• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2292-2314
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• 2006

Efficient numerical method is developed for the prediction of aerodynamic noise generation and propagation in low Mach number flows such as aeolian tone noise. The proposed numerical method is based on acoustic/viscous splitting techniques of which acoustic solvers use simplified linearised Euler equations, full linearised Euler equations and nonlinear perturbation equations as acoustic governing equations. All of acoustic equations are forced with immersed surface dipole model which is developed for the efficient computation of aerodynamic noise generation and propagation in low Mach number flows in which dipole source, originating from unsteady pressure fluctuation on a solid surface, is known to be more efficient than quadrupole sources. Multi-scale overset grid technique is also utilized to resolve the complex geometries. Initially, aeolian tone from single cylinder is considered to examine the effects that the immersed surface dipole models combined with the different acoustic governing equations have on the overall accuracy of the method. Then, the current numerical method is applied to the simulation of the aeolian tones from twin cylinders aligned perpendicularly to the mean flow and separated 3 diameters between their centers. In this configuration, symmetric vortices are shed from twin cylinders, which leads to the anti-phase of the lift dipoles and the in-phase of the drag dipoles. Due to these phase differences, the directivity of the fluctuating pressure from the lift dipoles shows the comparable magnitude with that from the drag dipoles at 10 diameters apart from the origin. However, the directivity at 100 diameters shows that the lift-dipole originated noise has larger magnitude than, but still comparable to, that of the drag-dipole one. Comparison of the numerical results with and without mean flow effects on the acoustic wave emphasizes the effects of the sheared background flows around the cylinders on the propagating acoustic waves, which is not generally considered by the classic acoustic analogy methods. Through the comparison of the results using the immersed surface dipole models with those using point sources, it is demonstrated that the current methods can allow for the complex interactions between the acoustic wave and the solid wall and the effects of the mean flow on the acoustic waves.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.157-167
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• 2011

A numerical model was developed to predict the stage-discharge curve and lateral distribution of unit discharge in open channels with nonuniform cross section or compound open-channels. The governing equation is the one-dimensional momentum equation based on assumptions of the steady and uniform flow conditions in the longitudinal direction and the uniform water surface elevation in a cross section. Vegetative drag force term was included in governing equation in order to reflect the effect of floodplain vegetation on the flow characteristics. Finite element method was applied to obtain the numerical solution of the governing equation. Stage-discharge curve and lateral distribution of unit discharge for a given water surface are calculated based on input data, such as the cross sectional geometry, Manning's roughness coefficient, vegetative information and longitudinal slope of channel bed. The developed model was verified by comparing the calculated results with the observed data and the results of Darby and Thorne's(1996) model and the nonlinear k-$\epsilon$ model. The verified model was applied to estimate the upstream boundary conditions in two-dimensional flow model. The numerical results using laterally distributed unit discharge were compared with those obtained using uniformly distributed unit discharge in two-dimensional flow model.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.1-15
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• 2007

The objective of this paper is the establishment of finite element analysis frame work for pavement research. Finite element analysis results simulating various loading experiments are verified with sensor measurements obtained from the KHC Test Road. The accuracy of the finite element analysis can be supported by these efforts so that it helps spread out the finite element analysis to pavement research and design processes. The finite element model used in this research is the full 3D nonlinear model including concrete slab, lean concrete base, subbase, shoulder, dowel, and tie-bar. In order to accomplish the accurate verification, the loading condition and the pavement temperature distribution are exactly simulated with field measured data. The curling behavior and the strain distribution are compared with measured responses from the loading tests with a truck and the FWD. Strain and curling predictions from the concrete slab are matched well with measured responses but the strain prediction from the lean concrete base is not matched with measured response. In addition, the magnitude of permanent curling is evaluated with the finite element analysis.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.97-106
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• 2011

Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.263-272
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• 2005

For the Communication, Ocean and Meteorological Satellite (COMS) which will be launched in 2008, an algorithm for finding the precise location of the sun-glint point on the ocean surface is studied. The precise locations of the sun-glint are estimated by considering azimuth and elevation angles of Sun-satellite-Earth geometric position and the law of reflection. The obtained nonlinear equations are solved by using the Newton-Raphson method. As a result, when COMS is located at $116.2^{\circ}E$ or $128.2^{\circ}E$ longitude, the sun-glint covers region of ${\pm}10^{\circ}(N-S)$ latitude and $80-150^{\circ}(E-W)$ longitude. The diurnal path of the sun-glint in the southern hemisphere is curved towards the North Pole, and the path in the northern hemisphere is forwards the south pole. The algorithm presented in this paper can be applied to predict the precise location of sun-glint region in any other geostationary satellites.

