• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.6
• /
• pp.43-54
• /
• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Journal of the Korean Society of Groundwater Environment
• /
• v.6 no.2
• /
• pp.95-100
• /
• 1999

Hydrocarbon compounds in vadose zone soils caused by adsorption onto the surfaces of solid particles are generally considered to show retardation effect. In this study, we investigated the retardation effect on the transport of Benzene in a sandy soil by conducting batch and column tests. The batch test was conducted by equilibrating dry soil mass with Benzene solutions of various initial concentrations. and by analyzing the concentrations of Benzene in initial and equilibrated solutions using HPLC. The column test consisted of monitoring the concentrations of effluent versus time known as a breakthrough curve (BTC). We used KCl and Benzene solutions with the concentration of 10 g/L and 0.88 g/L as a tracer, and injected them into the inlet boundary of the soil sample as a square pulse type respectively, and monitored the effluent concentrations at the exit boundary under a steady state condition using an EC-meter and HPLC. From the batch test, we obtained a distribution coefficient assuming that a linear adsorption isotherm exists and calculated the retardation factor based on the bulk density and porosity of the column sample. We also predicted the column BTC curve using the retardation factor obtained from the distribution coefficient and compared with the measured BTC of Benzene. The results of the column test showed that i) the peak concentration of Benzene was much smaller than that of KCl and ⅱ) the travel times of peak concentrations for the two tracers were more or less identical. These results indicate that adsorption of Benzene onto the sand panicles occurred during the pulse propagation but the retardation of Benzene caused by adsorption was not present in the studied soil. Comparison of the predicted with the measured BTC of Benzene resulted in a poor agreement due to the absence of the retardation phenomenon. The only way to describe the absolute decrease of Benzene concentration in the column leaching experiment was to introduce a decay or sink coefficient in the convection-dispersion equation (CDE) model to account for an irreversible sorption of Benzene in the aqueous phase.

• Journal of the Korean Society of Safety
• /
• v.11 no.4
• /
• pp.143-150
• /
• 1996

This is an explicit-Implicit, finite element analysis for linear as well as nonlinear hygrothermal stress problems. Additional features, such as moisture diffusion equation, crack element and virtual crack extension(VCE ) method for evaluating J-integral are implemented in this program. The Linear Elastic Fracture Mechanics(LEFM) Theory is employed to estimate the crack driving force under the transient condition for and existing crack. Pores in materials are assumed to be saturated with moisture in the liquid form at the room temperature, which may vaporize as the temperature increases. The vaporization effects on the crack driving force are also studied. The Ideal gas equation is employed to estimate the thermodynamic pressure due to vaporization at each time step after solving basic nodal values. A set of field equations governing the time dependent response of porous media are derived from balance laws based on the mixture theory Darcy's law Is assumed for the fluid flow through the porous media. Perzyna's viscoplastic model incorporating the Von-Mises yield criterion are implemented. The Green-Naghdi stress rate is used for the invariant of stress tensor under superposed rigid body motion. Isotropic elements are used for the spatial discretization and an iterative scheme based on the full newton-Raphson method is used for solving the nonlinear governing equations.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.16 no.6
• /
• pp.521-531
• /
• 2014

This paper is a study for behaviour of cavern type anchorage tunnels for suspension bridges with cable tension. Anchorage behaviour, design method for anchorage, and failure surface angle, ${\delta}$ are analyzed by comparing numerical analysis results and ultimate pullout capacities($P_u$) using bilinear corelation equation. Results show that design depths for cavern type anchorage tunnels are easily checked with linear relationships for $P/{\gamma}/H$ vs. displacement and $P_u/{\gamma}/H$ vs. H/b. The analysis results of maximum shear strain distribution and plastic status show that failure shapes are closer to circular arc model than soil cone model which frequently used. To an easy calculation of the ultimate pullout capacity, we propose a simple bilinear failure model in this study. The calculated ultimate pullout capacities from the proposed bilinear corelation equation using two failure angles results are similar to the ultimate pullout capacities from numerical analysis.

• Journal of Bio-Environment Control
• /
• v.26 no.4
• /
• pp.411-417
• /
• 2017

Environmental and growth factors such as light intensity, vapor pressure deficit, and leaf area index are important variables that can change the transpiration rate of plants. The objective of this study was to compare the transpiration rates estimated by modified Penman-Monteith model and artificial neural network. The transpiration rate of paprika (Capsicum annuum L. cv. Fiesta) was obtained by using the change in substrate weight measured by load cells. Radiation, temperature, relative humidity, and substrate weight were collected every min for 2 months. Since the transpiration rate cannot be accurately estimated with linear equations, a modified Penman-Monteith equation using compensated radiation (Shin et al., 2014) was used. On the other hand, ANN was applied to estimating the transpiration rate. For this purpose, an ANN composed of an input layer using radiation, temperature, relative humidity, leaf area index, and time as input factors and five hidden layers was constructed. The number of perceptons in each hidden layer was 512, which showed the highest accuracy. As a result of validation, $R^2$ values of the modified model and ANN were 0.82 and 0.94, respectively. Therefore, it is concluded that the ANN can estimate the transpiration rate more accurately than the modified model and can be applied to the efficient irrigation strategy in soilless cultures.

