• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.189-189
• /
• 2016

To generate information that contributes to climate change risk management, it is important to perform a precise assessment on the impact in diverse aspects. Considering this academic necessity, Japanese government launched continuous research project for the climate change impact assessment, and one of the representative project is Program for Risk Information on Climate Change (Sousei Program), Theme D; Precise Impact Assessment on Climate Change (FY2012 ~ FY2016). In this research program, quantitative impact assessments have been doing from a variety of perspectives including natural hazards, water resources, and ecosystems and biodiversity. Especially for the natural hazards aspect, a comprehensive impact assessment has been carried out with the worst-case scenario of typhoons, which cause the most serious weather-related damage in Japan, concerning the frequency and scale of the typhoons as well as accompanying disasters by heavy rainfall, strong winds, high tides, high waves, and landslides. In this presentation, a framework of comprehensive impact assessment with the worst-case scenario under the climate change condition is introduced based on a case study of Theme D in Sousei program There are approx. 25 typhoons annually and around 10 of those approach or make landfall in Japan. The number of typhoons may not change increase in the future, but it is known that a small alteration in the path of a typhoon can have an extremely large impact on the amount of rain and wind Japan receives, and as a result, cause immense damage. Specifically, it is important to assess the impact of a complex disaster including precipitation, strong winds, river overflows, and high tide inundation, simulating how different the damage of Isewan Typhoon (T5915) in 1959 would have been if the typhoon had taken a different path, or how powerful or how much damage it would cause if Isewan Typhoon occurs again in the future when the sea surface water temperature has risen due to climate changes (Pseudo global warming experiment). The research group also predict and assess how the frequency of "100-years return period" disasters and worst-case damage will change in the coming century. As a final goal in this research activity, the natural disaster impact assessment will extend not only Japan but also major rivers in Southeast Asia, with a special focus on floods and inundations.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.20 no.6
• /
• pp.774-780
• /
• 2014

This research aims to investigate the superstructure characteristics of the CFRP-yachts whose hulls are made of the light-weight material CFRP. CFRP-yachts, which belong to light-weight yachts, have a tendency of having very small superstructures compared to other vessels of the same length, and such a tendency is closely related to stability. In this research, a comparison of shape characteristics was made between common composite-plastic yachts and CFRP-yachts to find out the shape characteristics of CFRP-yacht. In the meantime, a case study was conducted concerning shape changes in superstructure to understand the effect of such changes on stability. For this purpose the shapes of a total of 10 GFRP-yachts and CFRP-yachts were comparatively analyzed, and the result showed the tendency of their hulls and superstructures. Whereas the case study on stability assessment involved various superstructure shapes of CFRP yachts, for assessment by superstructure size. Stability assessment was according to ISO 12217 (Small craft Stability and buoyancy assessment and categorization). A program was also developed based on stability assessment process due to rolling in beam waves and wind, and it was applied to the case study. The result of the case study showed that the windage area distribution tendency of the yachts whose hulls were made of the light-weight material CFRP was similar to that of the GFRP-yachts, but that the superstructure shapes of the CFRP-yachts were about 50% smaller than those of the GFRP-yachts. In addition, the stability assessment involving various superstructure areas of the CFRP-yachts showed that problems with stability occurred when their superstructure sizes were similar to, or larger by about 10% than, those of the GFRP-yachts.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.6
• /
• pp.731-736
• /
• 2021

Oil fences effectively prevent the spread of oil spilled in the sea, thereby reducing the damage to the marine environment. However, the fence is damaged by oil and structures at the accident site and is discarded. When incinerated disposal method for discarded fences, fine dust, and harmful materials are generated. Moreover, as a part of the damaged fence is dumped into the sea, it may cause secondary environmental pollution, such as microplastics. Therefore, in this study, durability was measured using the most common solid foam type oil fences. As a result, the reduction rate of after five days of contact was 13 % in seawater and 3 % in oil, affected by temperature changes. Thus, the durability of the fence should be improved because it is exposed to seawater and oil and affected by wind, light, and waves depending on the weather conditions. Therefore, we suggest a method to improve the oil fence inspection to strengthen the durability of the fence's fabric part.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.7
• /
• pp.953-959
• /
• 2018

This paper deals with controlling surge oscillations of a mooring vessel system under large external disturbances such as wind, waves and currents. A control synthesis based on Sliding Mode Control (SMC) with a Super-Twisting Algorithm (STA) has been applied to suppress nonlinear surge oscillations of a two-point mooring system. Despite the advantages of robustness against parameter uncertainties and disturbances for SMC, chattering is the main drawback for implementing sliding mode controllers. First-order SMC shows convergence within the desired level of accuracy, in which chattering is the main obstacle related to the destructive phenomenon. Alternatively, STA completely eliminates chattering phenomenon with high accuracy even for large disturbances. SMC based on STA is an effective tool for the motion control of a nonlinear mooring system because it avoids the chattering problems of a first-order sliding mode controller. In addition, the error trajectories of controlled mooring systems implemented by means of STA form in the bounded region. Finally, the control gain effect of STA can be observed in sliding surface and position trajectory errors.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.6
• /
• pp.561-568
• /
• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.2
• /
• pp.28-36
• /
• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.4
• /
• pp.601-609
• /
• 2022

