• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2246-2255
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• 2023

Evacuation time estimation (ETE) is crucial for the effective implementation of resident protection measures as well as planning, owing to its applicability to nuclear emergencies. However, as confirmed in the Fukushima case, the ETE performed by nuclear operators does not reflect behavioral features, exposing thus, gaps that are likely to appear in real-world situations. Existing research methods including surveys and interviews have limitations in extracting highly feasible behavioral features. To overcome these limitations, we propose a VR-based immersive experiment system. The VR system realistically simulates nuclear emergencies by structuring existing disasters and human decision processes in response to the disasters. Evacuation behavioral features were quantitatively extracted through the proposed experiment system, and this system was systematically verified by statistical analysis and a comparative study of experimental results based on previous research. In addition, as part of future work, an application method that can simulate multi-level evacuation dynamics was proposed. The proposed experiment system is significant in presenting an innovative methodology for quantitatively extracting human behavioral features that have not been comprehensively studied in evacuation. It is expected that more realistic evacuation behavioral features can be collected through additional experiments and studies of various evacuation factors in the future.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.2
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• pp.41-48
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• 2003

The human behavior is very important in development of simulation system for evacuation analysis. The walking speed of passenger is especially affected by dynamic effect and list due to damage and ship motion in wave. There are various methods to get an useful data for evacuation simulation. The onboard experimental approach is one of the most strong method. In this paper, the onboard experiment is performed to obtain human behavioral data. To realize ship trim and heel due to maritime casuality, the passage model for experiment is made. The experiment is carried out at dynamic and static condition respectively using the ship with passage model. The result is evaluated and it will be reflected in evacuation simulation tool.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.135-140
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• 2001

In the last years there have been some severe accidents with passenger vessels. So, International Maritime Organization(IMO) has recognized that computer stimulation of the evacuation may be required for passenger vessels. Human elements is a key issues of escape analysis on shipboard. There are technical requirements to simulate of escape analysis for human elements. Technical requirements include model of ship structure, evacuation algorithm, human behaviour analysis and influence of ship listing/motion. This paper provides the key issues and technologies of simulation for human escape on shipboard.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.233-234
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• 2022

In order to minimize casualties in case of a fire in a building, it is necessary to anticipate the time required for evacuation of occupants and the delay in evacuation in advance, and prepare countermeasures for possible occurrences. In fact, various factors that cannot be predicted exist and cannot be considered by excluding them, so the risk is predicted and evaluated through quantitative evacuation modeling. In order to understand this, we analyzed domestic and international evacuation modeling research trends. For about 40 years, starting with the characteristics of human movement, an evacuation modeling technique based on scientific methods has been developed through actual fire accident cases and various real-world experiments with humans. Then, in order to analyze the natural reaction of humans, which has a decisive influence in the recognition and decision-making phase, evacuation modelling studies have been conducted in depth using psychological and physical experimental methods.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.97-105
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• 2022

Human casualties from fires are increasing worldwide. The majority of human deaths occur during the evacuation process, as occupants panic and are unaware of the location of the fire and evacuation routes. Using an Internet of Things (IoT) sensor and reinforcement learning, we propose a method to find the safest evacuation route by considering the fire location, flame speed, occupant position, and walking conditions. The first step is detecting the fire with IoT-based devices. The second step is identifying the occupant's position via a beacon connected to the occupant's mobile phone. In the third step, the collected information, flame speed, and walking conditions are input into the reinforcement learning model to derive the optimal evacuation route. This study makes it possible to provide the safest evacuation route for individual occupants in real time. This study is expected to reduce human casualties caused by fires.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.2
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• pp.96-104
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• 2011

Modeling and simulation of human-involved complex systems pose challenges to representing human decision makings into logical systems because of the nondeterministic and dynamic nature of human behaviors. In modeling perspectives, human's activities in systems can increase uncertainty and complexity, because he or she can potentially access all other resources within the system and change the system states. To address all of these human involvements in the system, this research suggests applying the Finite State Automata (FSA)-based formal modeling of human-involved systems that incorporates the ecological concept of affordances to an evacuation simulation, so that human behavioral patterns under urgent and dynamic emergency situations can be considered in the real-time simulation. The proposed simulation methodologies were interpreted using the warehouse fire evacuation simulation to clarify the applicability of the proposed methodology. This research is expected to merge system engineering technologies and human factors, and come out to the new predictive modeling methodology for disaster simulations. This research can be applied to a variety of applications such as building layout designs and building access control systems for emergency situations.

