• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.22-28
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• 2021

This is a basic study on the development of deep learning-based algorithms to detect smoke before the smoke detector operates in the event of a ship fire, analyze and utilize the detected data, and support fire suppression and evacuation activities by predicting the spread of smoke before it spreads to remote areas. Proposed algorithms were reviewed in accordance with the following procedures. As a first step, smoke images obtained through fire simulation were applied to the YOLO (You Only Look Once) model, which is a deep learning-based object detection algorithm. The mean average precision (mAP) of the trained YOLO model was measured to be 98.71%, and smoke was detected at a processing speed of 9 frames per second (FPS). The second step was to estimate the spread of smoke using the coordinates of the boundary box, from which was utilized to extract the smoke geometry from YOLO. This smoke geometry was then applied to the time series prediction algorithm, long short-term memory (LSTM). As a result, smoke spread data obtained from the coordinates of the boundary box between the estimated fire occurrence and 30 s were entered into the LSTM learning model to predict smoke spread data from 31 s to 90 s in the smoke image of a fast fire obtained from fire simulation. The average square root error between the estimated spread of smoke and its predicted value was 2.74.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.395-408
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• 2021

In this study, we investigated the effects of wind speed and direction on building fires using GIS and a CFD model. We conducted numerical simulations for a fire event that occurred at an apartment in Ulsan on October 8, 2020. For realistic simulations, we used the profiles of wind speeds and directions and temperatures predicted by the local data assimilation and prediction system (LDAPS). First, using the realistic boundary conditions, we conducted two numerical simulations (a control run, CNTL, considered the building fire and the other assumed the same conditions as CNTL except for the building fire). Then, we conducted the additional four simulations with the same conditions as CNTL except for the inflow wind speeds and direction. When the ignition point was located on the windward of the building, strong updraft induced by the fire had a wide impact on the building roof and downwind region. The evacuation floor (15th floor) played a role to spread fire to the downwind wall of the building. The weaker the wind speed, the narrower fire spread around the ignition point, but the higher the flame above the building reaches. When the ignition point was located on the downwind wall of the building, the flame didn't spread to the upwind wall of the building. The results showed that wind speed and direction were important for the flow and temperature (or flame) distribution around a firing building.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.4
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• pp.75-83
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• 2023

Apart from implementing hardware solutions like raising the crest freeboard of coastal structures to efficiently counter wave-overtopping, there is a simultaneous requirement for software-driven disaster mitigation strategies. These tactics involve the swift and accurate dissemination of wave-overtopping information to the inland regions of coastal zones, enabling the regulation of evacuation procedures and movement. In this study, a method was proposed to estimate wave-overtopping by utilizing the temporal variation of wave heights exceeding the structure's crown level, with the aim of developing an on-site wave measurement system for providing wave-overtopping information in the field. Laboratory model experiments were conducted on vertical seawall structures to measure wave-overtopping volumes and wave runup heights under different wave conditions and structural freeboard variations. By assuming that the velocity of water inundation on the top of the structure during wave-overtopping events is equivalent to the long-wave velocity, an overtopping discharge coefficient was introduced. This coefficient was utilized to estimate the rate of wave-overtopping based on the temporal changes in wave runup heights measured at the top of the structure. Upon reasonably calculating the overtopping discharge coefficient, it was verified that the estimation of wave-overtopping could be achieved solely based on the wave runup heights.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.169-177
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• 2010

Recently due to the typhoon and extreme rainfall induced by abnormal weather and climate change, the probability of severe damage to human life and property is rapidly increasing. Thus it is necessary to create adequate and reliable flood risk map in preparation for those natural disasters. The study area is Seo-gu in Daegu which is located near Geumho river, one of the tributaries of Nakdong river. Inundation depth and velocity at each time were calculated by applying FLUMEN model to the target area of interest, Seo-gu in Daegu. And the research of creating flood risk map was conducted according to the Downstream Hazard Classification Guidelines of USBR. The 2-dimensional inundation analysis for channels and protected lowland with FLUMEN model was carried out with the basic assumption that there's no levee failure against 100 year precipatation and inflow comes only through the overflowing to the protected lowland. The occurrence of overflowing was identified at the levee of Bisan-dong located in Geumho watershed. The level of risk was displayed for house/building residents, drivers and pedestrians using information about depth and velocity of each node computed from the inundation analysis. Once inundation depth map and flood risk map for each region is created with this research method, emergency action guidelines for residents can be systemized and it would be very useful in establishing specified emergency evacuation plans in case of levee failure and overflowing resulting from a flood.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.28-33
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• 2020

