• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 추계 학술논문 발표대회
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• pp.6-7
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• 2019

Asbestos has been widely used for construction materials due to its sound absorption and insulation properties. Despite the announcement that asbestos may cause cancer, asbestos demolition work has become more active. Asbestos was scattered by demolition work and the government started to regulate it. This study was started to predict the scattering asbestos concentration according to the research that it can cause cancer even if the concentration of asbestos meets legal standards. Therefore, in this paper, a regression analysis was conducted to derive a predictive equation after collecting and arranging the variables affecting scattering asbestos. As well as, artificial neural network analysis was used to make a more suitable prediction model.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 가을 학술논문 발표대회
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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.

• 한국산업보건학회지
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• 제30권1호
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• pp.18-27
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• 2020

Objectives: For testing asbestos stabilizer products which are used for the maintenance and management of asbestos-containing materials, durability assessment should accompany the evaluation of basic properties and performance. Therefore, in this study we designed a testing method and constructed a database of durability performance, thereby providing basic data for reliability studies of asbestos stabilizer. Methods: Since the ceiling materials targeted in this study are interior materials, test conditions of 95% relative humidity and 60℃ temperature were designed in consideration of the effect of high relative humidity in summer and seasonal indoor temperatures. Plate-shaped specimens treated with asbestos stabilizers were maintained in a thermo-hygrostat for 5, 10, and 20 days, and then the asbestos scattering prevention rate was measured by air erosion testing. Results: The scattering concentration tended to increase with time under the single humidity condition, and exceeded the indoor air quality standard of 0.01 f/cc, during the 20 days of maintenance. On the other hand, there was little change according to the temperature condition. In the case of a complex condition with temperature and humidity, the results were similar to the humidity test, but the scattering concentration increased more sharply at 20 days. Conclusions: The main deterioration factor that affects the durability of asbestos stabilizer is humidity, and the deterioration is caused by a mechanism in which the stabilizer coated on the surface is re-dissolved by moisture and evaporates or the coating layer is peeled off, which is accelerated by high temperatures.