• 한국전산구조공학회논문집
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• 제16권3호
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• pp.229-236
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• 2003

손상평가를 위해 많은 연구자들에 의해 인공신경망이 이용되어 왔다. 그러나, 인공신경망을 이용한 손상평가에 있어 정확성과 능률성을 제고하기 위해서는 몇가지 문제점이 있다. 기존의 인공신경망 특히 역전파신경망(BPNN)의 경우 신경망 학습을 위해 많은 수의 학습패턴을 필요로 하며, 또한 신경망의 구조와 해의 수렴간에 어떤 확정적인 관계가 존재하지 않는다. 따라서 신경망의 은닉층의 수와 한 은닉층에서의 노드수는 시행착오적으로 결정되게 된다. 이러한 많은 훈련패턴의 준비와 최적의 신경망 구조 결정을 위해서는 많은 시간이 필요하다. 본 논문에서는 이러한 단점들을 극복하기 위해 확률신경망을 패턴분류기로 사용하였다. 이를 판형철도교의 손상평가에 수치해석적으로 검증하였다. 또한 확률신경망을 이용한 철도판형교 손상평가시 적절한 훈련패턴 선택을 위해 모드형상과 고유진동수를 사용한 경우의 적용성에 대해 검토하였다.

• 한국정보과학회논문지:시스템및이론
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• 제33권8호
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• pp.524-535
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• 2006

급속한 인터넷 기술의 발전으로 기업이나 기관에서의 업무 처리는 인터넷 기반 기술에 의존하고 있다. 또한 주요 정보통신 시설의 네트워크 의존도와 결합도가 증가함에 따라 시스템내의 취약성을 대상으로 하는 침해 행위와 같은 사이버 보안 사고의 수가 크게 증가하고 있다. 이에 따라 개인정보는 물론 컴퓨터 자원들의 침해와 관련된 피해 파급 (damage propagation)에 관한 연구가 요구된다. 그러나 기존의 제안된 모델들은 위험 관리 측면의 방법론적인 접근이거나, 바이러스 (virus) 나 웹 (worm) 같은 특정 위협 (threats) 에 대해서만 적용할 수 있는 연구가 진행되어 왔다. 따라서 본 논문에서는 과거의 위협 발생 데이타를 근거로 하여 전체 시스템이 가지고 있는 다양한 위협들에 대해 적용 가능한 마코프 프로세스 (markov process) 에 기반한 피해 파급 모델을 제시한다. 이를 통하여 각 위협별 발생 확률 및 발생 빈도를 예측할 수 있다.

• Structural Engineering and Mechanics
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• 제67권5호
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• pp.427-437
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• 2018

Structural pounding is commonly observed phenomenon during major ground motion, which can cause both structural and architectural damages. To reduce the amount of damage from pounding, the best and effective way is to increase the separation distance. Generally, existing design procedures for determining the separation distance between adjacent buildings subjected to structural pounding are based on approximations of the buildings' peak relative displacement. These procedures are based on unknown safety levels. The aim of this research is to estimate probabilistic separation distance between adjacent structures by considering the variability in the system and uncertainties in the earthquakes characteristics through comprehensive numerical simulations. A large number of models were generated using a robust Monte-Carlo simulation. In total, 6.54 million time-history analyses were performed over the adopted models using an ensemble of 25 ground motions as seismic input within OpenSees software. The results show that a gap size of 50%, 70% and 100% of the considered design code for the structural periods in the range of 0.1-0.5 s, leads to have the probability of pounding about 41.5%, 18% and 5.8%, respectively. Finally, based on the results, two equations are developed for probabilistic determination of needed structural separation distance.

• 한국소음진동공학회논문집
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• 제14권12호
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• pp.1347-1353
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• 2004

With respect to the researches of the optical flying head(OFH) , the head-gimbal assembly should be analyzed to guarantee the stable fabrication and the characteristics of shock resistance. The suitable design is proved through the Probabilistic analysis of the design parameters and material properties of the model. Probabilistic analysis is a technique that be used to assess the effect of uncertain input parameters and assumptions on your analysis model. Using a probabilistic analysis you can find out how much the results of a finite elements analysis are affected by uncertainties in the model. Another factor is analysis of the dynamic shock analysis. For the mobile application, one of the important requirements is durability under severe environmental condition, especially, resistance to mechanical shock. An important challenge in the disk recording is to improve disk drive robustness in shock environments. If the system comes in contact with outer shock disturbance. the system gets critical damage in head-gimbal assembly or disk. This paper describes probabilistic and dynamic shock analysis of head-gimbal assembly in micro MO drives using OFH slider.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.346-353
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• 2002

The risk of bearing failure is evaluated through the seismic response analysis of a bridge considering the probabilistic characteristics of structural properties such as the mass of superstructure, the stiffness of pier, and the translational and rotational stiffness of the foundation as well as seismic loadings during the bridge service lift. The effect of pounding between adjacent vibration units on the risk of bearing failure is also investigated. The probabilistic characteristics of structural properties are obtained by the Monte Carlo simulations based on the probabilistic characteristics of basic random variables included in the structural properties. From the simulation results, the failure probability of fixed bearings attached on the abutment is found to be much higher than those placed on the piers. It is also found that the pounding effect significantly increases the failure probability of bearings. In the simply supported bridges, the risk of bearing failure increases as the number of bridge spans increase. Therefore, the failure probability of fixed bearing due to the effects of pounding phenomena and the number of bridge spans should be considered in the seismic desist of bearings.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 추계 학술발표회논문집
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• pp.295-302
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• 2003

A quantitative approach for the retrofit prioritization of bridges is developed based on the damage risk of seismic vulnerable components. In the developed approach, seismic damage risk is estimated in the probabilistic perspectives with an analytical bridge model, which can consider various phenomena found in the seismic behaviors of girder-type bridges and damage models of various vulnerable components. Based on the total cost due to failure of structural components, weighting factors are proposed. Finally, the ranking index and retrofit priority of bridges are estimated from the overall damage risk and weighting factors of bridges. As a result, the retrofit priority of four PSC girder bridges is evaluated by using the proposed approach. The vulnerable components in need of seismic retrofit are selected accordingly. From simulated results, the validity of the proposed approach is verified by comparison with the existing approach. In addition, the proposed approach is found to be appropriate in evaluating the priority of existing bridges.

• 한국지반공학회논문집
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• 제33권5호
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• pp.25-35
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• 2017

액상화는 지진에 의해 발생하는 대표적인 피해 중 하나로 이에 대한 가능성을 평가하기 위한 많은 방법들이 개발되었으며, 최근에는 지반이 갖는 불확실성을 합리적으로 고려하기 위한 확률론적 접근방법에 대한 연구가 이루어지고 있다. 본 연구에서는 지반의 물성치가 갖는 공간 변동성을 고려하여 확률론적 해석을 수행하고자 서로 다른 변동특성을 갖는 세 지점의 CPT 데이터를 활용하여 콘관입 저항치에 대한 공간 변동성을 평가하였다. 이후, 각 지점의 공간 변동성을 고려한 콘관입 저항치의 확률장을 생성하였으며, CPT기반 액상화 평가방법을 통하여 액상화에 의해 유발되는 침하량의 확률론적 해석을 수행하였다. 연구결과, 공간변동성이 고려되지 않을 경우 지반의 불확실성을 과대평가할 수 있으며, 기준 허용 침하량에 따라 약 30%까지 큰 확률론적 차이가 발생할 수 있는 것으로 나타났다.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2009년도 정기 학술발표대회
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• pp.63.2-63.2
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• 2009