Recently, the overseas construction market has been actively promoted for about 10 years, and overseas dam construction has been continuously performed. For the economic and safe construction of the dam, it is important to prepare the main dam construction plan considering the design frequency of the diversion tunnel and the cofferdam. In this respect, the prediction of river level during the rainy season is significant. Since most of the overseas dam construction sites are located in areas with poor infrastructure, the most efficient and economic method to predict the water level in dam construction is to use the upstream water level. In this study, a linear regression model, which is one of the simplest statistical methods, was proposed and examined to predict the downstream level from the upstream level. The Pyeongchang River basin, which has the characteristics of the upper stream (mountain stream), was selected as the target site and the observed water level in Pyeongchang and Panwoon gaging station were used. A regression equation was developed using the water level data set from August 22th to 27th, 2017, and its applicability was tested using the water level data set from August 28th to September 1st, 2018. The dependent variable was selected as the "level difference between two stations," and the independent variable was selected as "the level of water level in Pyeongchang station two hours ago" and the "water level change rate in Pyeongchang station (m/hr)". In addition, the accuracy of the developed equation was checked by using the regression statistics of Root Mean Square Error (RMSE), Adjusted Coefficient of Determination (ACD), and Nach Sutcliffe efficiency Coefficient (NSEC). As a result, the statistical value of the linear regression model was very high, so the downstream water level prediction using the upstream water level was examined in a highly reliable way. In addition, the results of the application of the water level change rate (m/hr) to the regression equation show that although the increase of the statistical value is not large, it is effective to reduce the water level error in the rapid level rise section. Accordingly, this is a significant advantage in estimating the evacuation water level during main dam construction to secure safety in construction site.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.37-44
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• 2012

There are approximately 25,724 shelters to which people can be quickly evacuated for safety in case of emergency across the nation, and Seoul has about 3,870 shelters. Those nationwide shelters are located at a point within a five-minute radius for quick evacuation. Seoul's shelter capacity can hold 285% of its population. The problem is, however, that there is no knowing how many shelters are reachable within five minutes when considering walking speed according to individual differences in age, height, health state, and physical condition. In addition, available service areas become different according to the spatial allocation and distribution of shelters with possible vulnerable points. This study thus defined the pedestrian walking speed at 1m/s, 1.3m/s, and 2m/s by reviewing previous studies and conducted network analysis of the Location Allocation Model with the designated shelters and road networks in Seoul. The results identified the shelter service and vulnerable areas in each administrative district of Seoul according to walking speeds. It was analyzed that the vulnerable areas in which the elderly could not reach a shelter were more than twice as big as those of adult men and women with a fast walking speed.

• Spatial Information Research
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• v.23 no.5
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• pp.41-52
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• 2015

MOLIT (Minister of Land, Infrastructure and Transport) authorized Indoor Spatial Information as Basic spatial information in 2013. It became a legal evidence for constructing and managing Indoor Spatial Information. Although it has a little advantage to utilize as service level that Indoor Spatial Information by laser scan or measurement, it has a lot of problems such as consuming many resources, requiring additional progresses for inputting Object Information. In conclusion, it is inefficient to utilize for the maintenance and domestic AEC/FM field. The purposes of this study is to output Indoor Spatial Information by operating IFC model which based on open BIM and to improve availability of Indoor Spatial Information with data visualization. The open-sources of IFC Exporter, a inner program of Revit (Autodesk Inc), is used to output Indoor Spatial Information. Directs 3D Library is also operated to visualize Indoor Spatial Information. It is possible to inter-operate between XML format and the objects of Indoor Spatial Information. It can be utilized in various field as well. For example COBie linkage in facility management, construction of geo-database using air-photogrammetry of UAV (Unmaned Areal Vehicle), the simulation of large-scale military operations and the simulation of large-scale evacuation. The method that is purposed in this study has outstanding advantages such as conformance with national spatial information policy, high level of interoperability as indoor spatial information objects based on IFC, convenience of editing information, light level of data and simplifying progress of producing information.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.1-10
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• 2018

