• 대한기계학회논문집A
• /
• 제28권11호
• /
• pp.1741-1751
• /
• 2004

It is commonly requested that the steam generator tubes wall-thinned in excess of 40% should be plugged. However, the plugging criterion is known to be too conservative for some locations and types of defects and its application is limited to a single crack in spite of the fact that the occurrence of multiple through-wall cracks is more common in general. The objective of this research is to propose the optimum failure prediction models for two adjacent through-wall cracks in steam generator tubes. The conservatism of the present plugging criteria was reviewed using the existing failure prediction models for a single crack, and six new failure prediction models for multiple through-wall cracks have been introduced. Then, in order to determine the optimum ones among these new local or global failure prediction models, a series of plastic collapse tests and corresponding finite element analyses for two adjacent through-wall cracks in thin plate were carried out. Thereby, the reaction force model, plastic zone contact model and COD (Crack-Opening Displacement) base model were selected as the optimum ones for assessment of steam generator tubes with multiple through-wall cracks. The selected optimum failure prediction models, finally, were used to estimate the coalescence pressure of two adjacent through-wall cracks in steam generator tubes.

• 대한기계학회논문집A
• /
• 제29권5호
• /
• pp.754-761
• /
• 2005

The 40\% of wall thickness criterion which has been used as a plugging rule of steam generator tubes is applicable only to a single cracked tube. In the previous studies performed by authors, several global failure prediction models were introduced to estimate the failure loads of steam generator tubes containing two adjacent parallel axial through-wall cracks. These models were applied for thin plates with two parallel cracks and the COD base model was selected as the optimum one. The objective of this study is to verify the applicability of the proposed optimum global failure prediction model for real steam generator tubes with two parallel axial through-wall cracks. For the sake of this, a series of plastic collapse tests and finite element analyses have been carried out fur the steam generator tubes with two machined parallel axial through-wall cracks. Thereby, it was proven that the proposed optimum failure prediction model can be used as the best one to estimate the failure load quite well. Also, interaction effects between two adjacent cracks were assessed through additional finite element analyses to investigate the effect on the global failure behavior.

• 지질공학
• /
• 제30권4호
• /
• pp.663-671
• /
• 2020

최근 국내에서는 산림지역 뿐만 아니라 대도시지역에서도 자연재해가 많이 발생하고 있으며, 이에 대한 국가적인 요구사항은 증가하고 있다. 특히 국도 비탈면 붕괴에 대하여 체계적으로 관리할 수 있는 사전 재해정보 시스템은 전무한 실정이다. 본 연구에서는 CSMS(Cut Slope Management System)에서 관리하는 강원도와 경상도 지역의 국도 비탈면 붕괴 정밀조사 보고서와 비탈면 기초조사를 토대로 비탈면 붕괴 유발 인자에 대한 빅데이터 분석을 실시하였다. 분석 결과를 바탕으로 붕괴 비탈면 위치와 기상정보를 반영하여 분류 기반 머신러닝 모형인 Adaboost를 통한 비탈면 붕괴 위험도 예측모형을 구축하였다. 또한 시각화 프로그램인 비탈면 붕괴 위험도 시각화 지도를 개발하여 기상여건 변화에 따른 비탈면 위험도 파악을 통한 선제적 재해재난 예방대책에 활용할 수 있음을 보여주고 있다.

• Nuclear Engineering and Technology
• /
• 제44권3호
• /
• pp.323-330
• /
• 2012

The development of data-based models requires uncertainty analysis to explain the accuracy of their predictions. In this paper, an uncertainty analysis of the support vector regression (SVR) model, which is a data-based model, was performed because previous research showed that the SVR method accurately estimates the collapse moments of wall-thinned pipe bends and elbows. The uncertainty analysis method used in this study was an analytic uncertainty analysis method, and estimates with a 95% confidence interval were obtained for 370 test data points. From the results, the prediction interval (PI) was very narrow, which means that the predicted values are quite accurate. Therefore, the proposed SVR method can be used effectively to assess and validate the integrity of the wall-thinned pipe bends and elbows.

• 한국지반공학회논문집
• /
• 제32권2호
• /
• pp.5-17
• /
• 2016

터널에서의 붕괴는 터널 구조물의 특수성 및 예상치 못한 지반조건의 변화로 인해 언제 어디서든 발생될 수 있다. 그로 인한 경제적인 손실과 인명피해를 줄이기 위하여 사고를 미연에 방지하기 위한 방안에 대한 다양한 연구들이 계속 진행되고 있는 실정이다. 본 연구에서는 붕괴예측을 위하여 국내 터널 붕괴 현장 56개소의 시공데이터를 분석하고 인공신경망 기법에 적용할 입력인자를 민감도 분석으로 선정하였다. 또한 인공신경망 모델 설계는 선정된 입력인자로 학습을 수행하고 터널 붕괴 유형 예측에 최적화된 모델을 결정하였다. 이 모델을 이용하여 붕괴가 발생된 총 12개소에 적용성 평가를 실시하여 터널 붕괴 유형 예측 가능성을 검증하였다. 이러한 결과는 터널 시공 현장에서 붕괴 예방을 위한 기초 자료로서 활용 될 수 있을 것이다.

