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.

공력감쇠는 와류에 의한 풍직각방향의 응답을 평가하는데 매우 유용한 인자로 인식되어 왔다. 그러나 기존의 공력감쇠 산정 방식은 구조물 응답에 기반한 시스템 식별기술을 적용하는 것으로 와류하중속에 포함되어 있는 공력감쇠의 역할과 특성을 파악하는 데 한계를 가지고 있었다. 본 연구에서는 하중식별기술을 적용하여 와류하중을 직접적으로 구함으로써 와류하중을 구성하는 요소와 유발요인을 평가하고자 하였다. 이를 위하여 대기 경계층에서 원형 실린더 모델에 대한 공탄성 실험을 수행하여 풍직각방향 와류하중 을 추정하였으며 그로부터 공력감쇠의 특성을 분석하였다. 분석결과, 와류하중은 구조물 모달속도가 공력감쇠에 의해 풍하중으로 전 환되는 모달속도하중과 변동풍속에 의해 형성되는 순수 와류하중으로 구성되는 것으로 나타났다. 공력감쇠는 최상층 평균풍속에 의한 와류방출진동수가 구조물의 고유진동수에 근접하면서 부감쇠를 가지며 그 결과 총 감쇠가 작아져 응답증폭현상을 유발하는 것으로 파악되었다. 본 연구결과에 기초하면, 난류상태에서 와류하중 특성이 반영된 와류하중모델 구축이 가능할 것으로 사료되며, 구조물 풍직 각방향 진동을 보다 효과적으로 파악하는데 활용될 수 있을 것으로 사료된다.

이 연구는 사구 고정 구조물의 종류에 따라서 모래 퇴적속도, 형태, 퇴적량을 분석하여 해안복원 기초자료로 제공하기 위하여 수행되었다. 연구 대상지는 경상북도 포항시 북구 해안림이 조성된 해변 지역을 선정하였다. 계단식 옹벽과 퇴사울타리 설치 후 3년간(2014-2016) 모래퇴적을 모니터링하여 비교 분석하였다. 각 구조물의 모래퇴적을 분석한 결과, 평균 모래퇴적 높이는 계단식 옹벽이 퇴사울타리 보다 약 1.3배 더 퇴적되었다. 구조물의 풍속저감 효과는 0.5m 높이에서 계단식 옹벽이 43.3%, 퇴사울타리 32.2%로 나타났다. 이 연구의 결과는 앞으로 해안사구 조성 및 해안림 기반 조성의 기초자료로 활용될 것으로 기대된다.

The damage detection method using the extended Kalman filter(EKF) technique has been continuously used since EKF can estimation the responses of the damaged building structure and the stiffness of the structure. However, in the use of EKF, the requirement of setting the initial paramters P, Q, and R has caused the divergence and instability of the state vector, and various researches have been conducted to determine theses parameters. In this paper, adaptive extended Kalman filter(AEKF) method is proposed to solve the problem of setting the values of P, Q, and R, which are important parameters determining the convergence performance of the EKF state vector. By using the AEKF method proposed in this study, the P, Q, and R parameters are updated every k steps. The proposed algorithm is applied for the estimation of stiffness and the damage detection of 3-DOF problem. Based of the verification, it can be found that the selection process for the values of P, Q, and R can improve the convergence performance of EKF.

In this study, the seismic performance and behavior characteristics of the upper truss structure of the large stadium are analyzed by nonlinear dynamic analysis. In the nonlinear dynamic analysis, the earthquake records were generated by site response analysis to simulate the nonlinear behavior of the relevant soil condition where the structure is located. Nonlinear dynamic analysis was performed using Perform-3D and the nonlinear properties of the substructure and the superstructure were determined in accordance with KISTEC guideline. According to the analysis results, excessive deformation occurred in the upper truss element, and plastic hinges exceeded the target performance in some members. Buckling-restrained brace is used for seismic retrofit of stadium structures and the analysis results shows the interstory drift satisfies the target performance level with dissipating the seismic energy efficiently.

