• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.4
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• pp.21-31
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• 2001

When an oil-spilling accident occurs at sea, it is of the primary importance to predict the amount of oil leakage for the swift response and decision-making. The simplest method of oil-leakage estimation is based on the hydrostatic pressure balance between oil inside the tank and seawater outside of leakage hole, that is the so-called Torricelli equilibrium relation. However, there exists discrepancy between the reality and the Torricelli relation, since the latter is obtained from the quasi-steady treatment of Bernoulli equation ignoring viscous friction. A preliminary experiment has been performed to find out the oil-leaking speed and shape. Soy-bean oil inside the inner tank was ejected into water of the outer tank through four different leakage holes to record the amount of oil leakage. Furthermore, a CFD (Computational Fluid Dynamics) method was utilized to simulate the experimental situation. The Wavier-Stokes equations were solved for two-density flow of oil and water. VOF method was employed to capture the shape of their interface. It is found that the oil-leaking speed varies due to the frictional resistance of the leakage hole passage dependent on its aspect ratio. The Torricelli factor relating the speed predicted by using the hydrostatic balance and the real leakage speed is assessed. For the present experimental setup, Torricelli factors were in the range of 35%~55% depending on the aspect ratio of leakage holes. On the other hand, CFD results predicted that Torricelli factor could be 52% regardless of the aspect ratio of the leakage holes, when the frictional resistance of leakage hole passage was neglected.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.88-96
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• 2021

When oil tankers, large passenger ships and cargo ships sink under the sea owing to various maritime accidents, the residual cargo oil or fuel oil in the such vessels could pose direct risk to factor for the marine environment and it require safe and rapid removal. Although domestic and foreign salvage companies are adopting various recovery methods and technologies with customizations according to each site during recovery operations studies on reasonable assessment modules for the operation process are relatively insufficient. In this study, the data from trapped-oil recovery operations performed at different site conditions were collected and analyzed in order to designed an operation assessment module, define the operational process steps in terms of preparation, implementation and completion, and derive key factors for each detailed process. Subsequently, the module was designed in such a way as to construct performance indicators to assess these key factors. In order to exclude subjective opinions from the assessment as much as possible, the assessment each item was constructed with indicators based on data that could be evaluated quantitatively and its usefulness was verified by applying the module to the trapped-oil recovery operation cases. We expect this the method and the technology assessment module for the trapped-oil recovery operation on sunken vessels will help to verify the adequacy of the trapped-oil recovery such operation before or after. Furthermore, it is expected that the continuous accumulation of assessment data and feedback from past or future operation cases will contribute toward enhancing the overall safety, efficiency and field applicability of trapped-oil recovery operation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.6
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• pp.655-662
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• 2012

Gas leakage in an oil refinery causes damage to the environment and unsafe conditions. Therefore, it is necessary to develop a technique that is able to detect the location of the leakage and to filter abnormal gas-leakage signals from normal background noise. In this study, the adaptation filter of the finite impulse response (FIR) least mean squares (LMS) algorithm and a cross-correlation function were used to develop a leakage-predicting program based on LABVIEW. Nitrogen gas at a high pressure of 120 kg/$cm^2$ and the assembled equipment were used to perform experiments in a reverberant chamber. Analysis of the data from the experiments performed with various hole sizes, pressures, distances, and frequencies indicated that the background noise occurred primarily at less than 1 kHz and that the leakage signal appeared in a high-frequency region of around 16 kHz. Measurement of the noise sources in an actual oil refinery revealed that the noise frequencies of pumps and compressors, which are two typical background noise sources in a petrochemical plant, were 2 kHz and 4.5 kHz, respectively. The fact that these two signals were separated clearly made it possible to distinguish leakage signals from background noises and, in addition, to detect the location of the leakage.