Jack-up drilling rigs are mobile offshore platforms widely used in the offshore oil and gas exploration industry. These are independent, three-legged, self-elevating units with a cantilevered drilling facility for drilling and production. A typical jack-up rig includes a triangular hull, a tower derrick, a cantilever, a jackcase, living quarters and legs which comprise three-chord, open-truss, X-braced structure with a spudcan. Generally, jack-up rigs can only operate in water depths ranging from 130m to 170m. Recently, there has been an increasing demand for jack-up rigs for operating at deeper water levels and harsher environmental conditions such as waves, currents and wind loads. All static and dynamic loads are supported through legs in the jack-up mode. The most important issue by society is to secure the safety of the leg structure against collision that causes large instantaneous impact energy. In this study, nonlinear FE -analysis and verification of the requirement against collision for 35MJ recommended by DNV was performed using LS-Dyna software. The colliding ship used a 7,500ton of shore supply vessel, and five scenarios of collisions were selected. From the results, all conditions do not satisfy the class requirement of 35MJ. The loading conditions associated with chord collision are reasonable collision energy of 15M and brace collisions are 6MJ. Therefore, it can be confirmed that the identical collision criteria by DNV need to be modified based on collision scenarios and colliding members.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.2
• /
• pp.363-368
• /
• 2021

Ship engine rooms have improved automation systems owing to the advancement of technology. However, there are many variables at sea, such as wind, waves, vibration, and equipment aging, which cause loosening, cutting, and leakage, which are not measured by automated systems. There are cases in which only one engineer is available for patrolling. This entails many risk factors in the engine room, where rotating equipment is operating at high temperature and high pressure. When the engineer patrols, he uses his five senses, with particular high dependence on vision. We hereby present a preliminary study to implement an engine-room patrol robot that detects and informs the machine room while a robot patrols the engine room. Images of ship engine-room equipment were classified using a convolutional neural network (CNN). After constructing the image dataset of the ship engine room, the network was trained with a pre-trained CNN model. Classification performance of the trained model showed high reproducibility. Images were visualized with a class activation map. Although it cannot be generalized because the amount of data was limited, it is thought that if the data of each ship were learned through transfer learning, a model suitable for the characteristics of each ship could be constructed with little time and cost expenditure.

• Geophysics and Geophysical Exploration
• /
• v.26 no.1
• /
• pp.8-17
• /
• 2023

Various sources, such as wind, waves, ships, and gas leaks from the seafloor, forms bubbles in the ocean. Underwater bubbles cause signal scattering, considerably affecting acoustic measurements. This characteristic of bubbles is used to block underwater noise by attenuating the intensity of the propagated signal. Recently, researchers have been studying the large-scale release of methane gas as bubble plumes from the seabed. Understanding the physical properties and distribution of bubble plumes is crucial for studying the relation between leaked methane gas and climate change. Therefore, a water tank experiment was conducted to estimate the distribution of bubble plumes using seismic imaging techniques and acoustic signals obtained from artificially generated bubbles using a bubble generator. Reverse time migration was applied to image the bubble plumes while the acquired acoustic envelope signal was used to effectively estimate bubble distribution. Imaging results were compared with optical camera images to verify the estimated bubble distribution. The water tank experiment confirmed that the proposed system could successfully image the distribution of bubble plumes using reverse time migration and the envelope signal. The experiment showed that the scattering signal of artificial bubble plumes can be used for seismic imaging.

• Journal of Marine Life Science
• /
• v.8 no.1
• /
• pp.68-77
• /
• 2023

In this study, we investigated the quantitative distribution of microplastics in the surface seawater at 8 points near the Taean Peninsula using fluorescence staining. The study revealed a detection range of microplastics from 0 to 360.5 particles/l, with an average of 149.7 ± 46.0 particles/l. When classifying the microplastics by size, it was found that particles smaller than 50 ㎛ were dominant, although there were differences at Site 3. Moreover, it was not possible to identify clear correlations when comparing the number of microplastics based on collection area and particle size. Various physical and chemical factors, including plastic material, dynamic ocean conditions (such as currents, wind, waves, tides), geological characteristics (topography, slope), sediment materials including coastal organisms, human activities (fishing, development, tourism), and weather conditions (floods, rainfall), affect the behavior of microplastics. Therefore, future efforts should focus on standardizing quantitative analysis methods and conducting fundamental research on microplastic monitoring, including the analysis of environmental factors.