• 한국전자거래학회지
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• 제20권2호
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• pp.125-140
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• 2015

공급사슬에서 발생한 위험의 영향력은 위험이 발생한 영역에만 국한되는 것이 아니라 연결구조를 따라 네트워크 전체에 퍼지게 된다. 이러한 위험의 전파 현상으로 인해 공급사슬은 네트워크 연결 구조에 의해 위험의 영향을 받게 될 가능성이 달라진다. 따라서 공급사슬 네트워크를 설계하는 시점에 구조적 연결성을 고려하여 내외부 위험의 발생에 따른 비용을 최소화할 수 있어야 한다. 일반적으로 매개 중심성은 위험의 발생가능성과 영향력의 확산을 설명하는 지표로 해석할 수 있다. 본 연구에서는 구조적 취약성 관점에서의 재해석과 수정을 통해 서로 다른 공급사슬의 취약성을 정량적으로 비교하고, 보다 안정적인 네트워크 구조를 선택할 수 있는 방안을 제시한다.

• Smart Structures and Systems
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• 제23권2호
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• pp.185-194
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• 2019

The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.110-118
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• 2024

This study examines factors influencing nonusers' resistance to the adoption of the metaverse, focusing on propagation mechanisms. It elucidates the role of innovation resistance within the metaverse adoption process. We applied the Innovation Resistance Model in the context of the metaverse and considers three major groups of factors influencing resistance to the metaverse: innovation characteristics (perceived usefulness, compatibility, perceived risk, and complexity), consumer characteristics (personal innovativeness), and propagation mechanisms (mass media, online media, and personal communication). An online survey of college students who do not use the metaverse revealed that perceived usefulness, compatibility, personal innovativeness, and online media were negative predictors of resistance to the metaverse. Conversely, perceived risk, mass media, and personal communication were positive predictors of resistance to the metaverse. Furthermore, innovation resistance was found to play a mediating role in the metaverse adoption process. Drawing upon the findings, we suggested marketing strategies to decrease resistance to the metaverse.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2960-2973
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• 2022

Since Fukushima nuclear power plant (NPP) accident in 2011, the importance of research on various severe accident phenomena has been emphasized. Particularly, detailed analysis of combustion risk is necessary following the containment damage caused by combustion in the Fukushima accident. Many studies have been conducted to evaluate the risk of local hydrogen concentration increases and flame propagation using computational code. In particular, the potential for combustion by local hydrogen concentration in specific areas within the containment has been emphasized. In this study, the process of flame propagation generated inside a reactor core to containment during a loss of coolant accident (LOCA) was analyzed using MELCOR 2.1 code. Later in the LOCA scenario, it was expected that hydrogen combustion occurred inside the reactor core owing to oxygen inflow through the cold leg break area. The main driving force of the oxygen intrusion is the elevated containment pressure due to the molten corium-concrete interaction. The thermal and mechanical loads caused by the flame threaten the integrity of the containment. Additionally, the containment spray system effectiveness in this situation was evaluated because changes in pressure gradient and concentrations of flammable gases greatly affect the overall behavior of ignition and subsequent containment integrity.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.130-137
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• 2022

In the geological repository of radioactive nuclear waste, anaerobic corrosion can generate hydrogen, and may conservatively lead to the production of hydrogen-air layer. The accumulated hydrogen may cause a hazardous flame propagation resulting from any potential ignition sources. This study numerically investigates the processes of ignition and flame propagation in the layered mixture. Simple geometry was chosen to represent the geological repository, and reactive flow simulations were performed with different ignition power, energy, and locations. The simulation results revealed the effects of power and energy of ignition source, which were also analyzed theoretically. The mechanism of layered flame propagation was suggested, which includes three stages: propagation into the hydrogen area, downward propagation due to the product gas, and horizontal propagation along the top wall. To investigate the effect of the ignition source location, simulations with eight different positions were performed, and the boundary of hazardous ignition area was identified. The simulation results were also explained through scaling analysis. This study evaluates the potential risk of the accumulated hydrogen in geological repository, and illustrates the layered flame propagation in related ignition scenarios.

• 한국산업보건학회지
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• 제32권2호
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• pp.111-115
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• 2022

Objectives: The purpose of this study is to verify whether droplet-induced propagation, the main route of infectious diseases such as COVID-19, can occur in semiconductor FAB (Fabrication), based on research results on general droplet propagation. Methods: Through data surveys droplet propagation was modeled through simulation and experimental case analysis according to general (without mask) and mask-wearing conditions, and the risk of droplet propagation was inferred by reflecting semiconductor FAB operation conditions (air current, air conditioning system, humidity, filter conditions). Results: Based on the results investigated to predict the possibility of spreading infectious diseases in semiconductor FAB, the total amount of droplet propagation (concentration), propagation distance, and virus life in FAB were inferred by reflecting the management parameter of semiconductor FAB. Conclusions: The total amount(concentration) of droplet propagation in the semiconductor fab is most affected by the presence or absence of wearing a mask and the line air dilution rate has some influence. when worn it spreads within 0.35~1m, and since the humidity is constant the virus can survive in the air for up to 3 hours. as a result the semiconductor fab is judged to be and effective space to block virus propagation due to the special environmental condition of a clean room.

• Earthquakes and Structures
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• 제17권6호
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• pp.557-566
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• 2019

The evaluation of the seismic hazard for a given site is to estimate the seismic ground motion at the surface. This is the result of the combination of the action of the seismic source, which generates seismic waves, the propagation of these waves between the source and the site, and site local conditions. The aim of this work is to evaluate the sensitivity of dynamic response of extended structures to spatial variable ground motions (SVGM). All factors of spatial variability of ground motion are considered, especially local site effect. In this paper, a method is presented to simulate spatially varying earthquake ground motions. The scheme for generating spatially varying ground motions is established for spatial locations on the ground surface with varying site conditions. In this proposed method, two steps are necessary. Firstly, the base rock motions are assumed to have the same intensity and are modelled with a filtered Tajimi-Kanai power spectral density function. An empirical coherency loss model is used to define spatial variable seismic ground motions at the base rock. In the second step, power spectral density function of ground motion on surface is derived by considering site amplification effect based on the one dimensional seismic wave propagation theory. Several dynamics analysis of a curved viaduct to various cases of spatially varying seismic ground motions are performed. For comparison, responses to uniform ground motion, to spatial ground motions without considering local site effect, to spatial ground motions with considering coherency loss, phase delay and local site effects are also calculated. The results showed that the generated seismic signals are strongly conditioned by the local site effect. In the same sense, the dynamic response of the viaduct is very sensitive of the variation of local geological conditions of the site. The effect of neglecting local site effect in dynamic analysis gives rise to a significant underestimation of the seismic demand of the structure.

• 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.

• Nuclear Engineering and Technology
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• 제43권3호
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• pp.271-278
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• 2011

When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a $2{\times}3$ rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.329-337
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• 2003

Stock market prediction is regarded as a challenging task of financial time-series prediction. There have been many studies using artificial neural networks in this area. Recently, support vector machines (SVMs) are regarded as promising methods for the prediction of financial time-series because they me a risk function consisting the empirical ewer and a regularized term which is derived from the structural risk minimization principle. In this study, I apply SVM to predicting the Korea Composite Stock Price Index (KOSPI). In addition, this study examines the feasibility of applying SVM in financial forecasting by comparing it with back-propagation neural networks and case-based reasoning. The experimental results show that SVM provides a promising alternative to stock market prediction.