• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.158-164
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• 2014

LEO(Low Earth Orbit) Satellite which is discarded should be reentered to atmosphere in 25 years by '25 years rule' of IADC(Inter-Agency Space Debris Coordination Committee) Guidelines. If the parts of satellite are survived from severe aerothermodynamic condition, it could damage to human and property. South Korea operates KOMPSAT-2 and STSAT series as LEO satellite. It is necessary to dispose of them by reentering atmosphere. Therefore this paper analyze the trajectory, survivability, casualty area and casualty probability of a virtual LEO satellite using ESA(European Space Agency)'s DRAMA(Debris Risk Assesment and Mitigation Analysis) tool. As a result, it is noted that casuality area is $15.2742m^2$ and casualty probability is 5.9614E-03 then will be survived 198.831kg.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.2
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• pp.121-125
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• 2010

Carbon Capture and Storage (CCS) technology mitigates the emission amount of carbon dioxide into the atmosphere and can reduce green house effect which causes the climate change. Deep saline aquifer or obsolete oil/gas storage etc. in the marine geological structure are considered as the candidates for the storage. The injection and storage relating technology have been interested in the global society, however the adverse effect caused by leakage from the system failure. Even the safety level of the CCS is very high and there is almost no possibility to leak but, still the risk to marine ecosystem of the high concentrated carbon dioxide exposure is not verified. The present study introduces the system and environmental risk assessment methods. The feature, event and process approach can be a good starting point and we found the some possibility from the fault tree analysis for evaluation. From the FEP analysis, we drove the possible scenario which we need to concentrate on the construction and operation stages.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.289-302
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• 2017

The key risk analysis technologies for the re-entry of space objects into Earth's atmosphere are divided into four categories: cataloguing and databases of the re-entry of space objects, lifetime and re-entry trajectory predictions, break-up models after re-entry and multiple debris distribution predictions, and ground impact probability models. In this study, we focused on reentry prediction, including orbital lifetime assessments, for space situational awareness systems. Re-entry predictions are very difficult and are affected by various sources of uncertainty. In particular, during uncontrolled re-entry, large spacecraft may break into several pieces of debris, and the surviving fragments can be a significant hazard for persons and properties on the ground. In recent years, specific methods and procedures have been developed to provide clear information for predicting and analyzing the re-entry of space objects and for ground-risk assessments. Representative tools include object reentry survival analysis tool (ORSAT) and debris assessment software (DAS) developed by National Aeronautics and Space Administration (NASA), spacecraft atmospheric re-entry and aerothermal break-up (SCARAB) and debris risk assessment and mitigation analysis (DRAMA) developed by European Space Agency (ESA), and semi-analytic tool for end of life analysis (STELA) developed by Centre National d'Etudes Spatiales (CNES). In this study, various surveys of existing re-entry space objects are reviewed, and an efficient re-entry prediction technique is suggested based on STELA, the life-cycle analysis tool for satellites, and DRAMA, a re-entry analysis tool. To verify the proposed method, the re-entry of the Tiangong-1 Space Lab, which is expected to re-enter Earth's atmosphere shortly, was simulated. Eventually, these results will provide a basis for space situational awareness risk analyses of the re-entry of space objects.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.195-198
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• 2008

In this study we analyzed flood runoff and flood characteristics of an small urban river basin which is in an apartment complex in Yewol-Dong, Buchun-Si, Gyunggi-Do. A little discharge normally flows in the river, however this small river has a relatively high potential of flood damage risk in the flood season due to the high flood level and velocity. Therefore we used the GIS data, cross section data in the river, HEC-RAS model, etc. for investigating safety of a river against flood runoff and also we investigated the stability of hydraulic structures and ability of flood prevention in the river. As the result of investigation, we found that the river had the risk of flood damage occurrence due to the hydraulic structures constructed for various purposes in the river. So we should analyze backwater effect by the structures and consider the risk factors can be occurred by the flood runoff and velocity for more safe design of a small river basin in the residential area such as an apartment complex in the urban area.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.204-204
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• 2016

Thailand had set the National Water Management Strategy which covered main six areas in the next 12 years, i.e., by priority: (1) water for household, (2) water for agricultural and industrial production, (3) water for flood and drought management, (4) water for quality issue, (5) water from forest conservation and soil erosion protection, (6) water resources management. However due to the climate change impact, there is a question for all strategies is whether to complete this mission under future climate change. If the impact affects our target, we have to clarify how to mitigate or to adapt with it. Vulnerability assessment was conducted under the framework of ADB's (with the parameters of exposure, sensitivity and adaptive capacity) and the assessments were classified into groups due to their different characteristic and the framework of the National Water Management Strategy, i.e., water supply (rural and urban), water for development (agriculture and others), water disasters (floods (flash, overflow), drought, water quality). The assessments identified the parameters concerned and weight factors used for each groups via expert group discussions and by using GIS mapping technology, the vulnerability maps were produced. The maps were verified with present water situation data (floods, drought, water quality). From the analysis result of this water resources management strategy, we found that 30% of all projects face the big impacts, 40% with low impact, and 30% for no impact. It is clear that water-related agencies have to carefully take care approximately 70% of future projects to meet water resources management strategy. It is recommended that additional issues should be addressed to mitigate the impact from climate risk on water resource management of the country, i.e., water resources management under new risk based on development scenarios, relationship with area-based problems, priority definition by viewpoints of risk, vulnerability (impact and occurrence probability in past and future), water management system in emergency case and water reserve system, use of information, knowledge and technology in management, network cooperation and exchange of experiences, knowledge, technique for sustainable development with mitigation and adaptation, education and communication systems in risk, new impact, and emergency-reserve system. These issues will be described and discussed.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Safety and Health at Work
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• v.14 no.4
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• pp.398-405
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• 2023

