• Structural Engineering and Mechanics
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• v.27 no.1
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• pp.33-48
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• 2007

An Articulated tower is one of the compliant offshore structures connected to the sea-bed through a universal joint which is the most vulnerable location of the tower that sustains the randomly fluctuating shear stresses. The time history response of the bottom hinge shear is obtained and presented in the spectral form. The fatigue and fracture reliability assessment of the tower joint against randomly varying shear stresses have been carried out. Non-linear limit state functions are derived in terms of important random variables using S-N curve and fracture mechanics approaches. Advanced First Order Reliability Method is used for reliability assessment. Sensitivity analysis shows the influence of various variables on the hinge safety. Fatigue life estimation has been made using probabilistic approach.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.3
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• pp.266-281
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• 2017

Hydroelastic interactions of a deformable floating body with random waves are investigated in time domain. Both hydroelastic motion and structural dynamics are solved by expansion of elastic modes and Fourier transform for the random waves. A direct and efficient structural analysis in time domain is developed. In particular, an efficient way of obtaining distributive loads for the hydrodynamic integral terms including convolution integral by using Fubini theory is explained. After confirming correctness of respective loading components, calculations of full distributions of loads in random waves are expedited by reformulating all the body loading terms into distributed forms. The method is validated by extensive convergence tests and comparisons against the counterparts of the frequency-domain analysis. Characteristics of motion/deformation responses and stress resultants are investigated through a parametric study with varying bending rigidity and types of random waves. Relative contributions of componential loads are identified. The consequence of elastic-mode resonance is underscored.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.19-26
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• 2003

The dispersion of recycled particulates in the complex coastal terrain containing Kangnung city, Korea was investigated using a three-dimensional non-hydrostatic numerical model and lagrangian particle model (or random walk model). The results show that particulates at the surface of the city that float to the top of thermal internal boundary layer (TIBL) are then transported along the eastern slope of the mountains with the passage of sea breeze and nearly reach the top of the mountains. Those particulates then disperse eastward at this upper level over the coastal sea and finally spread out over the open sea. Total suspended particulate (TSP) concentration near the surface of Kangnung city is very low. At night, synoptic scale westerly winds intensify due to the combined effect of the synoptic scale wind and land breeze descending the eastern slope of the mountains toward the coast and further seaward. This increase in speed causes development of internal gravity waves and a hydraulic jump up to a height of about 1km above the surface over the city. Particulate matter near the top of the mountains also descends the eastern slope of the mountains during the day, reaching the central city area and merges near the surface inside the nocturnal surface inversion layer (NSIL) with a maximum ground level concentration of TSP occurring at 0300 LST. Some particulates were dispersed following the propagation area of internal gravity waves and others in the NSIL are transported eastward to the coastal sea surface, aided by the land breeze. The following morning, particulates dispersed over the coastal sea from the previous night, tend to return to the coastal city of Kangnung with the sea breeze, developing a recycling process and combine with emitted surface particulates during the morning. These processes result in much higher TSP concentration. In the late morning, those particulates float to the top of the TIBL by the intrusion of the sea breeze and the ground level TSP concentration in the city subsequently decreases.

• Journal of Ocean Engineering and Technology
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• v.12 no.1
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• pp.107-112
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• 1998

The purpose of this study is to analyze the amount of available wave power and its characteristics related to the development of apractical system for ocean wave energy conversion in Korean coastal waters. The analysis method of wave power was established through comparison between theory and numerical simulation of deep sea wave by Inverse Fourier Transform with random phase method. Based on the results of comparison, wave power was estimated by use of data set from observed offshore and coastal waves and hindasted deep sea waves around the Korean peninsula. Annual mean wave power is estimated as about 1.8 ~ 7.0 kW for every metre of wave frontage at East sea, 1.5~5.3 kW at South sea and 1.0 ~ 4.1 kW at West sea, respectively. Mean wave power along deep sea front of coastal waters of Korea amounts to about 4.7 GW. Regional distribution and seasonal variation of wave power were discussed to develop practical utilization system of wave power of not so high grade of available wave power.

• Journal of electromagnetic engineering and science
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• v.10 no.2
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• pp.61-66
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• 2010

This paper is concerned with an analysis of the back scattering of electromagnetic waves from a target moving along random rough surfaces such as the desert, and sea. First, the discrete ray tracing method(DRTM) is introduced, and then, this method is applied to the back scattering problem in order to investigate the effect of the back scattering from random rough surfaces on the electric field intensities. Finally, numerical examples of various height deviations of the Gaussian type of rough surfaces are shown. It is numerically demonstrated that the back scattering is dominated by the diffractions related to the reflections from the random rough surfaces.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.6
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• pp.813-820
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• 2010

The spread mooring system for FPSO is developed to explore deep sea area, in which swell is dominant. It is known that the tension response of mooring lines in this sea area shows bimodal spectrum. Assuming normal distribution of tension profile and Rayleigh distribution of tension amplitude, the power spectral density function (PSD) of the mooring tension under the bimodal stationary random process is applied for the calculation of spectrum fatigue. Three popular methods, which are simple summation method, combined spectrum method and Jioa-Moan method, are used to combine fatigue damages from bimodal spectrum characteristics. Each damage value is compared with damage using Rainflow Cycle Counting (RCC) method which is believed to be close to exact solution. Vanmarcke' parameter and RMS(Root Mean Square) ratio are employed to assess relative damage variations between from RCC method and from three combination methods. Finally the most reliable fatigue damage combining method for spread mooring system is suggested.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.11-17
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• 2019

In recent years, damage and loss of life and property have been occurred frequently due to swelling waves in the East Sea. Swelling waves are not easy to predict because they are caused by various factors. In this research, we build a model for predicting the swelling waves occurrence in the East Coast of Korea using machine learning technique. We collect historical data of unloading interruption in the Pohang Port, and collect air pressure, wind speed, direction, water temperature data of the offshore Pohang Port. We select important variables for prediction, and test various machine learning prediction algorithms. As a result, tide level, water temperature, and air pressure were selected, and Random Forest model produced best performance. We confirm that Random Forest model shows best performance and it produces 88.86% of accuracy

• Journal of Ocean Engineering and Technology
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• v.24 no.3
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• pp.21-30
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• 2010

This study presents a numerical simulation of sea water-exchange as a preliminary accessing tool of water quality in the protected shore behind a overtopped breakwater. The overtopped breakwater is taken into account for a safe swimming and beach protection. The overtopping rate is calculated by empirical models and the consequent currents, known as wave-induced currents, are calculated under the conditions of H.W.O.S.T and L.W.O.S.T. The rate of sea water exchange is used to evaluate the characteristics of sea water exchange and calculated through the simulation processes such as advective discharging through the outlets and random-walking diffusion of particles released within a basin. The numerical results show that the overtopped waves sufficiently improve the water exchange without healthless stagnation of contaminated mass and the consequent currents are not too strong for swimming.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.348-348
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• 2013

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1261-1272
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• 2018

It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.