• Journal of the Korean Society of Safety
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• v.39 no.3
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• pp.50-59
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• 2024

In recent years, building architecture has become increasingly complex and larger in scale to accommodate many people. In densely populated facilities, the interiors are becoming more intricate and high-rise, with narrow corridors, hallways, and stairs. This poses challenges for evacuating occupants in case of emergencies such as fires, making it crucial to assess the evacuation safety in advance. In evacuation safety research, there are significant limitations to theoretical studies owing to their association with crowd behavior and human evacuation characteristics, as well as the risks associated with experiments involving human participants. Consequently, evacuation experiments conducted using simulation-based methodologies are gaining recognition worldwide. However, crowd simulations face validation difficulties because of variations in crowd movement and evacuation characteristics across different cases and scenarios, as well as the challenge of accurately reflecting human characteristics during evacuations. In this study, we investigated validation methods for evacuation simulations using the SAFEGUARD validation data set (SGVDS) provided by the University of Greenwich, UK. The SGVDS collects data on crowd evacuations through actual evacuation tests conducted on ColorLine's large RO-PAX ferry and Royal Caribbean International's cruise ships. The accuracy of the crowd simulations can be validated by comparing SGVDS and crowd simulation results. This study will contribute to the development of highly accurate crowd simulations by verifying various crowd simulations.

• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.49-60
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• 2013

Evacuation process has been considered as one of the most important elements to be managed in public facilities. Although the importance is highlighted through numerous literatures, disaster evacuation planning, particularly fire accidents, faces a number of human behavior related limitations for a similar application to different types of facilities/occupants. To overcome the obstacles including complexity in human behaviors, a number of simulation techniques with limited consideration on human behaviors are utilized to predict foreseeable problems in evacuation process. Therefore, this research aims to propose system dynamics models incorporating human behaviors considering different types of occupants under disaster evacuation events. Analysis on emergent human behaviors such as group forming and interactions under urgent situation are conducted based on the main stream theories in social science field. The results suggest the influences of human behavior factors including cooperative intention, information sharing, and mobility change to evacuation behavior. The implications are expected to provide safety consideration at planning/designing phase of buildings and help facility safety managers for evacuation planning with more realistic management approaches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.535-546
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• 2019

The purpose of this research was to analyze the relationship between human risk factors and evacuation behavior stages for tunnel safety. Therefore, we conducted a survey using a structured questionnaire on the relationship between safety facilities and safety behavior in order to derive an optimized interaction between the two. The research subjects were 141 tunnel users who understand the tunnel environment. The survey period was from June 24, 2018, to September 28, 2018. As data analysis methods, we employed a frequency analysis, a multiple regression analysis, and an independent-sample t-test. In the analysis of the correlation between the human risk factors and the major variables of evacuation behavior, the evacuation phases 1, 2, and 3 were all correlated with acceleration and delay, and the human risk factors were partially correlated. In the multiple regression analysis, the will to comply with laws (${\beta}=0.188$, p=0.034) and information recognition within the tunnel (${\beta}=0.220$, p=0.009) were factors that influence the relationship between human risk factors and evacuation behavior, indicating 12% explanatory power of the impact of human risk factors for the acceleration of evacuation behavior 3. The important variables between human risk factors and evacuation behavior were compliance with laws and information recognition in tunnels. Hence, it is necessary to study the elements that interact with the environment in the tunnel.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.138-143
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• 2011

Growing attention of a society to protecting weak people leads an increase of various social welfare facilities. Therefore, safety of the occupants at emergency situations, such as fire, must be considered as an important factor during the design and operation of those facilities. In this paper an exploratory study is carried out on a method quantitatively assessing the human evacuation safety of social welfare facilities. A evacuation simulation method, being routinely used in the evacuation analysis of passenger ships deriving 'Evacuability' as a quantity of safety, is applied to assess the human safety of a facility for single-moms. Based on the simulation results, the main factors that must be considered while carrying out the evacuation simulation for the human safety assessment of the facility are investigated.