• Journal of the Society of Disaster Information
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• v.13 no.3
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• pp.286-295
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• 2017

In this study, it is compared various coefficients of subgrade reaction for application of numerical analysis based on measured data by using various theories and empirical formula. The ratio of the maximum and minimum value is 6.80 at the top of wall but it is 1.06 at the maximum displacement point depends on change of calculated coefficient of subgrade reaction. The data of displacement were generally similar considering an increment of a coefficient of subgrade reaction. And the results of comparison of the displacement at the maximum displacement point by numerical analysis and measured data show similar displacement shape.

• Advances in nano research
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• v.7 no.6
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• pp.419-429
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• 2019

The effect of an increasing percentage of nanofiller (glass cenosphere) with Glass/Epoxy hybrid composite curved panels modeled mathematically using the multiscale concept and subsequent numerical eigenvalues of different geometrical configurations (cylindrical, spherical, elliptical, hyperboloid and flat) predicted in this research article. The numerical model of Glass/Epoxy/Cenosphere is derived using the higher-order polynomial type of kinematic theory in association with isoparametric finite element technique. The multiscale mathematical model utilized for the customized computer code for the evaluation of the frequency data. The numerical model validation and consistency verified with experimental frequency data and convergence test including the experimental elastic properties. The experimental frequencies of the multiscale nano filler-reinforced composite are recorded through the impact hammer frequency test rig including CDAQ-9178 (National Instruments) and LABVIEW virtual programming. Finally, the nano cenosphere filler percentage and different design associated geometrical parameters on the natural frequency data of hybrid composite structural configurations are illustrated through a series of numerical examples.

• Computers and Concrete
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• v.25 no.2
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• pp.181-192
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• 2020

Nowadays, steel fiber reinforced concretes (SFRCs) are widely used in practical applications. Significant experimental research has thus been carried out to determine the constitutive equations that represent the behavior of SFRCs under multiaxial loadings. However, numerical modelling of SFRCs via FEM has been challenging due to the complexities of the implementation of these constitutive equations. In this study, following the literature, a plasticity model is constructed for the behavior of SFRCs that involves the Willam-Warnke failure surface with the relevant evolution laws and a non-associated flow rule for determining the plastic deformations. For the precise (yet rapid) integration of the constitutive equations, an explicit substepping scheme consisting of yield intersection and drift correction algorithms is employed and thus implemented in ABAQUS via UMAT. The FEM model includes various material parameters that are determined from the experimental data. Three sets of parameters are used in the numerical simulations. While the first set is from the experiments that are conducted in this study on SFRC specimens with various contents of steel fibers, the other two sets are from the experiments reported in the literature. The response of SFRCs under multiaxial compression obtained from various numerical simulations are compared with the experimental data. The good agreement between numerical results and the experimental data indicates that not only the adopted plasticity model represents the behavior of SFRCs very well but also the implemented integration scheme can be employed in practical applications of SFRCs.

• Environmental Engineering Research
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• v.23 no.4
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• pp.442-448
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• 2018

This paper presents the numerical simulation of advection-diffusion mechanism of BOD concentration which was used as an indicator of waste only in one flow-direction of waste stabilization ponds (1-dimension (1-D)). This model was represented in partial differential equation order 2. The purpose of this paper was to determine the simulation of the model 1-D of wastewater transport phenomena based advection-diffusion mechanism and did validate the model. Numerical methods which was used for the solution of this model is finite difference method with Forward Time Central Space scheme. The simulation results which was obtained would be compared with field observation data as a validation model. Collection of field data was carried out in the Wastewater Treatment Plant Sewon, Bantul, D.I. Yogyakarta. The results of numerical simulations were indicate that the advection-diffusion mechanism takes place continuously over time. Then validation of the model was state that there was a difference between the calculation results with the field data, with a correlation value of 0.998.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.63-63
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• 2021

Bed shear stress is important variable in river flow analysis. The bed shear stress has an effects on bed erosion, sediment transport, and mean flow characteristics. Quadratic formula to estimate bed shear stress is widely used, 𝜏=𝜌c_fu|u| in which friction coefficient, c_f, needs to be assigned to numerical models. The aim of this study is to estimate Chezy coefficient using bathymetry data measured by ADCP. Bed form geometry variables will be estimated form bed profile, then Chezy coefficient will be determined using estimated bed form geometry variables in order to set friction coefficient to numerical model. From the probability density function obtained from the bathymetry data, Chezy coefficient will be randomly generated since Chezy coefficient is not uniform over the space and it does not depend on spatial variables such as water depth and distance from river bank. Numerical test will be performed to find to demonstrate randomly extracted Chezy coefficient is appropriate. The result of this study is valuable in that the friction coefficient is estimated in consideration of the bed profile, and as a result, uncertainty of the friction coefficient can be reduced.

• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Structural Engineering and Mechanics
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• v.49 no.5
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• pp.555-568
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• 2014

In this article, stability of composite conical shells subjected to dynamic external pressure is investigated by numerical and experimental methods. In experimental tests, cross-ply glass woven fabrics were selected for manufacturing of specimens. Hand-layup method was employed for fabricating the glass-epoxy composite shells. A test-setup that includes pressure vessel and data acquisition system was designed. Also, numerical analyses are performed. In these analyses, effect of actual geometrical imperfections of experimental specimens on the numerical results is investigated. For introducing the imperfections to the numerical models, linear eigen-value buckling analyses were employed. The buckling modes are multiplied by very small numbers that are derived from measurement of actual specimens. Finally, results are compared together while a good agreement between results of imperfect numerical analyses and experimental tests is observed.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1645-1650
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• 2003

A numerical and experimental study is made of thermal behavior of a hot chuck which is specially designed for flip-chip bonders. The hot chuck consists of radiant heat sources and a heated plate of very high conductivity, which is for achievement of high-speed heat-up. A simplified numerical model is developed to simulate unsteady thermal behavior of the heated plate. Parallel experimental work is also conducted for a prototype of the hot chuck. Based on the experimental data, the numerical model is tuned to improve the reliability and accuracy. Design analysis using the numerical model is conducted. The results of numerical computations illustrate that the radiant heater system adopted in this study satisfies the key design requirements for a high-performance hot chuck.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.439-459
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• 2023

Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

• Journal of the Korean Ceramic Society
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• v.56 no.6
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• pp.596-600
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• 2019

Artificial intelligence with a sufficient amount of realistic big data in certain applications has been demonstrated to play an important role in designing new materials or in manufacturing high-quality products. To reduce cracks in ceramic products using machine learning, it is desirable to utilize big data in recently developed data-driven optimization schemes. However, there is insufficient big data for ceramic processes. Therefore, we developed a numerical algorithm to make "virtual" manufacturing data sets using indirect methods such as computer simulations and image processing. In this study, a numerical algorithm based on the random walk was demonstrated to generate images of cracks by adjusting the conditions of the random walk process such as the number of steps, changes in direction, and the number of cracks.