• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.166-176
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• 2021

Due to urbanization and industrialization, the importance of large-scale fire prevention, management and measures is increasing day by day. However, the fire site arrival rate in Golden Time, which is a factor that can minimize large-scale fire damage, of Pohang, a large city with a population of over 500,000, is relatively low. So additional fire fighting power deployment and infrastructure investment are required. However, as budget and manpower are limited, it is necessary to selectively deploy fire fighting power and invest in infrastructure. Therefore, this study attempted to present a fire damage rating that can compare the level of fire damage, which is an index that can help selectively provide fire fighting services in Pohang and make related decisions. For the index, the OD cost matrix was used to predict fire vulnerable areas with a high probability of increasing the fire scale in the event of a fire. Also fire damage was measured by predicting the level of fire damage in the event of a fire according to population, building density, and access of fire trucks. It is expected that the fire damage rating will be able to help in various decisions related to fire fighting service deployment and services not only in Pohang city, but also in other regions.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.547-550
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• 2004

We present a multiscale scheme which describes the dynamic pictures of atoms in the multiple length-scale systems. Large-scale atomic systems are reduced to coarse grained system by the quasicontinuum, of which the dynamic pathways are rendered by the action-derived molecular dynamics proved effective for multiple time-scale problems such as rare events. Adatom diffusions on the metal (001) surface are selected for our numerical examples. The energy barriers of the diffusions and the real dynamic trajectories of the adatoms are calculated.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2240-2248
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• 2015

The integration of the large-scale wind power brings great challenge to the stability of the power grid. This paper investigates and studies the fault on May 14, 2012 of the large-scale cascading trip-off of wind turbines in North China. According to the characteristics of the voltage variation, the fault process is divided into three stages: the pre-event stage, the critical stage before cascading, and the cascading stage. The scenes in the fault are reproduced, using the full-size actual power system model. Simulation models of double-fed induction generators (DFIGs) and SVCs including protection settings and controller strategies are carefully chosen to find out the reason of voltage instability in each stage. Some voltage dynamic that have never been observed before in the faults of the same kind are analyzed in detail, and an equivalent voltage sensitive dynamic model of DFIG is proposed for the fast computation. The conclusions about the voltage dynamics are validated by the actual PMU observation evidence.

• Computers and Concrete
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• v.7 no.2
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• pp.159-167
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• 2010

This paper demonstrates numerical techniques for complex large-scale modeling with microplane constitutive theories for reinforced high strength concrete, which for these applications, is defined to be around the 7000 psi (48 MPa) strength as frequently found in protective structural design. Applications involve highly impulsive loads, such as an explosive detonation or impact-penetration event. These capabilities were implemented into the authors' finite element code, ParaAble and the PRONTO 3D code from Sandia National Laboratories. All materials are explicitly modeled with eight-noded hexahedral elements. The concrete is modeled with a microplane constitutive theory, the reinforcing steel is modeled with the Johnson-Cook model, and the high explosive material is modeled with a JWL equation of state and a programmed burn model. Damage evolution, which can be used for erosion of elements and/or for post-analysis examination of damage, is extracted from the microplane predictions and computed by a modified Holmquist-Johnson-Cook approach that relates damage to levels of inelastic strain increment and pressure. Computation is performed with MPI on parallel processors. Several practical analyses demonstrate that large-scale analyses of this type can be reasonably run on large parallel computing systems.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.745-750
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• 1996

An analysis of a loss of residual heat removal system (RHRS) event during midloop operation after reactor shutdown was performed using the RELAP5/MOD3 thermal-hydraulic computer code. The experimental data of a 5% cold leg break test conducted at the ROSA-IV Large Scale Test Facility (LSTF) to simulate a main coolant pump shaft seal removal event during midloop operation of a Westinghouse-type PWR were used in the analysis. The predicted core boiling time and the peak primary system pressure showed good agreements with the measured data. Some differences between the calculational results and the experimental results were, however, found in areas of the timing of loop seal clearing and the temperature distribution in a pressurizer. Other calculational problems identified were discussed as well.

• Journal of Korean Society of Transportation
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• v.12 no.3
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• pp.49-64
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• 1994

The development of a mathematical modular framework based on Petri Network theory to model a traffic network is the subject of this paper. Traffic intersections are the primitive elements of a transportation network and are characterized as event driven and asynchronous systems. Petri network have been utilized to model these discrete event systems; further analysis of their structure can reveal information relevant to the concurrency, parallelism, synchronization, and deadlock avoidance issuse. The Petri-net based model of a generic traffic junction is presented. These modular networks are effective in synchronizing their components and can be used for modeling purposes of an asynchronous large scale transportation system. The derived model is suitable for simulations on a multiprocessor computer since its program execution safety is secured. The software pseudocode for simulating a transportation network model on a multiprocessor system is presented.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.161-168
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• 2019

Traffic accidents in tunnel can lead to large traffic accidents due to narrow and dark road characteristics. Therefore, special care of the driver is required when is driving in a tunnel. However, accidents can happen at any time. In the event of an accident, a narrow road structure may lead to a second accident. Therefore, all facilities installed inside the tunnel should be allowed to minimize damage in the event of an accident. We confirmed the safety of the collision target through the action of the sedan, Sport Utility Vehicle (SUV) and truck when the vehicle crashed into a stairway installed on the tunnel emergency escape route, and when a concrete barrier or guard rail was installed in front of the stairway. The behavior of the vehicle has resulted in a total of three results: rollover or rollover, change of speed and angle of the vehicle after collision. The sedan and SUV were the most secure when colliding with the guardrail, but considering the truck as a whole, concrete barriers were judged to be the most suitable for minimizing damage from the first accident and reducing the risk of the second accident.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.337-346
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• 2022

This study explores the impact of the COVID-19 pandemic on the stock prices of state-owned enterprises listed on the Indonesia Stock exchange. The impact of the pandemic is analyzed based on different pandemic phases and the corresponding government pandemic interventions to curb the disease. This study analyzes 6 pandemic event dates, covering the time period from January 2020 to February 2021. A total of 20 state-owned enterprises are included as the sample of this study. Test of difference is employed to compare the stock prices of the state-owned enterprises before and after each pandemic event date. In general, this study confirms the adverse impact of the COVID-19 pandemic on the stock prices, especially the event in 2020, although some variations do exist. The results of the study reveal a significant decrease in the stock prices of the state-owned enterprises after the announcement of the first confirmed COVID-19 cases, the announcement of COVID-19 as a global pandemic, the imposing of Large Scale Social Restriction (PSBB I and PSBB II). In contrast, the stock prices increase after the imposing of a new normal policy and the imposing of Public Activity Restriction (PPKM). This study also documents that the effect of the pandemic may vary based on the pandemic phase.

• Journal of the Korean Institute of Gas
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• v.23 no.2
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• pp.55-60
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• 2019

To develop a plant safety training system using virtual reality technology, we constructed a training system for a large scale plant. Compared with safety training for small plants or unit equipment, many system configurations such as virtual plant model, in-process data processing, work instruction, etc. are required and integrated system works have been carried out. The target plant, RDS process, is a high-risk process(high-temperature, high-pressure) that takes into account the training scenarios that can be taken in the event of a leaking fire in the range and refer to the actual shutdown procedure. The proposed safety training integration system can be used in similar situations that can occur in the RDS process and can be a platform for safety training using virtual reality in a large plant.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.