• Title/Summary/Keyword: building demolitions

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Analysis of Influencing Factors on Asbestos Demolitions Using a Text Mining Method (텍스트 마이닝 기법을 활용한 석면해체·제거작업 영향 요인 분석)

  • Lee, Jae-Woo;Kim, Do-Hyun;Kim, Yu-Jin;Noh, Jae-Yun;Han, Seungwoo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2022.04a
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    • pp.39-40
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    • 2022
  • The use of asbestos has been completely prohibited in Korea since 2015. Therefore, nationally, the asbestos demolitions in the building are actively underway. In the process of demolishing asbestos, scattering dust occurs, which poses a risk to human body. These dusts causes fatal disease, and especially there is an increasing concern of safety about construction workers and building users. Until this day, however, only few researches have been conducted on asbestos demolishing process. Accordingly, it is necessary to analyze key factors and to develop a safety prediction model for workers. This study is an early stage of building quantified DB, and aims to actualize the safety problems of asbestos demolishing process using text mining method.

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Development of an ANN based Model for Predicting Scattering Asbestos Concentration during Demolition Works (인공신경망 기반 석면 해체·제거작업 후 비산 석면 농도 예측 모델 개발)

  • Kim, Do-Hyun;Kim, Min-Soo;Lee, Jae-Woo;Han, SeungWoo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2022.11a
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    • pp.53-54
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    • 2022
  • There is an increasing demand for prediction of asbestos concentration which has an fatal effect on human body. While demolishing asbestos, the dust scatters and makes workers be exposed to danger. Up to this date, however, factors that particularly influences have not considered in predicting asbestos concentration. Most of the studies could not quantify the distribution of asbestos. Also, they did not use nominal data on buildings as important factors. Therefore, this study aims to build an asbestos concentration prediction model by quantifying distribution of asbestos and using nominal data of buildings based on Artificial Neural Network (ANN). This model can give significant contribution of improving the safety of workers and be useful for finding effective ways to demolish asbestos in planning.

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Case Study of Explosive Demolition for a Structure in Urban Area (Explosive Demolition of Former Sung-Nam City Hall to Construct Sung-Nam City Hospital) (도심지 구조물 발파해체 적용사례 (성남시 의료원 건립을 위한 구성남시청사 발파해체))

  • Jung, Min-Su;Song, Young-Suk;Heo, Eui-Haeng;Kim, Hyo-Jin
    • Explosives and Blasting
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    • v.30 no.1
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    • pp.17-28
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    • 2012
  • Building demolitions at urban area make some inconvenience to neighborhood through generating noises, ground vibrations, and dusts. For this reason, various methods to control such environmental impacts have been being designed and practiced. Among the methods, the use of explosive demolition is rapidly increasing because it can minimize the inconveniency as well as decrease the working time and cost. In this respect, the old Sung-Nam city hall, which was a Rahmen structure comprised of beams, slabs and columns, was decided to be demolished by explosive demolition. This paper shows that explosive demolition can be the most suitable way of removing old buildings eco-friendly, safely, and economically by showing the observation results obtained from the actual demolition operation for the Sung-Nam city hall.