• Computers and Concrete
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• v.12 no.1
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• pp.91-107
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• 2013

Corrosion of RC bridge decks eventually leads to delamination, severe cracking and spalling of the concrete cover. This is a prevalent deterioration mechanism and demands for the most costly repair interventions during the service life of bridges worldwide. On the other hand, decisions for repairs are usually made whenever the extent of a limit crack width, reported in routine visual inspections, exceeds an acceptable threshold level. In this paper, while random fields are applied to account for spatial variation of governing parameters of the corrosion process, an analytical model is used to simulate the corrosion induced crack width. However when dealing with random fields, the Monte Carlo simulation is apparently an inefficient and time consuming method, hence the utility of neural networks as a surrogate in simulation is investigated and found very promising. The proposed method can be regarded as an invaluable tool in decision making concerning maintenance of bridges.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.241-243
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• 2001

이동 컴퓨팅 환경이 급속하게 발전하면서 GIS 분야에서도 이동 클라이언트를 이용한 다양한 서비스에 대한 연구가 진행되고 있다. 특히, 이동 클라이언트를 이용한 공간 데이터 변경의 경우에 동시성 제어를 수행해야 하는데 기존 클라이언트-서버 환경에서 사용되는 잠금 기법은 잠금 획득을 위한 긴 대기시간 때문에 적합하지 않다. 본 논문에서는 이동 컴퓨팅 환경에서의 공간 데이터 변경을 위한 3-계층 구조를 제시하며 이 구조에서의 대리 트랜잭션 모델을 정의한다. 또한, 이동클라이언트의 공간 데이터 변경 트랜잭션의 동시성 제어를 위해 전통적인 낙관 기법을 확정하여 공간 데이터에 적합한 확인 기법을 제시하며 동시성 제어에서 트랜잭션 직렬화 보장의 예를 보인다.

• Asian Journal of Atmospheric Environment
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• v.2 no.1
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.2
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• pp.249-258
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• 2008

Historical emission data for 11 polychlorinated biphenyls (PCBs) and a regional multimedia environmental model, CoZMo-POP 2, were used to predict air concentrations and congener patterns in Korea. The total emission value for South Korea was allocated to sub-provinces and cities based on their population. The spatial distribution of PCB emissions was generally correlated with that of measured atmospheric levels, suggesting that population could be a good surrogate for the intensity of PCB emission in Korea. The simulated time trends of air concentrations well reflected those of emission with a peak in the mid-1970s and insignificant levels in the 2030s. The model predicted that the contribution of volatile PCBs had increased after emission reduction iii the 1970s. This trend would continue until the early 2030s. The measured and modeled PCB levels in the 2000s were in an agreement of an order of magnitude, and their congener patterns were very similar. Consequently, despite of high uncertainty for emission estimates, the emission data for Korea used in this study is considered to be reliable. The results of this study could be compared with simulation data based on a new emission inventory to be developed by measurements in the near future.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.486-495
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• 2021

Background: Particulate matter (PM) is one of the leading causes of premature death worldwide. Previous studies in South Korea have applied a relative risk calculated from Western populations when estimating the disease burden attributable to PM. However, the relative risk of PM on health outcomes may not be the same across different countries or regions. Objectives: This study aimed to estimate the premature deaths and socioeconomic costs attributable to long-term exposure to PM in South Korea. We considered not only the difference in PM concentration between regions, but also the difference in relative risk. Methods: National monitoring data of PM concentrations was obtained, and missing values were imputed using the AERMOD model and linear regression model. As a surrogate for relative risk, hazard ratios (HRs) of PM for cardiovascular and respiratory mortality were estimated using the National Health Insurance Service-National Sample Cohort. The nation was divided into five areas (metropolitan, central, southern, south-eastern, and Gangwon-do Province regions). The number of PM attributable deaths in 2018 was calculated at the district level. The socioeconomic cost was derived by multiplying the number of deaths and the statistical value of life. Results: The average PM₁₀ concentration for 2014~2018 was 45.2 ㎍/m³. The association between long-term exposure to PM₁₀ and mortality was heterogeneous between areas. When applying area-specific HRs, 23,811 premature deaths from cardiovascular and respiratory disease in 2018 were attributable to PM₁₀ (reference level 20 ㎍/m³). The corresponding socioeconomic cost was about 31 trillion won. These estimated values were higher than that when applying nationwide HRs. Conclusions: This study is the first research to estimate the premature mortality caused by long-term exposure to PM using relative risks derived from the national population. This study will help precisely identify the national and regional health burden attributed to PM and establish the priorities of air quality policy.

• Journal of Bio-Environment Control
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• v.26 no.2
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• pp.87-99
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• 2017

Recently the increase in an abnormal climate events and meteorological disasters which causes a great damage to greenhouse facilities. To minimize and evaluate the expected damages it is necessary to prepare countermeasures and a management system in advance. For this purpose, a quantitative analysis of weather and abnormal climate are needed to investigate protected cultivation areas which are vulnerable to natural disasters. This study focused on protected cultivation areas in Jeolla province, South Korea. Surrogate variables were calculated to analyze the vulnerable areas to meteorological disasters, and spatial distribution analysis was also performed by using GIS to present vulnerable areas on map. The map thus created and was compared with actual data of damages by meteorological disasters which occurred in target areas. The result of the comparison is as follows: About 50% of the target areas showed an agreement between the map created in this study and the actual data, these areas includes Gwangju metropolitan city, Naju city, Yeongam County, Jangseong County, Hampyeong County, and Haenam County. On the other hand, other areas, including Gunsan city, Mokpo city, and Muan County, suffered low damage in spite of high levels of vulnerability to meteorological disasters. This result was considered to be affected by such variables as different structural designs and management systems of greenhouses by region. This study carried out an analysis of meteorological data to find out more detailed vulnerability to protected cultivation area and to create a map of vulnerable protected cultivation areas. In addition, the map was compared with the record of natural disasters to identify actual vulnerable areas. In conclusion, this study can be utilized as basic data for preventing and reducing damages by meteorological disasters in terms of design and management of greenhouses.