R/V Isabu-Based First Ultraclean Seawater Sampling for Ocean Trace Elements in Korea

Ocean Science Journal - Trace elements (Mn, Fe, Co, Ni, Cu, Zn, etc.) are essential micronutrients for marine organisms and are thus related to major issues in the ocean, such as climate change,...     

Under-ice measurements of suspended particulate matters using ADCP and LISST-Holo

Ocean Science Journal - Using a mooring package comprising an acoustic Doppler current profiler (ADCP) and holographic imaging system, a 1-day ice camp study was performed under the Arctic sea ice...     

Evaluation of typhoon‐induced rainfall using nonparametric Monte Carlo simulation and locally weighted polynomial regression

Typhoons in Korea are the major causes of natural disasters in the Korean peninsula. In this study, rainfall generated by typhoons was quantitatively analysed using various statistical methods. First, the frequency analysis of rainfall induced by typhoons was carried out to calculate the design rainfall. Second, the frequency analysis of simulated rainfall derived by nonparametric Monte Carlo simulation (NMCS) was performed to evaluate the uncertainty of rainfall caused by typhoons. Third, the regression relationship between the physical characteristic factors of typhoons and rainfall was established by locally weighted polynomial regression (LWPR), and the characteristic factors of typhoons were simulated. The simulated characteristic factors were then used to estimate rainfall and to calculate the design rainfall by typhoons. Comparative analyses of design rainfalls as estimated using various statistical methods were performed. The LWPR showed good performance in terms of reproducing typhoon characteristics. Therefore, the combined NMCS and LWPR method suggested in this study can be used as a supplementary technique for assessing extreme rainfall with climate change and reflected variability. Copyright © 2010 John Wiley & Sons, Ltd.     

Determination of shape parameters of sands: a deep learning approach

Acta Geotechnica - The shape parameters of sand particles can be determined by either a Krumbein-Sloss chart or mathematical computation based on the particle image. However, these approaches are...     

Practically Applicable Central Limit Theorem for Spatial Statistics

Let {Z(s):s∈D⊆ℝ ^d } be a zero mean stationary random field observed at a finite number of locations. Lahiri (Sankhya Ser. A 65:356–388, 2003) proved spatial central limit theorems (CLT) for ∑ _i=1 ⁿ Z(s _i ) assuming a ‘nearly infill domain sampling’. Applications of his results depended on the underlying spatial sampling region and the design in a complicated fashion. The main objective of this paper is to provide CLTs that could be applied easily in practice. We present two main results assuming a ‘nearly infill domain sampling’ defined mainly in terms of dependence. Theorem 1 establishes a CLT for ∑ _i=1 ⁿ Z(s _i ) and Theorem 2 is obtained mainly for applications to density estimates. We report on a simulation study for illustrating a way of applying our results in practice.     

Distribution of Cs and Pu in the surface waters of the East Sea (Sea of Japan)

Surface and subsurface water samples for ¹³⁷Cs and ^239,240Pu analysis were collected in the East Sea (Sea of Japan) during August 1993. The ¹³⁷Cs levels of the surface waters are quite homogeneous in the East Sea (average = 3.1±0.2 mBq kg⁻¹). The ^239,240Pu levels vary from 6 to 10 μBq kg⁻¹ in the surface. ^239,240Pu to ¹³⁷Cs ratios in the surface water are within 0.002 to 0.003. The East Sea may be regarded as a part of the North Pacific Ocean in terms of ¹³⁷Cs dispersal in the surface, where the ¹³⁷Cs contents of the surface seawater seem to be controlled primarily by the atmospheric input. However, since our sampling was made just two months prior to the widely publicized Russian dumping incident on the 17th October 1993, our measurements may provide background data to assess the immediate impact of the Russian dumping on the levels of ¹³⁷Cs and ^239,240Pu in the East Sea.     

Characterisation of conduction phenomena in soils at the particle-scale: Finite element analyses in conjunction with synthetic 3D imaging

This paper describes an innovative method to characterise conduction parameters in geomaterials at the particle-scale. The technique is exemplified using 3D synthetic grain packing generated with discrete element approaches. This creates a geo-mechanically viable user-defined 3D granular image through which the particle skeleton and the corresponding pore network are constructed. Images are then imported into the finite element analyses to solve the governing equations of hydraulic and thermal conduction. Navier–Stokes equation is uniquely upscaled to Darcy’s law to assess hydraulic conductivity in soils, while a similar approach implements the Fourier equation to evaluate thermal conduction through grain chains and pore network. High performance computing is used to meet demanding numerical calculations of 3D meshed geometries. Packing density (i.e., porosity) and inter-particle contact areas are explored as variables to highlight the effects of pore volume and inter-particle contact condition in hydraulic and thermal conduction. This emerging technique allows not only characterising the macro-scale behaviour of conduction phenomena in soils but also quantifying and visualising the preferential and local conduction behaviour at the particle-scale. Laboratory measurements of hydraulic and thermal conductivities support numerically obtained results and validate the viability of the new methods used herein. This study introduces an alternative way to determine physical parameters of soils using emerging technology of rigorous numerical simulations in conjunction with 3D images, and to enable fundamental observation of particle-scale mechanisms of macro-scale manifestation.     

Effects of climate change on the thermal structure of lakes in the Asian Monsoon Area

This research investigates the effect of climate change on the thermal structure of lakes in response to watershed hydrology. We applied a hydrodynamic water quality model coupled to a hydrological model with a future climate scenario projected by a GCM A2 emission scenario to the Yongdam Reservoir, South Korea. In the climate change scenario, the temperature will increase by 2.1°C and 4.2°C and the precipitation will increase by 178.4?mm and 464.4?mm by the 2050 and 2090, respectively, based on 2010. The pattern changes of precipitation and temperature increase due to climate change modify the hydrology of the watershed. The hydrological model results indicate that they increase both surface runoff itself and temperature. The reservoir model simulation with the hydrological model results showed that increasing air temperature is related to higher surface water temperature. Surface water temperature is expected to increase by about 1.2°C and 2.2°C from the 2050 and 2090, respectively, based on the 2010 results. The simulation results of the effects of climate warming on the thermal structure of the Asian Monsoon Area Lake showed consistent results with those of previous studies in terms of greater temperature increases in the epilimnion than in the hypolimnion, increased thermal stratification, and decreasing thermocline depths during the summer and fall. From this study, it was concluded that the hydrodynamic water quality model coupled to the hydrological model could successfully simulate the variability of the epilimnetic temperature, changed depth and magnitude of the thermocline and the changed duration of summer stratification.