• Structural Engineering and Mechanics
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• 제85권6호
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• pp.793-808
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• 2023

Türkiye is located in a region where destructive earthquakes are frequently experienced due to its geological characteristics and geographical location. Therefore, considering the possibility of a devastating earthquake at any time, determining the reinforced concrete (RC) building seismic safety, constructed before or after the current seismic buildings code, is one of the most important issues to be completed firstly. For this purpose, rapid assessment methods developed to quickly determine the seismic safety of buildings are available in the literature. Comparison of the principles of Principles of the Determination of Risky Structures-2019, Column and Wall Index Method, P25 Scoring Method and Improved Discriminant Analysis Method, which are among these methods, have been aimed within the scope of this study. Within the scope of this paper, a total of 43 buildings in the Yalova/Çınarcık region of Türkiye that the damage level was determined by street observation method immediately after the 1999 Kocaeli (Izmit) Earthquake; 15 buildings with heavy damage and 28 buildings with moderate damage were examined by rapid assessment methods. Although the risk detection difference was not separated as a clear line in any of the methods used, the results obtained from the rapid assessment methods are evaluated as being compatible with the detected after earthquake structural seismic behavior of the buildings. The PDRS-2019 and column and wall index method gave the most approximate results. In the results obtained from the analyzes; structural features such as number of floors, frame continuity, soft/weak story irregularity, effective shear strength area, existence of heavy overhangs in plan, type of structural system have been found to be significantly effective on the earthquake behavior of buildings.

• Earthquakes and Structures
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• 제15권4호
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• pp.431-441
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• 2018

This study provides fragility-based assessment of seismic performance of reinforced concrete bridges. Seismic fragility curves were created using nonlinear analysis (NA) and artificial neural networks (ANNs). Nonlinear response history analyses were performed, in order to calculate the seismic performances of the bridges. To this end, 306 bridge-earthquake cases were considered. A multi-layered perceptron (MLP) neural network was implemented to predict the seismic performances of the selected bridges. The MLP neural networks considered herein consist of an input layer with four input vectors; two hidden layers and an output vector. In order to train ANNs, 70% of the numerical results were selected, and the remained 30% were employed for testing the reliability and validation of ANNs. Several structures of MLP neural networks were examined in order to obtain suitable neural networks. After achieving the most proper structure of neural network, it was used for generating new data. A total number of 600 new bridge-earthquake cases were generated based on neural simulation. Finally, probabilistic seismic safety analyses were conducted. Herein, fragility curves were developed using numerical results, neural predictions and the combination of numerical and neural data. Results of this study revealed that ANNs are suitable tools for predicting seismic performances of RC bridges. It was also shown that yield stresses of the reinforcements is one of the important sources of uncertainty in fragility analysis of RC bridges.

• Earthquakes and Structures
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• 제24권4호
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• pp.275-288
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• 2023

Based on the crucial role of high-speed railway bridges (HSRBs) in the safety of high-speed railway operations, it is an important approach to mitigate earthquake hazards by proceeding with seismic risk assessments in their whole life. Bridge seismic risk assessment, which usually evaluates the seismic performance of bridges from a probabilistic perspective, provides technical support for bridge risk management. The seismic performance of bridges is greatly affected by the degradation of material properties, therefore, material damage plays a nonnegligible role in the seismic risk assessment of the bridge. The effect of material damage is not considered in most current studies on seismic risk analysis of bridges, nevertheless. To fill the gap in this area, in this paper, a nonlinear dynamic time-history analysis has been carried out by establishing OpenSees finite element model, and a seismic vulnerability analysis is carried out based on the incremental dynamic analysis (IDA) method. On this basis, combined with the site risk analysis, the time-dependent seismic risk analysis of an offshore three-span HSRB in the whole life cycle has been conducted. The results showed that the seismic risk probabilities of both components and system of the bridge increase with the service time, and their seismic risk probabilities increase significantly in the last service period due to the degradation of the material strength, which demonstrates that the impact of durability damage should be considered when evaluating the seismic performance of bridges in the design and service period.

• Nuclear Engineering and Technology
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• 제52권10호
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• pp.2238-2249
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• 2020

In a seismic PSA, dependency among seismic failures of components has not been explicitly modeled in the fault tree or event tree. This dependency is separately identified and assigned with numbers that range from zero to unity that reflect the level of the mutual correlation among seismic failures. Because of complexity and difficulty in calculating combination probabilities of correlated seismic failures in complex seismic event tree and fault tree, there has been a great need of development to explicitly model seismic correlation in terms of seismic common cause failures (CCFs). If seismic correlations are converted into seismic CCFs, it is possible to calculate an accurate value of a top event probability or frequency of a complex seismic fault tree by using the same procedure as for internal, fire, and flooding PSA. This study first proposes a methodology to explicitly model seismic dependency by converting correlated seismic failures into seismic CCFs. As a result, this methodology will allow systems analysts to quantify seismic risk as what they have done with the CCF method in internal, fire, and flooding PSA.

