• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.99-108
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• 1998

In order to represent the surface characteristics in local meteorological model, soil type, vegetation index, surface roughness length, surface albedo and leaf area index should be prescribed on the surface process parameterization. In this study, the $1^{\circ}/1^{\circ}leaf$ area index, surface roughness length, and snow free surface albedo and fine mesh NDVI with seasonal variation derived from the satellite observation were applied to the land surface process parameterization. From comparison between with and without satellite data in the interactions between biosphere and atmosphere, land and atmosphere, the sensitivity of the simulated heat, energy and water vapor fluxes, ground temperature, wind, canopy water content, specific humidity, and precipitation fields were investigated.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.213-224
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• 2008

Flexible pavement responses to vehicular loading, such as critical stresses and strains, in each pavement layer, could be predicted by the multilayered elastic analysis. However, multilayered elastic theory suffers from major drawbacks including spatial dimension of a numerical model, material properties considered in the analysis, boundary conditions, and ill-presentation of tire-pavement contact shape and stresses. To overcome these shortcomings, three-dimensional finite element (3D FE) models are developed and numerical analyses are conducted to calculate pavement responses to moving load in this study. This paper introduces a methodology for an effective 3D FE to simulate flexible pavement structure. It also discusses the mesh development and boundary condition analysis. Sensitivity analyses of flexible pavement response to loading are conducted. The infinite boundary conditions and time-dependent history of calculated pavement responses are considered in the analysis. This study found that the outcome of 3D FE implicit dynamic analysis of flexible pavement that utilizes appropriate boundary conditions, continuous moving load, viscoelastic hot-mix asphalt model is comparable to field measurements.

• Steel and Composite Structures
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• v.43 no.4
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• pp.447-456
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• 2022

Recent experimental studies showed that deep steel I-shaped profiles classified as high ductility class sections in seismic design international codes exhibit low deformation capacity when subjected to cyclic loading. This paper presents an innovative retrofit solution to increase the rotation capacity of beams using bonded carbon fiber reinforced polymers (CFRP) patches validated with advanced finite element analysis. This investigation focuses on the flexural cyclic behaviour of I-shaped hot rolled steel deep section used as beams in moment-resisting frames (MRF) retrofitted with CFRP patches on the web. The main goal of this CFRP reinforcement is to increase the rotation capacity of the member without increasing the overstrength in order to avoid compromising the strong column-weak beam condition in MRF. A finite element model that simulates the cyclic plasticity behavior of the steel and the damage in the adhesive layer is developed. The damage is modelled using the cohesive zone modelling (CZM) technique that is able to capture the crack initiation and propagation. Details on the modelling techniques including the mesh sensitivity near the fracture zone are presented. The effectiveness of the retrofit solution depends strongly on the selection of the appropriate adhesive. Different adhesive types are investigated where the CZM parameters are calibrated from high fidelity fracture mechanics tests that are thoroughly validated in the literature. This includes a rigid adhesive commonly found in the construction industry and two tough adhesives used in the automotive industry. The results revealed that the CFRP patch can increase the rotation capacity of a steel member considerably when using tough adhesives.

• International Journal of Highway Engineering
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• v.5 no.4 s.18
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• pp.1-11
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• 2003

Recently, the new pavement design method considering Korean environment and the specification for improving performance of pavement are being developed in Korea. The Jointed Concrete Pavement Program Applying Load Discretization Algorithm (called HEART-JCP) is one of the results of Korea Pavement Research Project in Korea. HEART-JCP program is developed to analyze various loading condition using the load discretization algorithm without mesh refinement. In addition, it can be modified easily into multi-purpose concrete pavement nidyses program because of the modularized structure characteristic of HEART-JCP. The program consists of basic program part and load discretization part. In basic program part, the displacement and stress are computed in the concrete slab, sub-layer, and dowel bar, which are modeled with plate/shell element, spring element and beam element. In load discretization program part, load discretization algorithm that was used for the continuum solid element is modified to analyze the model with plate and shell element. The program can analyze the distributed load, concentrated load, thermal load and body load using load discretization algorithm. From the result of verification and sensitivity study, it was known that the loading position, the magnitude of load, and the thickness of slab were the major factors of concrete pavement behavior as expected. Since the result of the model developed is similar to the results of Westergaard solution and ILLISLAB, the program can be used to estimate the behavior of jointed concrete pavement reasonably.

• Nuclear Engineering and Technology
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• v.26 no.1
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• pp.126-139
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• 1994

Best-estimate thermal-hydraulic codes, CATHARE2 V1.2 and RELAP5/MOD3, hate been assessed against the BETHSY 6.2 tc six-inch cold leg break loss-of-coolant accident (LOCA) test. Main objective is to analyze the overall capabilities of the two codes on physical phenomena of concern during the small break LOCA i.e. two-phase critical flow, depressurization, core water level de-pression, loop seal clearing, liquid holdup, etc. The calculation results show that the too codes predict well both in the occurrences and trends of major two-phase flow phenomena observed. Especially, the CATHARE2 calculations show better agreements with the experimental data. However, the two codes, in common, show some deviations in the predictions of loop seal clearing, collapsed core water level after the loop seal clearing, and accumulator injection behaviors. The discrepancies found from the comprision with the experimental data are larger in the RELAP5 results than in the CATHARE2. To analyze the deviations of the two code predictions in detail, several sensitivity calculations have been performed. In addition to the change of two-phase discharge coefficients for the break junction, fine nodalization and some corrections of the interphase drag term are made. For CATHARE2, the change of interphase drag force improves the mass distribution in the primary side. And the prediction of SG pressure is improved by the modification of boundary conditions. For RELAP5, any single input change doesn't improve the whole result and it is found that the interphase drag model has still large uncertainties.

• Applied Biological Chemistry
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• v.26 no.2
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• pp.104-109
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• 1983

Gas chromatographic method for the analysis of phorate(0,0-diethyl S-ethyl-thiomethyl phosphorithioate) and its metabolites in soil and vegetables was studied by using a mixed phase column(10% DC-200+8% Reoplex-400+2% QF-1 on Gas Chrom Q, $1.8{\times}2mm$ i.d, borosilicate glass column). This column can separate completely phorate and its four metabolites except phoratoxon sulfoxide. Retention time of standard mixture ranged 1.8 to 16.1 minutes at column temperature programming from 130 to $200^{\circ}C$ at $5^{\circ}C/min$ and detector sensitivity was also very high(0.05 to 1.05ng). Recoveries from soil and vegetables untreated but fortified with phorate and its three major metabolites at 0.05 and 0.5ppm levels were above 90% for phorate, phorate sulfoxide and phorate sulfone while recovery of phoratoxon metabolite was about 84%.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.