• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1995년도 가을 학술발표회 논문집
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• pp.334-338
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• 1995

In recent years, the prediction of the deterioration rate of concrete structures has become major research interest. However, there are still many uncertain factors in the deterioration process and the relation between deterioration and durability of structures. This is mainly due to various uncertainties involved in the construction process and the environmental conditions which affect the rate of deterioration of concrete structures. In this study a limit state model in terms of random crack width due to applied dead and live loads is proposed for the assessment of crack damage of reinforced concrete structures. The AFOSM reliability method is used for the reliability evaluation of the crack durability of concrete bridges. The proposed model for crack durability of concrete bridges is applied to the Seoul interior circuit elevated expressway. The sensitivity analyses are performed for the proposed model.

• Earthquakes and Structures
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• 제22권1호
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• pp.83-94
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• 2022

In recent years, some studies have identified and quantified factors that can increase or decrease the seismic vulnerability of buildings. These modifier factors, related to the building characteristics and condition, are taken into account in the vulnerability assessment, by means of a numerical estimation resulting from the quantification of these modifiers through vulnerability indexes. However, views have differed on the definition and the quantification of modifiers. In this study, modifier parameters and scores of the Risk-UE Level 1 method are adjusted based on the Algerian seismic code recommendations and the reviews proposed in the literature. The adjusted modifiers and scores are applied to reinforced concrete (RC) buildings in Boumerdes city, in order to assess probable seismic damage. Comparison between estimated damage and observed damage caused by the 2003 Boumerdes earthquake is done, with the objective to (i) validate the model involving influence of the modifier parameters on the seismic vulnerability, and (ii) to define the relationship between modifiers and damage. This research may help planners in improving seismic regulations and reducing vulnerability of existing buildings.

• Structural Engineering and Mechanics
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• 제51권3호
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• pp.447-470
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• 2014

Numerical simulation of the non-linear behavior of (RC) structural walls subjected to severe earthquake ground motions requires a reliable modeling approach that includes important material characteristics and behavioral response features. The objective of this paper is to optimize a simplified method for the assessment of the seismic response and damage development analyses of an RC structural wall building using macro-element model. The first stage of this study investigates effectiveness and ability of the macro-element model in predicting the flexural nonlinear response of the specimen based on previous experimental test results conducted in UCLA. The sensitivity of the predicted wall responses to changes in model parameters is also assessed. The macro-element model is next used to examine the dynamic behavior of the structural wall building-all the way from elastic behavior to global instability, by applying an approximate Incremental Dynamic Analysis (IDA), based on Uncoupled Modal Response History Analysis (UMRHA), setting up nonlinear single degree of freedom systems. Finally, the identification of the global stiffness decrease as a function of a damage variable is carried out by means of this simplified methodology. Responses are compared at various locations on the structural wall by conducting static and dynamic pushover analyses for accurate estimation of seismic performance of the structure using macro-element model. Results obtained with the numerical model for rectangular wall cross sections compare favorably with experimental responses for flexural capacity, stiffness, and deformability. Overall, the model is qualified for safety assessment and design of earthquake resistant structures with structural walls.

• 국토계획
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• 제53권6호
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• pp.117-130
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• 2018

Heavy snow is a natural disaster that causes serious economic damage. Since snowfall has been increasing recently, there is a need for measures against heavy snowfall. In order to make a policy decision on heavy snowfall, it is necessary to estimate the precise amount of damage by heavy snowfall. The direct damage of the heavy snow is severe, however the indirect damage caused by the road congestion and the urban dysfunction is also serious. Therefore, it is necessary to estimate indirect damage of snowfall. The purpose of this study is to estimate the effects on the regional economy from the limitation in traffic logistics caused by heavy snow using the transport demand model and inoperability input-output Model. The result shows that the amount of production loss caused by the heavy snow is KRW 2,460 billion per year and if the period of snowfall removal is shortened by one day or two days, it could be reduced to KRW 1,219 or 2,787 billion in production loss.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.1393-1394
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• 2004

• Smart Structures and Systems
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• 제31권5호
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• 한국강구조학회 논문집
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• 제11권1호통권38호
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• pp.79-88
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• 1999

신경망을 이용하여 강박스거더교의 손상을 평가하였다. 최근, 신경망을 이용한 손상평가는 구조공학분야에서 많은 연구가 진행되고 있다. 이것은 기존방법의 한계를 극복하고자 하는 새로운 시도로서 본 연구에서는 강교의 손상평가에 적용되었다. 신경망 학습을 위한 자료는 이동하중에 의한 교량의 가속도 응답으로부터 얻었다. 유한요소모델이 우선 정의되고 여기에 5, 10, 15 및 20%의 손상을 가정하였다. 평가단계에서는 학습한 손상은 물론 학습하지 않은 손상도 잘 감지하였다. 본 연구에서는 손상부위가 몇 개의 부위로 한정되었으며 현장의 적용을 위해서는 보다 많은 연구가 필요하다.

• Smart Structures and Systems
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• 제30권6호
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.

• Computers and Concrete
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• 제12권1호
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• pp.65-77
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• 2013

This paper examines the dynamic response of an arch dam subjected to blast loading. A damage model is developed for three dimensional analysis of arch dams. The modified Drucker-Prager criterion is adopted as the failure criteria of the damage evolution in concrete. Then, Xiluodu arch dam serves as an example to simulate the failure behaviors of structures with the proposed model. The results obtained using the proposed model can reveal the reliability degree of the safe operation level of the high arch dam system as well as the degree of potential failure, providing a reliable basis for risk assessment and risk control.

• Structural Engineering and Mechanics
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• 제52권6호
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• pp.1157-1176
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• 2014

The objective of this research is to develop a practical design and assessment approach of steel frames with steel slit walls (SSWs) that focuses on the damage-control behavior to enhance the structural resilience. The yielding sequence of SSWs and frame components is found to be a critical issue for the damage-control behavior and the design of systems. The design concept is validated by the full-scale experiments presented in this paper. Based on a modified energy-balance model, a procedure for designing and assessing the system motivated by the framework regarding the equilibrium of the energy demand and the energy capacity is proposed. The damage-control spectra constructed by strength reduction factors calculated from single-degree-of-freedom systems considering the post stiffness are addressed. A quantitative damage-control index to evaluate the system is also derived. The applicability of the proposed approach is validated by the evaluation of example structures with nonlinear dynamic analyses. The observations regarding the structural response and the prediction during selected ground motions demonstrate that the proposed approach can be applied to damage-control design and assessment of systems with satisfactory accuracy.