• Earthquakes and Structures
• /
• 제11권5호
• /
• pp.779-807
• /
• 2016

Ground Motion Prediction Equations (GMPEs) are essential tools in seismic hazard analysis. With the introduction of probabilistic approaches for the estimation of seismic response of structures, also known as, performance based earthquake engineering framework; new tasks are defined for response spectrum such as the reference criterion for effective structure-specific selection of ground motions for nonlinear time history analysis. One of the recent efforts to introduce a high quality databank of ground motions besides the corresponding selection scheme based on the broadband spectral consistency is the development of SIMBAD (Selected Input Motions for displacement-Based Assessment and Design), which is designed to improve the reliability of spectral values at all natural periods by removing noise with modern proposed approaches. In this paper, a new global GMPE is proposed by using selected ground motions from SIMBAD to improve the reliability of computed spectral shape indicators. To determine regression coefficients, 204 pairs of horizontal components from 35 earthquakes with magnitude ranging from Mw 5 to Mw 7.1 and epicentral distances lower than 40 km selected from SIMBAD are used. The proposed equation is compared with similar models both qualitatively and quantitatively. After the verification of model by several goodness-of-fit measures, the epsilon values as the spectral shape indicator are computed and the validity of available prediction equations for correlation of the pairs of epsilon values is examined. General consistency between predictions by new model and others, especially, in short periods is confirmed, while, at longer periods, there are meaningful differences between normalized residuals and correlation coefficients between pairs of them estimated by new model and those are computed by other empirical equations. A simple collapse assessment example indicate possible improvement in the correlation between collapse capacity and spectral shape indicators (${\varepsilon}$) up to 20% by selection of a more applicable GMPE for calculation of ${\varepsilon}$.

• Structural Engineering and Mechanics
• /
• 제23권2호
• /
• pp.177-193
• /
• 2006

Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

• 터널과지하공간
• /
• 제10권1호
• /
• pp.33-44
• /
• 2000

이 연구에서는 지하공동의 점진적인 붕락이 지표침하에 미치는 영향을 조사하기 위하여, 주문진산 표준사를 이용하여 모형지반을 구성하였으며, 공동의 심도를 달리하는 6가지 모델에 대하여 실내 모형실험을실시하였다. 여기서 공동의 심도와 붕락구간의 크기에 따른 침하발생양상을 조사하였다. 또한 NCB 방법, 지수함수를 이용한 윤곽함수법 영향함수법 등의 침하예측방법을 이용하여 모형실험으로부터 측정된 수직 및 수평변위를 해석하였으며, 모래지반에 적합한 침하예측방법을 제안하였다.

• 해양환경안전학회지
• /
• 제20권2호
• /
• pp.218-227
• /
• 2014

본 연구에서는 실험 모형을 이용한 탄소성 대변형 시리즈 해석을 수행하여 플레이트 거더의 파손모드와 최종하중을 예측하였다. 수치해석 모형의 붕괴모드는 재하 시 플랜지에서 소성 힌지가 형성되었으며 실험모형의 붕괴모드와 일치하였다. 또한, 웹에서 항복선이 형성되어 크리플링 붕괴모드가 발생하는 것을 관찰할 수 있었으며 각각의 실험모형과 수치모형 최종하중의 평균값 1.07, 표준편차 0.04, 변동계수 0.04로 선형성을 유지하였으며 전체 최종하중 결과도 대략 8 % 오차를 나타내었다. 이는 수치모형 결과가 실험 및 적용 기준에 매우 만족하고 양호한 결과를 도출하였다고 생각한다. 따라서 알루미늄합금 플레이트 거더의 최종하중 예측 시 실험 및 적용 기준과 함께 병행하여 적용을 한다면 이에 대한 합리적 안전수준을 유지한다면 더 효율적이고 경제적 알루미늄 합금 플레이트 거더의 파손모드 및 최종하중에 대해 예측할 수 있을 거라고 생각한다.

• 한국농공학회논문집
• /
• 제59권5호
• /
• pp.101-108
• /
• 2017

Recently, the occurrence of landslides has been increasing over the years due to the extreme weather event. Developments of landslides monitoring technology that reduce damage caused by landslide are urgently needed. Therefore, in this study, a strain ratio sensor was developed to predict the ground behavior during the slope failure, and the change in surface ground displacement was observed as slope failed on the field model experiment. As a result, in the slope failure, the ground displacement process increases the risk of collapse as the inverse displacement approaches zero. It is closely related to the prediction of precursor. In all cases, increase in displacement and reverse speed of inverse displacement with time was observed during the slope failure, and it is very important event for monitoring collapse phenomenon of risky slopes. In the future, it can be used as disaster prevention technology to contribute in reduction of landslide damage and activation of measurement industry.