• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.125-140
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• 2015

It is general that the impact of supply chain risk spread out to the whole network along the connected structure. Due to the risk propagation the probability to exposure a certain risk is affected by not only the characteristics of each risk factor but also network structure. It means that the structural connectivity among vertices should be considered while designing supply chain network in order to minimize disruption cost. In this research, the betweenness centrality has been utilized to quantitatively assess the structural vulnerability. The betweenness centrality is interpreted as the index which can express both the probability of risk occurrence and propagation of risk impact. With the structural vulnerability index, it is possible to compare the stability of each alternative supply chain structure and choose the better one.

• Smart Structures and Systems
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• v.23 no.2
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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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• v.13 no.2
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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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• v.54 no.8
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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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• v.54 no.1
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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.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.2
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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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• v.17 no.6
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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.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.8
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• pp.524-535
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• 2006

With rapid development of Internet technology, business management in an organization or an enterprise depends on Internet-based technology for the most part. Furthermore, as dependency and cohesiveness of network in the communication facilities are increasing, cyber attacks have been increased against vulnerable resource in the information system. Hence, to protect private information and computer resource, research for damage propagation is required in this situation. However the proposed traditional models present just mechanism for risk management, or are able to be applied to the specified threats such as virus or worm. Therefore, we propose the probabilistic model of damage propagation based on the Markov process, which can be applied to diverse threats in the information systems. Using the proposed model in this paper, we can predict the occurrence probability and occurrence frequency for each threats in the entire system.

• Nuclear Engineering and Technology
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• v.43 no.3
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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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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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.