• Fire Science and Engineering
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• v.17 no.3
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• pp.61-73
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• 2003

Most of the accidents occurred from the chemical plants are related to the catastrophic gas release events when the large amount of toxic materials is leaked from its storage tank or transmitting pipe lines. In this case, the greatest concerns are how the spreading behaviors of leakages are depended on the ambient conditions such as air stability and other environmental factors. Hence, we have focused on the risk assessments and consequential analysis for chlorine as an illustrative example. As appeared in the result, Fire & Explosion Index depicted it a bit dangerous with presenting the comprehensive degrees of hazard 90.7. And as a result of Phast6.0/ALOHA, the trends of each scenario appeared considerably identical although there are some differences in the resulting effects according to the input data for the Gas Model. The consequence analysis is performed numerically based on the dense gas mode. In the future, using more correct input data, material properties, and topographical configuration, the method of this research will be useful for the guideline of the risk assessment when the release of toxicants breaks out.

• Ocean Systems Engineering
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• v.8 no.1
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• pp.41-55
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• 2018

Accidental oil and gas leak is a critical concern for the offshore industry because it can lead to severe consequences and as a result, it is imperative to evaluate the probabilities of occurrence of the consequences of the leakage in order to assess the risk. Event Tree Analysis (ETA) is a technique to identify the consequences that can result from the occurrence of a hazardous event. The probability of occurrence of the consequences is evaluated by the ETA, based on the failure probabilities of the sequential events. Conventional ETA deals with events with crisp failure probabilities. In offshore applications, it is often difficult to arrive at a single probability measure due to lack of data or imprecision in data. In such a scenario, fuzzy set theory can be applied to handle imprecision and data uncertainty. This paper presents fuzzy ETA (FETA) methodology to compute the probability of the outcomes initiated due to oil/gas leak in an actual offshore-onshore installation. Post FETA, sensitivity analysis by Fuzzy Weighted Index (FWI) method is performed to find the event that has the maximum contribution to the severe sequences. It is found that events of 'ignition', spreading of fire to 'equipment' and 'other areas' are the highest contributors to the severe consequences, followed by failure of 'leak detection' and 'fire detection' and 'fire water not being effective'. It is also found that the frequency of severe consequences that are catastrophic in nature obtained by ETA is one order less than that obtained by FETA, thereby implying that in ETA, the uncertainty does not propagate through the event tree. The ranking of severe sequences based on their probability, however, are identical in both ETA and FETA.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.75-80
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• 2005

Because there are only a limited number of means of action that are available for the master to pursue in the event of flooding, onboard decision support system has been required The majority of systems activated during a flooding emergency (such as watertight and semi-watertight doors, bulkhead valves, dewatering pumps etc.) almost exclusively aim to restore a sufficiently high level of subdivision to prevent flooding from spreading through the ship. Even though assuming the flooding scenario is not catastrophic, the use of ballast tanks can be an additional and very effective tool to ensure both prevention of flooding spreading and also improve ship stability. This paper describes an optimization algorithm devised to choose the set of ballast tanks that should be filled in order to achieve an optimal response to a flooding accident.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.15-23
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• 2022

Among the learning methods for Continuous Learning environments, "Learning without Forgetting" has fixed regularization strengths, which can lead to poor performance in environments where various data are received. We suggest a way to set weights variable by identifying the features of the data we want to learn. We applied weights adaptively using correlation and complexity. Scenarios with various data are used for evaluation and experiments showed accuracy increases by up to 5% in the new task and up to 11% in the previous task. In addition, it was found that the adaptive weight value obtained by the algorithm proposed in this paper, approached the optimal weight value calculated manually by repeated experiments for each experimental scenario. The correlation coefficient value is 0.739, and overall average task accuracy increased. It can be seen that the method of this paper sets an appropriate lambda value every time a new task is learned, and derives the optimal result value in various scenarios.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1059-1069
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• 2023

Dam-break flow occurs when an elevated dam suddenly collapses, resulting in the catastrophic release of rapid and uncontrolled impounded water. This study compares laminar and turbulent closure models for simulating three-dimensional dam-break flows using OpenFOAM. The Reynolds-Averaged Navier-Stokes (RANS) model, specifically the k-ε model, is employed to capture turbulent dissipation. Two scenarios are evaluated based on a laboratory experiment and a modified multi-layered block obstacle scenario. Both models effectively represent dam-break flows, with the turbulent closure model reducing oscillations. However, excessive dissipation in turbulent models can underestimate water surface profiles. Improving numerical schemes and grid resolution enhances flow recreation, particularly near structures and during turbulence. Model stability is more significantly influenced by numerical schemes and grid refinement than the use of turbulence closure. The k-ε model's reliance on time-averaging processes poses challenges in representing dam-break profiles with pronounced discontinuities and unsteadiness. While simulating turbulence models requires extensive computational efforts, the performance improvement compared to laminar models is marginal. To achieve better representation, more advanced turbulence models like Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) are recommended, necessitating small spatial and time scales. This research provides insights into the applicability of different modeling approaches for simulating dam-break flows, emphasizing the importance of accurate representation near structures and during turbulence.