• Journal of Korean Society of Disaster and Security
• /
• v.5 no.2
• /
• pp.61-70
• /
• 2012

The range of special management target facilities is seperated by the building sector and the field of civil engineering. In the present study, the risk analysis was performed, related to fire occurred for the last five years, in the field of residential and non-residential facilities in buildings. Most of fire incidents occurred in residential and non-residential facilities was the cause of the electrical, and the resulting casualties were also very high. Therefore, based on the results, the risk evaluation index was developed, identifying the causes of fire occur and doing the fire vulnerability analysis for each facility. The result of this study can be utilized safety management to these facilities for the future, especially, inducing a more specialized and intensive safety management.

• Journal of Korean Association for Spatial Structures
• /
• v.11 no.4
• /
• pp.89-99
• /
• 2011

As the scope of the target of terrorism is recently extending, the danger of domestic terroristic attacks is increasing constantly, and the form of terrorism is changing from hard targets such as significant facilities of the country into soft target of multi-complex buildings such as skyscrapers. Accordingly this study analyzes the terrorism threat level on skyscrapers by comparing the assessment results of the terrorism threat level on skyscrapers and high-rise buildings with the assessment results of the terrorism threat level on low-rise buildings through fema 455 - Rapid Visual Screening. As a result, skyscrapers and high-rise buildings are relatively higher threat rating than consequences and vulnerability rating. This is caused by the fact that the terrorism threat level on skyscrapers is high due to their residents and their national or regional symbolism and visibility

• The Journal of the Korea Contents Association
• /
• v.9 no.5
• /
• pp.249-256
• /
• 2009

The purpose of this study is to suggest the strategies of building disaster resistant communities to overcome communities destruction and vulnerability caused by the Hebei Spirit oil spill accident in Taean on December 7th, 2007. For accomplishing the purpose, we drew problems of approach based on context of community, governance strategy, and community-based approach. And based on the results of this analysis, suggestions were made as follows for building disaster resistant communities. First, when Hebei Spirit oil spill accident occurred we have been short of regional study and unreality of regional safety plan. For overcoming this points, we have need of activation of regional study and establishment of regional safety plan based on the bottom-up approach. Second, while the spill has brought a milestone activation of volunteer, we have not still efficient disaster management based on governance. So we have to establish network-governance to cooperate with government-business-private sector for efficient disaster management. Third, we argue that it is important to build social capital such as social networks, social contacts for community-based disaster resistant communities.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.16 no.5
• /
• pp.33-40
• /
• 2012

To reduce the vulnerability of torsional irregular buildings caused by seismic loads, the torsional amplification factor was introduced by the seismic code. This factor has been applied differently in a variety of seismic codes. In this study, the final static eccentricity, and the lateral and torsional stiffness ratios of buildings designed with different design eccentricities were compared. The increment of the torsional amplification factor resulted in a decrement of the final static eccentricity of the building. However, after reaching the maximum value of this factor, the final static eccentricity of the building increased again. The final static eccentricity of the building designed by multiplying the sum of the inherent and accidental eccentricity by the torsional amplification factor was zero or had a minus value, depending to the position of the vertical element.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.5
• /
• pp.265-278
• /
• 2021

When a dangerous event arises for people inside a building and an immediate evacuation is required, it is important that suitable routes have been previously defined. These situations can happen especially when buildings are crowded, making the occupants have a very high vulnerability and can be trapped if they do not evacuate quickly and safely. However, in most cases, routes are considered based just on their proximity or short distance to the exit areas, and evacuation simulations that include more variables are not performed. This work aims to propose a methodology for building's indoor evacuation activities under the premise of processing simulation scenarios in multi-agent environments. In the methodology, importance indexes of simplified and validated geometry data from a BIM (Building Information Modeling) are considered as heuristic input data in a proposed algorithm. The algorithm is based on AP-Theta^* pathfinding and collision avoidance machine learning techniques. It also includes conditioning variables such as the number of people, speed of movement as well as reaction ability of the agents that influence the evacuation times. Moreover, collision avoidance is applied between people or with objects along the route. The simulations using the proposed algorithm are tested in NetLogo for diverse scenarios, showing feasible evacuation routes and calculating evacuation times in a multi-agent environment. The experimental results are obtained by applying the method in a study case and demonstrate the level of effectiveness of the algorithm, and the influence of the conditioning variables analyzed together when performing safe evacuation routes.

• Journal of the Korea Institute of Building Construction
• /
• v.23 no.6
• /
• pp.797-807
• /
• 2023

This research aims to investigate the alterations in typhoon patterns attributable to climate change and to quantitatively assess the risk of damage to residential structures. The increasing prevalence of climate anomalies and severe weather events, a consequence of global warming, is causing escalating damage globally. Notably, numerous countries are facing substantial devastation due to shifts in typhoon trajectories. Despite this, there exists a gap in empirical research quantifying the impact of these changes on building integrity and the associated risk alterations driven by climate change. In addressing this gap, our study analyzes the frequency and intensity of typhoons impacting Korea, examining the evolution of these meteorological phenomena. Furthermore, we employ the Korean Typhoon Vulnerability Function for residential facilities to quantify the altered risk posed by these changing patterns. The outcomes of this study provide the private sector with essential data to formulate diverse scenarios and business strategies in response to the escalating risks of typhoon-related damage. Additionally, it equips governmental bodies with the necessary insights to develop comprehensive risk management strategies to mitigate the effects of future typhoons.

• Convergence Security Journal
• /
• v.24 no.1
• /
• pp.11-20
• /
• 2024

Recently, smart buildings that can efficiently manage energy using ICT technology and operate and control through the building automation system by collecting data from a large number of IoT sensors in real time are attracting attention. However, as data management is carried out through an open environment, the safety of smart buildings is threatened by the security vulnerability of the existing building automation protocol. Therefore, in this paper, we analyze the major data link technology of BACnet, which is used universally, and propose OWE-based efficient BACnet/SC that can ensure the reliability of data in a wireless environment. The proposed protocol enables safe communication even in an open network by applying OWE and provides the same level of security as BACnet/SC in a TLS environment. As a result, it reduces the connection process twice and reduces the average time required by 40%, enabling more efficient communication than before.

• Journal of Korea Water Resources Association
• /
• v.55 no.8
• /
• pp.589-601
• /
• 2022

Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.1
• /
• pp.11-21
• /
• 2022

Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.159-165
• /
• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.