• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.87-94
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• 1997

There are many kinds of complicated equipments in the chemical plants. So the chemical plants have high possibility of accidents. Hazard analysis is one of the basic tasks to ensure the safety of chemical plants. However, it has many shortcomings. To overcome the problems, there have been attempts to automate this work by utilizing computer technology, particularly knowledge-based technique. However, many of the past approaches are lacking in properties: safeguard consideration, accident diversity, cause and consequence diversity, pathway leading to accidents, and various hazard analysis reasoning. Therefore, in this study, three analysis algorithms were proposed using multimodel approach, and a hazard analysis system, AHA, was developed on G2. The case study was solved with AHA system successfully.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2003.04a
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• pp.224-229
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• 2003

• Fire Science and Engineering
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• v.17 no.4
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• pp.20-27
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• 2003

Hazard Analysis is one of the basic tasks to ensure the safety of chemical plants. However, it is an arduous, tedious, time-consuming work and requires multidisciplinary knowledge and demands considerable cognitive load from the analysts. To overcome these problems, there have been attempts to automate this work by utilizing computer technology, particularly in the area of knowledge-based technique. There is two methods in the risk assessment of Chemical plant; quantitative and qualitative risk assessment. Both of them have been applied respectively, but if the integrated method of quantitative and qualitative risk assessments is used, all of the advantage of two methods can be applied. It is difficult to carry out integrated risk management of chemical plant. Therefore, automated integration system of risk management is necessary. We developed S/W Automated System for Hazard Screening & Analysis(ASCA) and applied to practical plant. By applying ASCA to case study, we can get the information about relative ranks of equipments, variable deviation, and consequence of potential accident. In this study, we applied ASCA to the H.T.U(Hydrotreating Unit) of the process to produce aromatic material. We could know relative ranks of equipments, variable deviation of malfunction in storage tank, D-101, and consequence of potential accident using ASCA. If integrated risk management in the chemical plant is applied, we can develop the emergency plan and prevent the accident.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.1-20
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• 2018

Despite many measures, still from time to time catastrophic events occur, even after reviewing potential scenarios with HAZID tools. Therefore, it is evident that in order to prevent such events, answering the question: "What can go wrong?" requires more enhanced HAZID tools. Recently, new system based approaches have been proposed, such as STPA (system-theoretic process analysis) and Blended Hazid, but for the time being for several reasons their availability for general use is very limited. However, by making use of available advanced software and technology, traditional HAZID tools can still be improved in degree of completeness of identifying possible hazards and in work time efficiency. The new HAZID methodology proposed here, the Data-based semi-Automatic HAZard IDentification (DAHAZID), seeks to identify possible scenarios with a semi-automated system approach. Based on the two traditional HAZID tools, Hazard Operability (HAZOP) Study and Failure Modes, Effects, and Criticality Analysis (FMECA), the new method will minimize the limitations of each method. This will occur by means of a thorough systematic preparation before the tools are applied. Rather than depending on reading drawings to obtain connectivity information of process system equipment elements, this research is generating and presenting in prepopulated work sheets linked components together with all required information and space to note HAZID results. Next, this method can be integrated with proper guidelines regarding process safer design and hazard analysis. To examine its usefulness, the method will be applied to a case study.

• Journal of the Korean Society of Safety
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• v.13 no.1
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• pp.77-84
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• 1998

Hazard and operability (HAZOP) analysis is one of the safety analysis method that is used in the chemical complex, because it can systematically identify causes and consequences of all the deviation that could occur. Since this method needs to hire specialized experts, it is costly and time-consuming. Therefore HAZOP Expert System has been developed to automate this analysis. This approach introduced object-oriented method and knowledge representation which is hierarchical tree of units to supply flexibility in the system, functional semantic network, propagation equation and rule-chaining method to set up the expert system for automating HAZOP analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• 한국가스학회:학술대회논문집
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• 2003.05a
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• pp.246-251
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• 2003

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.251-261
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• 2019

The importance of autonomous driving systems that utilize V2X services such as V2V(Vehicle to Vehicle) and V2I(Vehicle to Infrastructure) for safer and more comfortable driving is increasing with the recent development of autonomous vehicles. Partly autonomous vehicles based on environmental sensors have limitations for predicting and determining areas beyond the recognition distance of the mounted sensors and in response to atypical objects that are difficult to detect. Therefore, it is important to utilize the V2X service to improve the limit of sensor detection performance and to make driving safer and more comfortable. However, there may be an accident risk of autonomous vehicles due to incorrect information provided by V2X. Thus, the application of technology to prevent this needs to be considered. In this pater, we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to derive the risk sources of autonomous vehicles due to V2I malfunctions by using the communication between vehicles and infrastructure among V2X. We also developed ASIL ratings based on the simulations and real vehicle tests of the malfunctions of major cases of usnig V2I.

• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.91-98
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• 2009

The "3+3 Process" for safety critical software for nuclear power plants' I&C (Instrumentation and Control system) has been developed in this work. The main idea of the "3+3 Process" is both to simplify the software development and safety analysis in three steps to fulfill the requirements of a software safety plan [1]. The "3-Step" software development process consists of formal modeling and simulation, automated code generation and coverage analysis between the model and the generated source codes. The "3-Step" safety analysis consists of HAZOP (hazard and operability analysis), FTA (fault tree analysis), and DV (design validation). Put together, these steps are called the "3+3 Process". This scheme of development and safety analysis minimizes the V&V work while increasing the safety and reliability of the software product. For assessment of this process, validation has been done through prototyping of the SDS (safety shut-down system) #1 for PHWR (Pressurized Heavy Water Reactor).

• Korean Journal of Radiology
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• v.24 no.9
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• pp.849-859
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• 2023

Objective: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. Materials and Methods: We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. Results: Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the non-sarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the non-myosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25-2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84-3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08-3.54]; P = 0.027). Conclusion: Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.