• 한국전산구조공학회논문집
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• 제33권2호
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• pp.129-136
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• 2020

본 연구에서 기기 지진취약도 정보의 부분 종속 관계를 정확하게 고려할 수 있는 샘플링 기반 지진 확률론적 리스크 평가 정량화 기법을 개발하였다. 구체적으로 두 가지 대표적 방법론인 EPRI 지진취약도 입력기반 정량화 방법과 JAERI 지진취약도 입력기반 정량화 기법의 장점을 결합하여 리스크 정량화 방법를 제안하였다. 본 연구에서 제안하는 방법의 가장 중요한 특징은 EPRI 지진취약도 입력을 JAERI 지진취약도 입력 공간으로 치환하여 샘플링 방법으로 SPRA 수행하는 것에 있다. 제안된 샘플링기반 접근법을 간단한 예제부터 실제 원전의 지진 확률론적 리스크 평가 문제에 적용한 결과, 본 연구에서 제안하는 방법이 정해에 가까운 시스템 지진취약도 및 지진리스크 값을 산출함을 확인할 수 있었다. 그러므로 본 연구에서 제안하는 방법론은 기존의 SPRA 정량화 방법이 다룰 수 없는 시스템 내 부분 종속 조건을 고려하여 지진 리스크를 정확하게 평가할 수 있는 유용한 도구로 활용될 수 있을 것이라 기대한다.

• 한국안전학회지
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• 제25권3호
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• pp.91-99
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• 2010

In this study, the advanced numerical algorithm is developed which can performed the static and dynamic stochastic finite element analysis by considering the effect of uncertainties included in the member stiffness of steel cable-stayed bridges and seismic load. After conducting the linear and nonlinear initial shape analysis, the advanced numerical algorithm is the assessment tool which can performed structural the response analysis considering the static linearity and non-linearity of before or after induced intial tensile force, and examined the reliability assessment more efficiently. The verification of the developed numerical algorithm is evaluated by analyzing the regression analysis and coefficient of correlation using the direct monte carlo simulation. Also, the dynamic response characteristic and coefficient of variation of the steel cable-stayed bridge is calculated by considering the uncertainty of random variables using the developed numerical algorithm. In addition, the quantitative structural safety of the steel cable-stayed bridges is evaluated by conducting the reliability assessment based upon the dynamic stochastic finite element analysis result.

• 한국안전학회지
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• 제35권1호
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• pp.97-106
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• 2020

The objective of this paper is to suggest a new quantification method for multi-unit probabilistic safety assessment (PSA) that removes the overestimation error caused by the existing delete-term approximation (DTA) based quantification method. So far, for the actual plant PSA model quantification, a fault tree with negates have been solved by the DTA method. It is well known that the DTA method induces overestimated core damage frequency (CDF) of nuclear power plant (NPP). If a PSA fault tree has negates and non-rare events, the overestimation in CDF drastically increases. Since multi-unit seismic PSA model has plant level negates and many non-rare events in the fault tree, it should be very carefully quantified in order to avoid CDF overestimation. Multi-unit PSA fault tree has normal gates and negates that represent each NPP status. The NPP status means core damage or non-core damage state of individual NPPs. The non-core damage state of a NPP is modeled in the fault tree by using a negate (a NOT gate). Authors reviewed and compared (1) quantification methods that generate exact or approximate Boolean solutions from a fault tree, (2) DTA method generating approximate Boolean solution by solving negates in a fault tree, and (3) probability calculation methods from the Boolean solutions generated by exact quantification methods or DTA method. Based on the review and comparison, a new intersection removal by probability (IRBP) method is suggested in this study for the multi-unit PSA. If the IRBP method is adopted, multi-unit PSA fault tree can be quantified without the overestimation error that is caused by the direct application of DTA method. That is, the extremely overestimated CDF can be avoided and accurate CDF can be calculated by using the IRBP method. The accuracy of the IRBP method was validated by simple multi-unit PSA models. The necessity of the IRBP method was demonstrated by the actual plant multi-unit seismic PSA models.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• 대한토목학회논문집
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• 제40권5호
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• pp.455-463
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• 2020

사용연수가 30년 이상 된 노후 시설물은 향후 10년 사이 3배 이상 급증될 것으로 조사되고 있다. 또한, 2017년 행정안전부 "내진설계기준 공통적용"개정으로 도로시설물의 내진성능 확보유무가 검토되어야 하며, 이는 기존 설계기준을 통해 내진보강 되었거나, 내진설계가 된 시설물을 포함한 모든 기존 도로시설물을 대상으로 내진성능 확보유무가 재평가 되어야 함을 의미한다. 이렇듯 대량의 시설물에 대한 내진성능관리를 위해서는 빠른 시간 내에 경제적이고 신뢰성 있는 결과를 제공할 수 있는 의사결정 지원기술이 필요하다. 하지만, 우리나라에서 사용되고 있는 지수평가방법은 결정론적인 방법으로서, 개별시설물의 내진성능을 정성적인 지수 값으로 산정하고 지수 값의 크기에 따라 내진보강 우선순위만을 결정하고 있어 합리적인 내진성능관리를 위한 다양한 의사결정을 지원하기 어려운 실정이다. 이러한 단점을 극복하고 내진성능관리 의사결정에 필요한 시설물의 직접손실비용, 사회·경제적 간접손실비용, 재원투입효과 등의 정보를 제공할 수 있는 지진위험도평가 방법으로 전환이 필요하다.

• Nuclear Engineering and Technology
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• 제49권4호
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• pp.710-720
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• 2017

In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.