Background: Starting from March 2020 until December 2021, different phases of Covid-19 pandemic have been identified in Italy, with several containing/lifting measures progressively enforced by the National government. In the present study, we investigate the change in occupational risk during the subsequent pandemic phases and we propose an estimate of the incidence of the cases by economic sector, based on the analysis of insurance claims for compensation for Covid-19. Methods: Covid-19 epidemiological data available for the general population and injury claims of workers covered by the Italian public insurance system in 2020-2021 were analyzed. Monthly Incidence Rate of Covid-19 compensation claims per 100,000 workers (MIRw) was calculated by the economic sector and compared with the same indicator for general population in different pandemic periods. Results: The distribution of Covid-19 MIRw by sector significantly changed during the pandemic related to both the strength of different waves and the mitigation/lifting strategies enforced. The level of occupational fraction was very high at the beginning phase of the pandemic, decreasing to 5% at the end of 2021. Healthcare and related services were continuously hit but the incidence was significantly decreasing in 2021 in all sectors, except for postal and courier activities in transportation and storage enterprises. Conclusion: The analysis of compensation claim data allowed to identify time trends for infection risk in different working sectors. The claim rates were highest for human health and social work activities but the distribution of risk among sectors was clearly influenced by the different stages of the pandemic.

• Journal of Environmental Policy
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• v.13 no.3
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• pp.43-73
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• 2014

Cities in Korea have rapidly urbanized and they are not well prepared for natural disasters which have been increased by climate change. In particular, they often struggle with urban flooding. Recently, green infrastructure has been emphasized as a critical strategy for flood mitigation in developed countries due to its capability to infiltrate water into the ground, provide the ability to absorb and store rainfall, and contribute to mitigating floods. However, in Korea, green infrastructure planning only focuses on esthetic functions or accessibility, and does not think how other functions such as flood mitigation, can be effectively realized. Based on this, we address this critical gap by suggesting the new green infrastructure planning framework for improving urban water cycle and maximizing flood mitigation capacity. This framework includes flood vulnerability assessment for identifying flood risk area and deciding suitable locations for green infrastructure. We propose the use of the combination of frequency ratio model and GIS for flood vulnerability assessment. The framework also includes the selection process of green infrastructure practices under local conditions such as geography, flood experience and finance. Finally, we applied this planning framework to the case study area, namely YeonJe-gu an Nam-gu in Busan. We expect this framework will be incorporated into green infrastructure spatial planning to provide effective decision making process regarding location and design of green infrastructure.

• Journal of Environmental Impact Assessment
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• v.31 no.2
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• pp.106-116
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• 2022

Multilateral Development Banks (MDBs) have actively responded to global climate change, and developed and operated the Common Principles for Climate Finance Tracking. They estimate climate finance in a granular manner with a conservative view. In other words, the MDBs track their financing only for those elements or proportions of projects that directly contribute to or promote climate adaptation or mitigation. The MDBs have reported jointly on climate finance since the first edition in 2012, which reported for 2011 and up to the 10th edition in 2021, which reported for 2020. MDBs apply two difference methodologies for adaptation and mitigation. For adaptation, the methodology is based on a context and location specific approach and captures the amounts associated with activities directly linked to vulnerability to climate change. For mitigation, it is evaluated in accordance with a comprehensive list of activities thatreduce greenhouse gas emissions. The result of climate risk assessment is one of the major due diligence items for MDBs alongside with that of environmental and social impact assessment. Under the circumstance that many countries endeavor to deal with climate change at project level, it is meaningful to understand how MDBs have addressed climate change issues in their project approval process. This would be a good reference to establish a methodology for responding to climate change and to expand scope of environmental and social impact assessment.

• Smart Structures and Systems
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• v.16 no.5
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• pp.873-889
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• 2015

In civil engineering, probabilistic seismic risk assessment is used to predict the economic damage to a lifeline system of possible future earthquakes. The results are used to plan mitigation measures and to strengthen the structures where necessary. Instead, after an earthquake public authorities need mathematical models that compute: the damage caused by the earthquake to the individual vulnerable components and links, and the global behavior of the lifeline system. In this study, a framework that was developed and used for prediction purpose is modified to assess the consequences of an earthquake in quasi real-time after such earthquake happened. This is possible because nowadays entire seismic regions are instrumented with tight networks of strong motion stations, which provide and broadcast accurate intensity measure maps of the event to the public within minutes. The framework uses the broadcasted map and calculates the damage to the lifeline system and its component in quasi real-time. The results give the authorities the most likely status of the system. This helps emergency personnel to deal with the damage and to prioritize visual inspections and repairs. A highway transportation network is used as a test bed but any lifeline system can be analyzed.