In this study, an algorithm applying deep learning to the truss structures was proposed. Deep learning is a method of raising the accuracy of machine learning by creating a neural networks in a computer. Neural networks consist of input layers, hidden layers and output layers. Numerous studies have focused on the introduction of neural networks and performed under limited examples and conditions, but this study focused on two- and three-dimensional truss structures to prove the effectiveness of algorithms. and the training phase was divided into training model based on the dataset size and epochs. At these case, a specific data value was selected and the error rate was shown by comparing the actual data value with the predicted value, and the error rate decreases as the data set and the number of hidden layers increases. In consequence, it showed that it is possible to predict the result quickly and accurately without using a numerical analysis program when applying the deep learning technique to the field of structural analysis.

In this study, a numerical approach based on mid-point integrated finite elements and a viscous boundary is proposed for time-domain wave-propagation analyses in infinite poroelastic media. The proposed approach is accurate, efficient, and easy to implement in time-domain analyses. In the approach, an infinite domain is truncated at some distance. The truncated domain is represented by mid-point integrated finite elements with real element-lengths and a viscous boundary is attached to the end of the domain. Given that the dynamic behaviors of the proposed model can be expressed in terms of mass, damping, and stiffness matrices only, it can be implemented easily in the displacement-based finite-element formulation. No convolutional operations are required for time-domain calculations because the coefficient matrices are constant. The proposed numerical approach is applied to typical wave-propagation and soil-structure interaction problems. The model is verified to produce accurate and stable results. It is demonstrated that the numerical approach can be applied successfully to nonlinear soil-structure interaction problems.

In this paper, we study the existing results of the structure-soil-structure interaction (SSSI) effect on seismic responses of structures and summarize important parameters. The parameters considered in this study are a combination of buildings in the power block of a nuclear power plant, the characteristics of earthquake ground motions and its direction, and the characteristics embedded under the ground. Based on these parameters, the seismic analysis model of the structures in the power block of the nuclear power plant is developed and the structure-soil-structure interaction analyses are performed to analyze the influence of the parameters on the seismic response. For all analyses, the soil-structure interaction (SSI) analysis program CNU-KIESSI, which was developed to enable large-sized seismic analysis, is used. In addition, the SSI analyses is performed on individual structures and the results are compared with the SSSI analysis results. Finally, the influence of the parameters on the seismic response of the structure due to the SSSI effect is reviewed through comparison of the analysis results.

As a method of seismic-design for pile-supported wharves, equivalent static analysis, response spectrum analysis, and time history analysis method are applied. Among them, the response spectrum analysis is widely used to obtain the maximum response of a structure. Because the ground is not modeled in the response spectrum analysis of pile-supported wharves, the amplified input ground acceleration should be calculated by ground classification or seismic response analysis. However, it is difficult to calculate the input ground acceleration through ground classification because the pile-supported wharf is build on inclined ground, the methods to calculate the input ground acceleration proposed in the standards are different. Therefore, in this study, the dynamic centrifuge model tests and the response spectrum analysis were carried out to calculate the appropriate input ground acceleration. The pile moment in response spectrum analysis and the dynamic centrifuge model tests were compared. As a result of comparison, it was shown that the response spectrum analysis results using the amplified acceleration in the ground surface were appropriate.

