화력발전소 구조물 중 하나인 보일러 강구조물은 물탱크가 올라가게 되는 중요한 설비지만 그 중요성이 비해 지진에 대한 안전성 평가에 대한 연구가 미비하다. 본 연구에서는 취약도 곡선을 도출하고자 16개의 지진파에 12개의 PGA값을 선정하고 포 항지진을 포함해 총 200회의 동적 비선형 해석을 수행하였다. 강재의 인장, 압축응력과 강구조물의 상대변위를 측정하였다. 강재 재료적 특성의 경우 변형은 발생하였으나 파괴는 발생하지 않았고, 상대변위의 경우 한계점에 못 미치는 변위가 발생하였다. 취약도 곡선 도출결과 국내의 지진구역 구분 및 지역계수를 기준으로 강재의 재료적 변형(400MPa)에서는 인장이 38%, 압축이 62.5%로 변형이 발생하였고, 상대변위는 0%의 확률로 한계점을 넘었다. 이러한 보일러 강구조물에 대한 취약도 곡선은 대상구조물에 대한 한 계상태를 판별하는 정량적 근거와 지진에 대한 안전설계시 활용될 수 있다.

In this study, we propose a new scheme of nonlinear analysis for Incheon International Airport Terminal-2 which was opened on January of 2018 for the Olympic Winter Games of PyeongChang in South Korea. The terminal was built by a single layered irregular space frame. It has hard problems for nonlinear analysis geometrically, because of a limitation of personal computer's ability by the number of rigid joints in the roof. Therefore we attempt easier approach to be chosen a center part of the roof instead of the whole structure, and to substitute the other boundary parts as springs. The scheme shows some merits for saving memory and calculation time and so on.

하천의 생태 환경적인 측면을 고려하여 여러 가지 친환경적인 호안공법이 적용되어 시공되는 사례가 증가하고 있다. 친환경적인 호안공법으로는 식생공이 대표적이나 중량물을 시공하는 호안공법과 달리 식생매트를 고정핀으로 고정하는 방식의 식생매트와 같은 호안공법의 경우 중량물을 설계하는 여타의 공법과 달리 적합한 설계방법이 없어 경험적인 방법을 통해서 제 품의 개발과 시공이 이루어지고 있는 실정이다. 따라서 본 연구에서는 식생매트공법에 사용되는 고정핀과 고정핀이 정착된 지반을 모델링하고 유한요소법을 활용하여 호안식생매트의 안전성을 평가하였다. 해석결과 핀의 상단 부분에서 인발에 저항하기 위해 인장응력이 유발되고 있으며, 헤드 부분은 거의 응력이 작용하지 않는 것으로 나타났고, 핀의 Von Mises 응력값이 인장강 도에 비해 낮게 나타나 파괴모드가 재료 자체의 항복 또는 파쇄에 의한 파괴가 아닌 핀과 지반사이의 뽑힘이 전체 거동을 지배 한다고 평가하였다. 본 연구는 유한요소법을 통해서 식생매트공법의 안전성을 변위와 발생응력에 대하여 평가하였다.

There has been considerable recent interest in deep learning techniques for structural analysis and design. However, despite newer algorithms and more precise methods have been developed in the field of computer science, the recent effective deep learning techniques have not been applied to the damage detection topics. In this study, we have explored the structural damage detection method of truss structures using the state-of-the-art deep learning techniques. The deep neural networks are used to train knowledge of the patterns in the response of the undamaged and the damaged structures. A 31-bar planar truss are considered to show the capabilities of the deep learning techniques for identifying the single or multiple-structural damage. The frequency responses and the elasticity moduli of individual elements are used as input and output datasets, respectively. In all considered cases, the neural network can assess damage conditions with very good accuracy.

In order to increase the seismic safety of nuclear power plant (NPP) structures, a technique to reduce the seismic load transmitted to the NPP structure by using a seismic isolation device such as a lead-rubber bearing has recently been actively researched. In seismic design of NPP structures, three directional (two horizontal and one vertical directions) artificial synthetic earthquakes (G0 group) corresponding to the standard design spectrum are generally used. In this study, seismic analysis was performed by using three directional artificial synthetic earthquakes (M0 group) corresponding to the maximum-minimum spectrum reflecting uncertainty of incident direction of earthquake load. The design basis earthquake (DBE) and the beyond design basis earthquakes (BDBEs are equal to 150%, 167%, and 200% DBE) of G0 and M0 earthquake groups were respectively generated for 30 sets and used for the seismic analysis. The purpose of this study is to compare seismic responses and seismic fragility curves of seismically isolated NPP structures subjected to DBE and BDBE. From the seismic fragility curves, the probability of failure of the seismic isolation system when the peak ground acceleration (PGA) is 0.5 g is about 5% for the M0 earthquake group and about 3% for the G0 earthquake group.

In the precedent study, the retractable-roof spatial structure was selected as the analytical model and a tuned mass damper (TMD) was installed to control the dynamic response for the earthquake loads. Also, it is analyzed that the installation location of TMD in the analytical model and the optimal number of installations. A single TMD mass installed in the analytical model was set up 1% of the mass of the whole structure, and the optimum installation location was derived according to the number of change. As a result, it was verified that most effective to install eight TMDs regardless of opening or closing. Thus, in this study, eight TMDs were installed in the retractable-roof spatial structure and the optimum mass ratio was inquired while reducing a single TMD. In addition, the optimum mass distribution ratio was identified by redistributing the TMD masses differently depending on the installation position, using the mass ratio of vibration control being the most effective for seismic load. From the analysis results, as it is possible to confirm the optimum mass distribution ratio according to the optimum mass ratio and installation location of the TMD in the the retractable-roof spatial structure, it can be used as a reference in the TMD design for large space structure.