Recently, localized heavy rainfall has led to increasing flood damage in urban areas such as Gangnam, Seoul ('12), Busan ('13), Ulsan ('16) Incheon and Busan ('17) etc. Urban flooding occurs relatively rapidly compared to flood damage in river basin, and property damage including damage to houses, cars and shopping centers is more serious than facility damage to structures such as levees and small bridges. In Korea, heavy rain warnings are currently announced using the criteria set by KMA (Korea Meteorological Administration). However, these criteria do not reflect regional characteristics and are not suitable to urban flood. So in this study, estimated the flooding limit rainfall amount based on the damage records for Seoul and Ulsan. And for regions that can not estimate the flooding limit rainfall since there is no damage records, we estimated the flooding limit rainfall using a Neuro-Fuzzy model with runoff characteristics. Based on the estimated flooding limit rainfall, the urban flood warning criteria was set. and applied to the actual flood event. As a result of comparing the estimated flooding limit rainfall with the actual flooding limit rainfall, the error of 1.8~20.4% occurred. And evacuation time was analyzed from a minimum of 28 minutes to a maximum of 70 minutes. Therefore, it can be used as a warning criteria in the urban flood.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.71-80
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• 2018

For the stream management, time of concentration is one of the important factors. In particular, as the requirement about various application of the stream increased, accuracy assessment of concentration time in the stream as waterfront area is extremely important for securing evacuation at the flood. the past studies for the assessment of concentration time, however, were only performed on the single hydrological event in the complex basin of natural streams. The development of a assessment methods for the concentration time on the complex hydrological event in a single watershed of urban streams is insufficient. Therefore, we estimated the concentration time using the rainfall- runoff data for the past 10 years (2006~2015) for the Oncheon stream, the representative stream of the Busan, where frequent flood were taken place by heavy rains, in addition, reviewed the reliability using artificial neural network method based on Matlab. We classified a total of 254 rainfalls events based on over unrained 12 hours. Based on the classification, we estimated 6 parameters (total precipitation, total runoff, peak precipitation/ total precipitation, lag time, time of concentration) to utilize for the training and validation of artificial neural network model. Consequently, correlation of the parameter, which was utilized for the training and the input parameter for the predict and verification were 0.807 and 0.728, respectively. Based on the results, we predict that it can be utilized to estimate concentration time and analyze reliability of urban stream.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.136-143
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• 2018

Cellular automata have been applied to simulations in many fields such as astrophysics, social phenomena, fire spread, and evacuation. Using cellular automata, this study develops a model for consequence analysis of the dispersion of hazardous chemicals, which is required for risk assessments of and emergency responses for frequent chemical accidents. Unlike in cases of detailed plant safety design, real-time accident responses require fast and iterative calculations to reduce the uncertainty of the distribution of damage within the affected area. EPA ALOHA and KORA of National Institute of Chemical Safety have been popular choices for these analyses. However, this study proposes an initiative to supplement the model and code continuously and is different in its development of free software, specialized for small and medium enterprises. Compared to the full-scale computational fluid dynamics (CFD), which requires large amounts of computation time, the relative accuracy loss is compromised, and the convenience of the general user is improved. Using Python open-source libraries as well as meteorological information linkage, it is made possible to expand and update the functions continuously. Users can easily obtain the results by simply inputting the layout of the plant and the materials used. Accuracy is verified against full-scale CFD simulations, and it will be distributed as open source software, supporting GPU-accelerated computing for fast computation.