경량한 세장 구조물의 내풍안정성을 향상시키기 위하여 다양한 제진장치가 사용되어 왔다. 제진장치에 의하여 구조물에 부가되는 감쇠는 기존의 질량, 강성에 비례하는 고전감쇠와 달리 비고전 특성을 가진다. 비고전 감쇠는 복소의 모달 특성을 보유하기 때문에 해석과 평가과정에서 모드의 거동을 파악하기 어렵다. 이러한 이유 때문에 복소 모달 변수를 실수로 변경하기 위한 방법이 요구 되며, 변경된 실수 모달 특성이 가지는 물리적 의미를 고찰할 필요가 있다. 본 연구에서는 상태공간에서 비고전 감쇠시스템의 복소 모달 변수를 실수 모달 변수로 변경하는 과정을 소개하고 그 모달변수가 가지는 특성을 분석함으로써 비고전 감쇠를 가지는 구조물의 해석 및 평가가 보다 명쾌한 물리적 의미를 가지고 이루어질 수 있도록 하였다. 또한 비고전 감쇠구조물의 계측응답만으로 실수의 모달 특성을 추정할 수 있는 상태공간 기반 모드분해 기법에 대해서 다루고 그 특성을 비교 검증하였다. 본 연구에서 제시된 기법을 카고메 트러스 댐퍼가 설치된 비고전 감쇠 구조물에 적용하여 수치적으로 검증하였으며, 수치해석 결과로부터 복소 모드형상이 실수공간으로의 변환이 가능하며, 그 실수 모드형상이 계측응답만으로도 추정 가능함을 알 수 있었다.

본 연구에서는 옹벽 구조물의 내진성능 평가를 위해 2차원 유한요소 해석을 수행하였다. 2차원 유한요소 모델은 실제로 시공된 옹벽 구조를 기반으로 2차원 평면변형 요소로 모델링되었으며, 지반은 각각 유한요소와 무한요소로 모델링 하였다. 지진하중은 총 38개의 인공 지진을 생성하여 사용하였고, 생성된 인공 지진파를 11개의 PGA로 나누어 총 418회의 시간이력해석을 수행하였다. 수치해석 결과를 바탕으로 옹벽 구조물의 지진에 대한 취약도를 분석하였다. 취약도 분석 결과 콘크리트 및 철근의 취약도 곡선이 낮은 PGA 수준에서 급격히 변하는 것을 관찰할 수 있었다. 유한요소 해석 결과를 바탕으로 실제 현장의 옹벽 구조에서 상대적으로 낮은 수준의 지진파가 발생하더라도 높은 파괴확률로 인해 지진에 상대적으로 취약함을 확인하였다.

본 연구에서는 DVR 내부 공기유동을 직접 제어하여 CPU의 온도를 낮추기 위한 유동제어 구조물을 제안하였다. 제안된 구조물은 세 개의 얇은 판의 형태로 구성되었으며, DVR 내부의 공기 유동을 포괄적으로 제어하여 CPU의 효율적인 방열을 유도하고자 하였다. DOE와 RSM을 이용한 매개변수 연구기법을 통해 유동제어 구조물의 형상을 최적화하였으며, 해석에는 유한체적방법을 이용한 유체역학 분석 패키지인 FlowVision을 사용하였다. 실제 DVR 기기에서의 실험을 통해 해석 결과를 검증한 결과 CPU의 온도가 16.1℃ 낮아짐을 확인하였다

Laminated composite structures have started to play a very significant role in primary and secondary structural weight savings in high performance automobile industries. However, one of the main challenges in implementing these composites is the lack of understanding of the progress of the damage under various loading conditions. In order to understand the influence of design parameters related to the use of composite materials, a proper study of the laminated composite structures requires a complete failure analysis, which includes both initiation and propagation of damage. In this study, a new damage model was developed to predict the progressive damage of the composite, and the progress of damage was investigated by making center-notch and open-hole tensile test specimens for various lay-ups. The simulations, in agreement with experimental tests, indicate that the model is capable of predicting the failure load in open hole composite structures.

This paper describes a development of design tool for knowledge based engineering(KBE) that covers structural, aerodynamic, and optical analysis of large-scale telescope structures. A module of the commercial program Adaptive Modeling Language(AML) was used to develop a knowledge-based design tool that reflects the design of parameters for rapid design change and analysis. Through this study, it is proposed a design tool with a knowledge based engineering and a function based design technique. The knowledge based engineering design is good at frequent design changes, and it is effective to extract a core design behavior from previous designs. It is concluded that the developed tool can bring fair effects in implementing a time and cost-effective design environment.