• Title/Summary/Keyword: Fire casualties

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Hazardous and Noxious Substances (HNSs) Styrene Detection Using Spectral Matching and Mixture Analysis Methods (분광정합 및 혼합 분석 방법을 활용한 위험·유해물질 스티렌 탐지)

  • Jae-Jin Park;Kyung-Ae Park;Tae-Sung Kim;Moonjin Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.spc
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    • pp.1-10
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    • 2022
  • As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m2. The study is expected to play a major role in marine HNS monitoring.

Development of Detailed Design Automation Technology for AI-based Exterior Wall Panels and its Backframes

  • Kim, HaYoung;Yi, June-Seong
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1249-1249
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    • 2022
  • The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

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A Study on Evaluation Parameters of Safety City Models (안전도시 모델의 평가지표에 관한 연구)

  • Joon-Hak Lee;Okkyung Yuh
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.2
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    • pp.1-13
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    • 2023
  • As interest in urban safety has increased since COVID-19, various institutions have developed and used indicators that evaluate the safety city model. Yongsan-gu was ranked No. 1 in 2021 by Social Safety Index evaluation and was selected as the safest city in Korea. However, the Itaewon disaster in Yongsan-gu in 2022 caused many casualties. The study of indicators for evaluating cities' safety was necessary. This study aims to examine domestic and foreign safe city models and review the differences between each model and the indicators used to evaluate safe cities. As a result of collecting 11 safe city models and analyzing each evaluation index, safe city models can be classified into program-based safe city models, such as the World Health Organization's International safe community and the UN Office for Disaster Risk Reduction's International Safe city. Considering the diversification of threats to safety, it is reasonable to comprehensively consider digital security, health safety, infrastructure safety, personal safety, environmental safety, traffic safety, fire safety, crime safety, life safety, suicide, and infectious diseases when evaluating safe cities as evaluation parameters.

Prediction of Damages and Evacuation Strategies for Gas Leaks from Chlorine Transport Vehicles (염소 운송차량 가스누출시 피해예측 및 대피방안)

  • Yang, Yong-Ho;Kong, Ha-Sung
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.407-417
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    • 2024
  • The objective of this study is to predict and reduce potential damage caused by chlorine gas leaks, a hazardous material, when vehicles transporting it overturn due to accidents or other incidents. The goal is to forecast the anticipated damages caused by chlorine toxicity levels (ppm) and to design effective response strategies for mitigating them. To predict potential damages, we conducted quantitative assessments using the ALOHA program to calculate the toxic effects (ppm) and damage distances resulting from chlorine leaks, taking into account potential negligence of drivers during transportation. The extent of damage from toxic gas leaks is influenced by various factors, including the amount of the leaked hazardous material and the meteorological conditions at the time of the leak. Therefore, a comprehensive analysis of damage distances was conducted by examining various scenarios that involved variations in the amount of leakage and weather conditions. Under intermediate conditions (leakage quantity: 5 tons, wind speed: 3 m/s, atmospheric stability: D), the estimated distance for exceeding the AEGL-2 level of 2 ppm was calculated to be 9 km. This concentration poses a high risk of respiratory disturbance and potential human casualties, comparable to the toxicity of hydrogen chloride. In particular, leaks in urban areas can lead to significant loss of life. In the event of a leakage incident, we proposed a plan to minimize damage by implementing appropriate response strategies based on the location and amount of the leak when an accident occurs.

Evaluating Impact Resistance of Externally Strengthened Steel Fiber Reinforced Concrete Slab with Fiber Reinforced Polymers (섬유 보강재로 외부 보강된 강섬유 보강 콘크리트 슬래브의 충격저항성능 평가)

  • Yoo, Doo-Yeol;Min, Kyung-Hwan;Lee, Jin-Young;Yoon, Young-Soo
    • Journal of the Korea Concrete Institute
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    • v.24 no.3
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    • pp.293-303
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    • 2012
  • Recently, as construction technology improved, concrete structures not only became larger, taller and longer but were able to perform various functions. However, if extreme loads such as impact, blast, and fire are applied to those structures, it would cause severe property damages and human casualties. Especially, the structural responses from extreme loading are totally different than that from quasi-static loading, because large pressure is applied to structures from mass acceleration effect of impact and blast loads. Therefore, the strain rate effect and damage levels should be considered when concrete structure is designed. In this study, the low velocity impact loading test of steel fiber reinforced concrete (SFRC) slabs including 0%~1.5% (by volume) of steel fibers, and strengthened with two types of FRP sheets was performed to develop an impact resistant structural member. From the test results, the maximum impact load, dissipated energy and the number of drop to failure increased, whereas the maximum displacement and support rotation were reduced by strengthening SFRC slab with FRP sheets in tensile zone. The test results showed that the impact resistance of concrete slab can be substantially improved by externally strengthening using FRP sheets. This result can be used in designing of primary facilities exposed to such extreme loads. The dynamic responses of SFRC slab strengthened with FRP sheets under low velocity impact load were also analyzed using LS-DYNA, a finite element analysis program with an explicit time integration scheme. The comparison of test and analytical results showed that they were within 5% of error with respect to maximum displacements.