• Journal of the Korean Institute of Rural Architecture
• /
• v.9 no.3
• /
• pp.33-45
• /
• 2007

Recently, large scale disasters have been occurred in rural areas. Most people suffering from the disaster live in the temporary containers. These could not provide the fundamental occupancy performances such as thermal insulation, ventilation and heating system. It is very important to rebuild the residence for sufferers quickly and safely. Because modular building system has some advantages such as short construction time, mobility, light-weight structure, modularity, flexibility and economical efficiency, it is expected that it could be easily applied to the disaster restoration. So, this research aims at developing the design model of modular building system for disaster restorations in fishing and agrarian villages. For this purpose, current counterplan for restoration was firstly investigated. Also the basic guideline was established through the investigation of current status of residence in fishing and agrarian villages. Finally, 2 types of design model such as single story residence and temporary accommodation facility were proposed. We could see that we could make the flexible building plan when applying the modular building system to the temporary housing for the sufferers.

• Smart Structures and Systems
• /
• v.33 no.6
• /
• pp.449-463
• /
• 2024

Automated crack detection is crucial for structural health monitoring and post-earthquake rapid damage detection. However, realizing high precision automatic crack detection in the absence of corresponding manual labeling presents a formidable challenge. This paper presents a novel crack segmentation transfer learning method and a novel crack segmentation model called Swin-CrackFormer. The proposed method facilitates efficient crack image style transfer through a meticulously designed data preprocessing technique, followed by the utilization of a GAN model for image style transfer. Moreover, the proposed Swin-CrackFormer combines the advantages of Transformer and convolution operations to achieve effective local and global feature extraction. To verify the effectiveness of the proposed method, this study validates the proposed method on three unlabeled crack datasets and evaluates the Swin-CrackFormer model on the METU dataset. Experimental results demonstrate that the crack transfer learning method significantly improves the crack segmentation performance on unlabeled crack datasets. Moreover, the Swin-CrackFormer model achieved the best detection result on the METU dataset, surpassing existing crack segmentation models.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2015.05a
• /
• pp.253-254
• /
• 2015

Currently, according to the climate change, the damages due to the hurricane is more increased than before. In this respect, several countries have been conducted the studies regarding the damage prediction model of buildings to minimize the damages from natural disaster. As hurricane is the complex disaster including a strong wind and heavy rain, to predict the damage of hurricane, various factors has to be considered. However, mostly research has been conducted to consider only hurricane properties. Therefore, the objective of this study is to develop the regression model for predicting damages of buildings considering geography, socio-economy, construction environment and hurricane information. In the future, this study can be utilized to developing damage prediction model for building from hurricane in South Korea.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.8 no.2
• /
• pp.65-73
• /
• 2008

Since the damages caused by disasters increase every year associated with wrenching climatic changes and the diversification of the social structure, the efficient management system is required to reduce damages and an assessment of the vulnerable disaster areas is necessary to prevent and mitigate the damages. In this paper, we have estimated the vulnerable disaster areas based on the records of the past damage histories and performed the risk assessment of the social infrastructures in Busan city to provide the fundamental information for the real-time monitoring system and the systematic approach for disaster prevention system to build V-City model. These results are illustrated by using Geographical Information System (GIS) and the order of vulnerable disaster areas are also estimated.

• Earthquakes and Structures
• /
• v.13 no.6
• /
• pp.573-588
• /
• 2017

The earthquake input is required when the soil-structure interaction (SSI) analysis is performed by the direct finite element method. In this paper, the earthquake is considered as the obliquely incident plane body wave arising from the truncated linearly elastic layered half space. An earthquake input method is developed for the time-domain three-dimensional SSI analysis. It consists of a new site response analysis method for free field and the viscous-spring artificial boundary condition for scattered field. The proposed earthquake input method can be implemented in the process of building finite element model of commercial software. It can result in the highly accurate solution by using a relatively small SSI model. The initial condition is considered for the nonlinear SSI analysis. The Daikai subway station is analyzed as an example. The effectiveness of the proposed earthquake input method is verified. The effect of the obliquely incident earthquake is studied.

