• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2836-2846
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• 2020

During severe nuclear power plant (NPP) accidents, a H₂/CO mixture can be generated in the reactor pressure vessel by core degradation and in the containment as well by molten corium-concrete interaction. In spite of its importance, a state-of-the-art methodology predicting H₂/CO combustion risk relies predominantly on empirical correlations. It is therefore necessary to develop a proper methodology for flammability evaluation of H₂/CO mixtures at ex-vessel phases characterized by three factors: CO concentration, high temperature, and diluents. The developed methodology adopted Le Chatelier's law and a calculated non-adiabatic flame temperature model. The methodology allows the consideration of the individual effect of the heat transfer characteristics of hydrogen and carbon monoxide on low flammability limit prediction. The accuracy of the developed model was verified using experimental data relevant to ex-vessel phase conditions. With the developed model, the prediction accuracy was improved substantially such that the maximum relative prediction error was approximately 25% while the existing methodology showed a 76% error. The developed methodology is expected to be applicable for flammability evaluation in chemical as well as NPP industries.

• Macromolecular Research
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• v.17 no.10
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• pp.797-806
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• 2009

The mechanical and thermal behaviors of polyamide-6/clay nanocomposites were studied using the continuum-based, micromechanical models such as Mori-Tanaka, Halpin-Tsai and shear lag. Mechanic-based model prediction provides a better understanding regarding the dependence of the nanocomposites' reinforcement efficiency on conventional filler structural parameters such as filler aspect ratio ($\alpha$), filler orientation (S), filler weight fraction (${\Psi}_f$), and filler/matrix stiffness ratio ($E_f/E_m$). For an intercalated and exfoliated nanocomposite, an effective, filler-based, micromechanical model that includes effective filler structural parameters, the number of platelets per stack (n) and the silicate inter-layer spacing ($d_{001}$), is proposed to describe the mesoscopic intercalated filler and the nanoscopic exfoliated filler. The proposed model nicely captures the experimental modulus behaviors for both intercalated and exfoliated nanocomposites. In addition, the model prediction of the heat distortion temperature is examined for nanocomposites with different filler aspect ratio. The predicted heat distortion temperature appears to be reasonable compared to the heat distortion temperature obtained by experimental tests. Based on both the experimental results and model prediction, the reinforcement efficiency and heat resistance of the polyamide-6/clay nanocomposites definitely depend on both conventional (${\alpha},\;S,\;{\Psi}_f,\;E_f/E_m$) and effective (n, $d_{001}$) filler structural parameters.

• Smart Media Journal
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• v.11 no.5
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• pp.38-47
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• 2022

Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R² value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R² values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.

• Journal of Radiation Protection and Research
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• v.36 no.1
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• pp.1-7
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• 2011

A simple mathematical model of simultaneous combined action of environmental agents has been proposed to describe the synergistic interaction of microwave and high ambient temperature treatment on animal heating. The model suggests that the synergism is caused by the additional effective damage arising from an interaction of sublesions induced by each agent. These sublesions are considered to be ineffective if each agent is taken individually. The additional damage results in a higher body temperature increment when compared with that expected for an independent action of each agent. The model was adjusted to describe the synergistic interaction, to determine its greatest value and the condition under which it can be achieved. The prediction of the model was shown to be consistent with experimental data on rabbit heating. The model appears to be appropriate and the conclusions are valid.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.44-50
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• 2004

The purpose of this study is to improve the prediction ability of the atomization and vaporization processes of GDI spray under high-pressure and high-temperature conditions. Several models have been introduced and compared. The atomization process was modeled using hybrid breakup model that is composed of Conical Sheet Disintegration (CSD) model and Aerodynamically Progressed TAB(APTAB) model. The vaporization process was modeled using Spalding model, modified Spalding model and Abramzon ＆ Sirignano model. Exciplex fluorescence method was used for comparing the calculated with the experimental results. The experiment and calculation were performed at the ambient pressure of 0.5 MPa and 1.0 MPa and the ambient temperature of 473k. Comparison of caldulated and experimental spray characteristics was carried out and Abramzon ＆ Sirignano model and modified Spalding model had the better prediction ability for vaporization process than Spalding model.

• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Journal of the korean Society of Automotive Engineers
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• v.7 no.3
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• pp.83-93
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• 1985

The prediction of emission concentrations in a 4cycle spark ignition engine was made by considering nonuniform model with thermodynamics, chemical equilibrium and kinetic mechanism of nitric oxide. Calculation of this model shows that a temperature difference of the order of 500K can be established across he cylinder. Results of the kinetic calculation of nitric oxide show that the temperature gradient across the cylinder has a profound effect on the nitric oxide formation. The predicted values for nitric oxide, carbon dioxide and carbon monoxide agree with measured ones for a variety of equivalence ratio.

• Ocean and Polar Research
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• v.23 no.2
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• pp.181-188
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• 2001

We describe here the Korea ocean prediction system that closely resembles operational numerical weather prediction systems. This prediction system will be served for real-time forecasts. The core of the system is a three-dimensional primitive equation numerical circulation model, based on ${\sigma}$-coordinate. Remotely sensed multi-channel sea surface temperature (MCSST) is imposed at the surface. Residual subsurface temperature is assimilated through the relationship between vertical temperature structure function and residual of sea surface height (RSSH) using an optimal interpolation scheme. A unified grid system, named as [K-E-Y], that covers the entire seas around Korea is used. We present and compare hindcasting results during 1990-1999 from a model forced by MCSST without incorporating RSSH data assimilation and the one with both MCSST and RSSH assimilated. The data assimilation is applied only in the East Sea, hence the comparison focuses principally on the mesoscale features prevalent in the East Sea. It is shown that the model with the data assimilation exhibits considerable skill in simulating both the permanent and transient mesoscale features in the East Sea.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.366-372
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• 2009

Creep life prediction has been commonly used by a time-temperature parameter (TTP) which is correlated to an applied stress and temperature, such as Larson-Miller (LM), Orr-Sherby-Dorn (OSD), Manson-Haferd (MH) and Manson-Succop (MS) parameters. A stress-temperature linear model (STLM) based on Arrhenius, Dorn and Monkman-Grant equations was newly proposed through a mathematical procedure. For this model, the logarithm time to rupture was linearly dependent on both an applied stress and temperature. The model parameters were properly determined by using a technique of maximum likelihood estimation of a statistical method, and this model was applied to the creep data of Alloy 617. From the results, it is found that the STLM results showed better agreement than the Eno’s model and the LM parameter ones. Especially, the STLM revealed a good estimation in predicting the long-term creep life of Alloy 617.