• Geomechanics and Engineering
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• v.17 no.4
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• pp.375-383
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• 2019

In underground retreating longwall coal mining, hard roof collapse is one of the most challenging safety problems for mined-out areas. Identifying precursors for hard roof collapse is of great importance for the development of warning systems related to collapse geohazards and ground control. In this case study, the Xinhe mine was chosen because it is a standard mine and the minable coal seam usually lies beneath hard strata. Real-time monitoring of hard roof collapse was performed in longwall face 5301 of the Xinhe mine using support resistance and microseismic (MS) monitoring; five hard roof collapse cases were identified. To reveal the characteristics of MS activity during hard roof collapse development and to identify its precursors, the change in MS parameters, such as MS event rate, energy release, bursting strain energy, b value and the relationships with hard roof collapse, were studied. This research indicates that some MS parameters showed irregularity before hard roof collapse. For the Xinhe coalmine, a substantial decrease in b value and a rapid increase in MS event rate were reliable hard roof collapse precursors. It is suggested that the b value has the highest predictive sensitivity, and the MS event rate has the second highest.

• The Korean Journal of Emergency Medical Services
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• v.8 no.1
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• pp.179-187
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• 2004

The purpose of the study was to injury types in Daegu subway fire accident, Sampung department store collapse, Mokpo airport civil aircraft accident, and Buan sunken ship disaster. The conclusion obtained from these analyses are as following. 1. The total of victims were Sampung department store collapse(l440 people). Buan sunken ship disaster(355 people), Daegu subway fire accident(340 people), and Mokpo airport civil aircraft accident(110 people). 2. The total of dead people were Sampung department store collapse(502 people), Buan sunken ship disaster(287 people), Daegu subway fire accident(192 people), and Mokpa airport civil aircraft accident(66 people). 3. The total of injured people were Sampung department store collapse(938 people), Daegu subway fire accident(148 people), Mokpo airport civil aircraft accident(84 people), and Buan sunken ship disaster(67 people). 4. The major types of victims presented smoke inhalation such as coughing, dyspnea, and sore throat in Daegu subway fire accident. 5. The major types of victims presented crushing(multiple fractures), vertebral, and soft tissues injuries in Sampung department store collapse. 6. The major types of victims presented multiple fractures. In addition to, a lot of people showed vertebral injuries and shock symptoms in Mokpo airport civil aircraft accident. 7. The major types of victims presented drowning as well lots of hypothermia patients in Buan sunken ship disaster. There were a wide variety of types in human disaster. Therefore, the most important disaster training program need to each disaster aspect in the local emergency medical services system. Moreover, the emergency medical services personnel should be understand and training for injury types of each human disaster.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.825-830
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• 2005

Cut slope and facility of management investigation is the protection of humans and properties. it is very important the prevention of disaster facility and the damage of the slope protection facility. It is very difficult to forecast slope stability, disaster possibility and collapse. It will be able to minimize the damage which it prepare against slope facility and cut slope of deformable investigation and collapse and the disaster. therefore those deformable investigation is important. Investigations execute upheaval, crack, sliding for slope and cut slope reinforcement. Investigation executes forecast in place where the construction problem, the effect which the damage in road traffic or the contiguity facility.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.113-114
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• 2020

During the construction work, many deaths and injuries have occurred in the formwork. This study aims to analyze the perceptions of construction workers about the disaster of formwork collapse. In this study, the IPA(Importance-Performance Analysis) technique was used to analyze the perception of construction workers and derive urgent factors for improvement. As a result of IPA analysis, the fourth quadrant factor needed to be improved first, and the second quadrant factor needed effort distribution. Therefore, it is judged that this study can be used as basic data for safety management and disaster prevention activities.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.313-318
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• 2006

The main cause of natural disaster in Korea is meteorological phenomenon, such as typhoon, heavy rain, storm, rainstorm, heavy snow, hailstorm, overflowing of sea and so on(including thunderstroke, blast, snow damage, freezing and earthquake), and among those disasters, heavy rain takes place most often, and it occupies 80% of total disaster Especially, disaster related to slope collapse (landslide, collapse of retaining wall, burying ect.) takes place every year due to meteorological cause such as localized heavy rain, which is getting stronger. (National Institute for Prevention Disaster, 2002, Meteorological Administration) Accordingly, it is necessary to analyze the features of slope collapse related to natural disaster in Korea, and also to make up counterplan to prevent disaster. This paper will try to analyze potential areas which are susceptible to landslide regarding factors inducing landslide and heavy rain, and to evaluate the potentiality of landslide regarding local particularity of rainfall, furthermore to provide essential information for development of community such as preventing damages from landslide, construction Industry, and effective use of land.

• Wind and Structures
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• v.25 no.1
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• pp.79-100
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• 2017

The use of wind energy resources is developing rapidly in recent decades. There is an increasing number of wind farms in high wind-velocity areas such as the Pacific Rim regions. Wind turbine towers are vulnerable to tropical cyclones and tower failures have been reported in an increasing number in these regions. Existing post-disaster failure case studies were mostly performed through forensic investigations and there are few numerical studies that address the collapse mode simulation of wind turbine towers under strong wind loads. In this paper, the wind-induced failure analysis of a conventional 65 m hub high 1.5-MW wind turbine was carried out by means of nonlinear response time-history analyses in a detailed finite element model of the structure. The wind loading was generated based on the wind field parameters adapted from the cyclone boundary layer flow. The analysis results indicate that this particular tower fails due to the formation of a full-section plastic hinge at locations that are consistent with those reported from field investigations, which suggests the validity of the proposed numerical analysis in the assessment of the performance of wind-farms under cyclonic winds. Furthermore, the numerical simulation allows to distinguish different failure stages before the dynamic collapse occurs in the proposed wind turbine tower, opening the door to future research on the control of these intermediate collapse phases.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.757-766
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• 2022

This study is to examine how well the hydrologic model reproduces the dam collapse. To do this, A hydrologic model FLO-2D is being operated to reproduce dam collapse with rainfall data and surface data in a small dam. In order to examine the performance of the model, the simulation was compared and reviewed with the data collected through the field survey. The results show that it takes about 2 hours to reach 1 km downstream. Inundation areas are about 188,640 m2 by the simulation and the difference from the field investigation is about 6.1%. Ten representative points were selected from the areas where the simulation and the field survey did not match. The discrepancy is less than about 0.08 m and does not appear to be significant. This study will present basic information on disaster preparedness operation and planning to minimize damage caused by sudden collapse of agricultural soil dams in the future.

• Earthquakes and Structures
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• v.18 no.5
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• pp.555-565
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• 2020

The main objective of seismic codes is to prevent structural collapse and ensure life safety. Collapse probability of a structure is usually assessed by making a series of analytical model assumptions. This paper investigates the effect of finite element modeling (FEM) assumptions on the estimated collapse capacity of a reinforced concrete (RC) frame building and points out the modeling limitations. Widely used element formulations and hysteresis models are considered in the analysis. A full-scale, three-story RC frame building was utilized as the experimental model. Alternative finite element models are established by adopting a range of different modeling strategies. Using each model, the collapse capacity of the structure is evaluated via Incremental Dynamic Analysis (IDA). Results indicate that the analytically estimated collapse capacities are significantly sensitive to the utilized modeling approaches. Furthermore, results also show that models that represent stiffness degradation lead to a better correlation between the actual and analytical responses. Results of this study are expected to be useful for in developing proper models for assessing the collapse probability of RC frame structures.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.819-829
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• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.849-858
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• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.