• Korean Journal of Food Science and Technology
• /
• v.36 no.5
• /
• pp.733-739
• /
• 2004

Model for optimally dimensioned PE film bag was developed according to fruit size to maintain best quality of 'Fuyu' persimmon in modified atmosphere packaging (MAP) storage based on relationship between quality and oxygen and carbon dioxide in PE film bag. Harvested persimmons were graded into five sizes, and average weights were LL:261, L:217, M:188, S:168, and SS:154 g. Five fruit units of each grade were optimized in five PE film bag sizes of $150{\times}376,\;140{\times}357,\;130{\times}344,\;130{\times}333,\;and\;120{\times}3l8\;mm$. To minimize quality deterioration such as softening and discoloration, optimal oxygen and carbon dioxide concentrations in PE film bag were 0.5-1.0 and 6.0-8.0%, respectively, and optimal thickness of PE film bag according to fruit size were LL:45, L:50, M:55, S:60, and $SS:65\;{\mu}m$. For all fruit sizes, model for PE film bag area $(mm^2)$ was good quadratic simple equation by fruit weight (g): $Y=-4055.707+627.993X_1-0.701{X_1}^2$. Model far optimal oxygen and carbon dioxide (Y) concentration in PE film bag was suited to linear multiple equation by fruit weight $(X_1,\;g)$ and PE film thickness $(X_2,\;{\mu}m)$. Equations for oxygen and carbon dioxide concentrations (%) were $Y=5.798-0.0109X_l-0.0491X_2\;and\;Y=-2.427+0.01927X_l +0.09646X_2$, respectively.

• Geophysics and Geophysical Exploration
• /
• v.15 no.1
• /
• pp.33-38
• /
• 2012

A resistivity method has been applied to wide range of engineering and environmental problems with the help of automatic and precise data acquisition. Thus, more accurate modeling and inversion of time-lapse monitoring data are required since resistivity monitoring has been introduced to quantitatively find out subsurface changes With respect to time. Here, we used the finite element method (FEM) for 3D resistivity modeling since the method is easy to realize complex topography and arbitrary shaped anomalous bodies. In the FEM, the linear elements, also referred to as first order elements, have certain advantages of simple formulation and narrow bandwidth of system equation. However, the linear elements show the poor accuracy and slow convergence of the solution with respect to the number of elements or nodes. To achieve the higher accuracy of finite element solution, high order elements are generally used. In this study, we developed a 3D resistivity modeling program using high order Serendipity elements. Comparing the Serendipity element solutions for a cube model with the linear element solutions, we assured that the Serendipity element solutions are more accurate than the linear element solutions in the 3D resistivity modeling.

• Journal of the Korean GEO-environmental Society
• /
• v.15 no.9
• /
• pp.87-92
• /
• 2014

The Ground anchor is reinforcement to resist pull-out through ground that is used supports structure. The pull-out resistance of anchor is constructed by skin friction resistance from compression borehole wall in expanded wings and bearing pressure from the ground. Especially, underreamed ground anchor is reinforcement that adopts active reinforcement to prevent deformation of ground using bearing resistance generated reaming anchorage. This study is conducted to calculate bearing resistance of underreamed ground anchor. Realistic model tests were fulfilled to determine bearing resistance of anchor, and correlate results of tests to Uniaxial Compressive Strengths (UCS) of ground models that assumed weathered rock condition in 8 case. In a comprehensive series of the tests, the bearing resistances were measured by pull-out tests. The bearing resistances derived from tests have a linear correlation with UCS. We also suggest empirical equation between bearing resistance and UCS of rocks by single linear regression analyses. In test results of this study, the bearing resistances were evaluated approximately 13 times higher than UCS of the grounds, and it is qualitatively similar to numerical values of pull-out force derived from theory.

• Journal of Microbiology and Biotechnology
• /
• v.17 no.9
• /
• pp.1437-1444
• /
• 2007

A response surface model was developed for predicting the growth rates of Staphylococcus aureus in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10, 20, 30, and $40^{\circ}C$. In all experimental variables, the primary growth curves were well ($r^2=0.9000$ to 0.9975) fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. aureus were generally decreased by basic (pH 9-10) or acidic (pH 5-6) conditions and higher NaCl concentrations. The response surface model was identified as an appropriate secondary model for growth rates on the basis of correlation coefficient (r=0.9703), determination coefficient ($r^2=0.9415$), mean square error (MSE=0.0185), bias factor ($B_f=1.0216$), and accuracy factor ($A_f=1.2583$). Therefore, the developed secondary model proved reliable for predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. aureus in TSB medium.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.6
• /
• pp.1075-1083
• /
• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.