• Journal of Navigation and Port Research
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• v.27 no.5
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• pp.527-537
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• 2003

The characteristics of ship induced waves caused by navigation become widely different from both ship's speed and water depth condition. The ship induced waves specially generated in coastwise routes frequently give rise to call unforeseen danger for swimmers and small boats as well as shoreline erosion or sea wall destruction in coastal zones. The main concern of ship induced wave study until now is either how to reduce ship resistance or how to manoeuvre the ship safely under a constant water depth in the view point of shipbuilding engineers. Moreover, due to the trends for appearance of the high speed ships at the shallow coastal water, we are confronted with the danger of damages from those ship induced waves. Therefore, it is necessary to examine the development of ship induced waves and the influence of their deformation effects according to its propagation ray. In present study, in order to predict the development of the ship induced waves and their propagation under the conditions of complicate and variable shallow water depth with varying ship's speed, we constructed a computer model using Boussinesq equation with a fixed coordinate system and verified the model results by comparison with experimental results. Additionally, the model was applied under the variable water depth based on actual passage and we then confirmed the importance of the variable water depth consideration.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.261-271
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• 2003

A condition evaluation procedure for the pavement foundations using multi-load level Falling Weight Deflectometer(FWD) deflections is presented in this paper. A dynamic finite element program incorporating a stress-dependent material model, was used to generate the synthetic deflection database. Based on this synthetic database, the relationships between surface deflections and critical responses, such as stresses and strains in base and subgrade layers, have been established. FWD deflection data, Dynamic Cone Penetrometer(UP) data, and repeated load resilient modulus testing results used in developing this procedure were collected from the Long Term Pavement Performance (LTPP) and North Carolina Department of Transportation (NCDOT) database. Research effort focused on investigation of the effect of the FWD load level on the condition evaluation procedures. The results indicate that the proposed procedure can estimate the pavement foundation conditions. It is also found that structurally adjusted Base Damage Index (BDI) and Base Curvature Index (BCI) are good indicators for the prediction of stiffness characteristics of aggregate base and subgrade respectively. A FWD test with a load of 66.7 kN or less does not improve the accuracy of this procedure. Results from the study for the nonlinear behavior of a pavement foundations indicate that the deflection ratio obtained from multi-load level deflections can predict the type and quality of the pavement foundation materials.

• Journal of the Korea Concrete Institute
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• v.20 no.6
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• pp.697-704
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• 2008

This paper presents an analytical prediction of Nonlinear characteristics of prestressed concrete bridges by strengthened of externally tendon considering construction sequence, using unbonded tendon element and beam-column element based on flexibility method. Unbonded tendon model can represent unbounded tendon behavior in concrete of PSC structures and it can deal with the prestressing transfer of posttensioned structures and calculate prestressed concrete structures more efficiently. This tendon model made up the several nodes and segment, therefore a real tendon of same geometry in the prestressed concrete structure can be simulated the one element. The beam-column element was developed with reinforced concrete material nonlinearities which are based on the smeared crack concept. The fiber hysteresis rule of beam-column element is derived from the uniaxial constitutive relations of concrete and reinforcing steel fibers. The formulation of beam-column element is based on flexibility. Beam-column element and unbonded tendon element were be involved in A computer program, named RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), that were used the analysis of RC and PSC structures. The proposed numerical method for prestressed concrete structures by strengthened of externally tendon is verified by comparison with reliable experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.533-538
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• 2013

The damage caused by Recent frequently occurring locality torrential rains is increasing rapidly. In case of densely populated metropolitan area, casualties and property damage is a serious due to landslides and debris flows and floods. Therefore, the importance of predictions about the torrential is increasing. Precipitation characteristic of the bad weather in Korea is divided into typhoons and torrential rains. This seems to vary depending on the duration and area. Rainfall is difficult to predict because regional precipitation is large volatility and nonlinear. In this paper, Very short-term precipitation forecasting pattern model is implemented using KLAPS data used by Korea Meteorological Administration. we designed very short term precipitation forecasting pattern model using GA-based RBFNNs. the structural and parametric values such as the number of Inputs, polynomial type,number of fcm cluster, and fuzzification coefficient are optimized by GA optimization algorithm.