• Journal of Ocean Engineering and Technology
• /
• v.16 no.3
• /
• pp.40-45
• /
• 2002

In this study, the effects on hydraulic characteristics are discussed as the permeable underlayer thickness of the rubble mound structure changes. A series of hydraulic experiments were performed and wave run-up, reflection and set-up were investigated. Result indicated that wave run-down was affected by the water out from the permeable underlayer during down-rush. As the thickness increased, relative wave run-up decreased.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2001.05a
• /
• pp.160-165
• /
• 2001

In this study, the effects on hydraulic characteristics are discussed as the permeable underlayer width of the rubble mound structure changes. A series of hydraulic experiments were performed and wave run-up, reflection and set-up were investigated. Results indicated that wave run-down was affected by the water out from the permeable underlayer during down-rush. As the width increased, relative wave run-up decreased.

• Journal of Ocean Engineering and Technology
• /
• v.22 no.3
• /
• pp.18-23
• /
• 2008

This study investigated interactions between the internal-external wave field of a permeable coastal structure consisting of rubble. The study examined the application criteria of an existing numerical model (CADMAS-SURF V.4.0) and proposed a modified method to provide reasonable results. In particular, the study focused on and emphasized the water surface profiles in front of a structure, wave run-up/run-down on a slope, and internal water level fluctuations due to the drag coefficient and porosity of a rubble mound structure. In conclusion, the result show that when the vertical fluctuations of the internal water levels in permeable coastal structures exhibited high-quality representation. Sane responses can be seen for wave run-up/run-down characteristics on its slopes.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.3
• /
• pp.723-728
• /
• 2014

Hydraulic experiments are performed in order to verify the swash effect of seashore structures installed to prevent scouring. However, a great deal of investment and time are required for producing the test apparatus and seashore structure used to perform the hydraulic experiment. The swash effect can be predicted, however, by using a numerical model and validation can be done based on comparisons of the numerical model and hydraulic experiment analysis results, thereby saving the cost and time required for producing the test apparatus and seashore structure. Taking a polyhedral rubble mound structure as the subject, this study performed a comparative analysis of wave run-up and run-down height of the numerical model interpretative results and the hydraulic experiment results, and validated the interpretative simulation wave test modeling technique. The study also predicted the swash effect by using the numerical interpretation approach method, whereby the volume ratio and friction area of the rubble mound were varied for different results.

• Journal of computational fluids engineering
• /
• v.19 no.4
• /
• pp.52-60
• /
• 2014

Recently, coastal structures have been built to protect coastal areas. However, if a tidal wave caused by an earthquake hits the coast, it would cause catastrophic damages. It is important to analyze the basics and the characteristics of a tsunami to reduce damages caused by natural disasters. In this study, a tsunami passing over different topographical changes is simulated with VOF method based on FVM(Finite Volume Method). The reduction of both scale and velocity is accomplished by similarity analysis, and an initial energy is generated by increasing the water level as needed to create a tsunami as if it is caused by a crustal movement. It is found that the present method is appropriate to simulate the tsunami with its mechanism.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.21 no.5
• /
• pp.591-598
• /
• 2015

A hydraulic characteristics in the surf zone such as wave breaking points, wave set-down, wave set-up, wave-induced currents and run-up heights are studied using the SWASH model during Typhoon NAKRI(1412) in Haeundae Beach. Incident wave conditions is obtained from one-hourly observed wave data by KHOA and irregular wave by JONSWAP spectrum is given as an open boundary condition in the model. A Wave-induced current patterns by the SWASH model is compared with the observed currents and sediment flux patterns in that areas, the calculated maximum wave run-up heights in the model is compared with the video monitoring data, the empirical formula by Stockdon et al. and Mase. A dominant longshore currents toward the east of the beach appears due to the effect of incident wave direction and the geographical features and some rip currents occurs at the central part of the beach. The maximum wave run-up height(1.15 m) by the SWASH model shows a similar pattern with the video monitoring data(1.26 m) and the magnitude shows a similar result(1.33m) by Stockdon et al.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.74.2-75
• /
• 2021

We demonstrate that a deep learning classifier that only uses to gravitational wave (GW) detectors auxiliary channel data can distinguish various types of non-Gaussian noise transients (glitches) with significant accuracy, i.e., ≳ 80%. The classifier is implemented using the multi-scale neural networks (MSNN) with PyTorch. The glitches appearing in the GW strain data have been one of the main obstacles that degrade the sensitivity of the gravitational detectors, consequently hindering the detection and parameterization of the GW signals. Numerous efforts have been devoted to tracking down their origins and to mitigating them. However, there remain many glitches of which origins are not unveiled. We apply the MSNN classifier to the auxiliary channel data corresponding to publicly available GravitySpy glitch samples of LIGO O1 run without using GW strain data. Investigation of the auxiliary channel data of the segments that coincide to the glitches in the GW strain channel is particularly useful for finding the noise sources, because they record physical and environmental conditions and the status of each part of the detector. By only using the auxiliary channel data, this classifier can provide us with the independent view on the data quality and potentially gives us hints to the origins of the glitches, when using the explainable AI technique such as Layer-wise Relevance Propagation or GradCAM.