• Journal of the Korean Society of Safety
• /
• v.30 no.3
• /
• pp.135-140
• /
• 2015

Individuals who are vulnerable during disaster - including elderly, people with disabilities, children, pregnant women and etc - have a strong desire to protect themselves when disaster strikes since they are less capable to deal with the impact of disaster. Their experience and effort to keep them safe can be used as a resource to reduce the impacts of disaster not only for them but also for the community as a whole. Therefore, voluntary disaster management program will contribute to our society as a tool to respond effectively to disaster not only to meet the vulnerable's special needs but also to enhance community safety and public interest. This paper suggests a model that able "disaster vulnerable population" to take a leadership role in identifying risk and vulnerability factors, recommending disaster management strategy, and through that, contributing to enhance society's disaster plan. Therefore, this study aimed to surveyed individuals including "disaster vulnerable population" in order to assess the vulnerable's participation in disaster related volunteer work and surveyed associated institutions(volunteer centers, community centers) in order to research currently existing relevant programmes and the participation of "disaster vulnerable population" in such programmes. Also conducted focus group interview to explore voluntary program which will possibly integrate "disaster vulnerable population" into disaster management activities. As a result, three types of voluntary disaster management programs - education, public-relations, and activity - were suggested.

• Journal of Korean Academy of Nursing
• /
• v.51 no.6
• /
• pp.648-660
• /
• 2021

Purpose: This study aimed to develop an emerging infectious disease (COVID-19) simulation module for nursing students and verify its effectiveness. Methods: A one-group pretest-posttest quasi-experimental study was conducted with 78 under-graduate nursing students. A simulation module was developed based on the Jeffries simulation model. It consisted of pre-simulation lectures on disaster nursing including infectious disease pandemics, practice, and debriefings with serial tests. The scenarios contained pre-hospital settings, home visits, arrival to the emergency department, and follow-up home visits for rehabilitation. Results: Disaster preparedness showed a statistically significant improvement, as did competencies in disaster nursing. Confidence in disaster nursing increased, as did willingness to participate in disaster response. However, critical thinking did not show significant differences between time points, and neither did triage scores. Conclusion: The developed simulation program targeting an infectious disease disaster positively impacts disaster preparedness, disaster nursing competency, and confidence in disaster nursing, among nursing students. Further studies are required to develop a high-fidelity module for nursing students and medical personnel. Based on the current pandemic, we suggest developing more scenarios with virtual reality simulations, as disaster simulation nursing education is required now more than ever.

• Journal of Coastal Disaster Prevention
• /
• v.5 no.4
• /
• pp.183-192
• /
• 2018

In recent years, coastal areas have been suffering from coastal erosion, such as destruction of coastal roads and military facilities. In this study, the Delft3D model was used to analyze the sediment transport pattern due to seasonal characteristics of summer and winter waves in Anmok beach of the East coast. Typhoon and high waves are mainly are coming from ENE direction in the summer season and the flows occur in the northward. In winter, high waves are incident from NE and the flows occur in the southward. These seasonal patterns were simulated by using Delft3D model. As for model input, reanalysis wave data of the past 38 years were used, and the seasonal patterns were analyzed by dividing the whole year into summer and winter season. The grid point of the 38 year reanalysis data is far from the Anmok beach, so the three model grid systems (wide grid -> intermediate grid -> detailed grid) are constructed. Most of the flows in the NW direction occurred in summer, but erosion and deposition was alternated along the coastline. In winter, sediment was deposited near Gangnung Port due to the southern flow and the southern port. Strong winter waves compared to summer tend to cause deposition around Gangnung Port throughout the year.

• Smart Structures and Systems
• /
• v.31 no.5
• /
• pp.469-483
• /
• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2023.11a
• /
• pp.57-58
• /
• 2023

기 발생된 재난 정보를 분석하고 이를 통하여 재난 발생의 원인과 재난 정보를 도출함으로써 재난 예방과 대비를 효과적으로 할 수 있다. 재난 정보를 실시간으로 얻을 수 있는 뉴스 정보, 그리고 국민재난안전포털의 안전관리일일상황 정보 등으로부터 데이터를 수집하여 이를 분석하고, 운용할 수 있는 체계 연구를 통하여 지자체 등에서 재난관련 예산 편성, 우선순위 설정 등에 활용하여 발생 재난에 대한 다양한 예방, 대비, 대응을 함으로써 재난 발생의 최소화, 발생된 재난의 조기 대응, 그리고 다양한 연구 활용을 할 수 있는 기반체계를 제공한다.