 and D3 expansion segments of the 28S ribosomal RNA from 10 Suanguina moxae populations found in Korea. The amplification of the D1-D3 expansion segments of 28S gene of all populations tested produced a single PCR product approximately 1.03kb in size, suggesting the lack of D1-D3 expansion region size polymorphism among populations. The secondary structure model of 28S expansion segments D2 and D3 for Subanguina Moxae was predicted based on free energy minimization with comparative sequence analysis and new sequence alignment was conducted based on predicted secondary structure model. The predicted model was compared with previous predicted models of plant and animal parasite nematode. This predicted secondary structure model will provide valuable information to allocate positional sequence homology and reconstruction of reliable phylogenetic trees.