• Atmosphere
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• v.33 no.4
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• pp.355-365
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• 2023

To proactively manage climate risk, near-term climate predictions on annual to decadal time scales are of great interest to various communities. This study evaluates the near-term climate prediction skills in East Asia with DePreSys4 retrospective decadal predictions. The model is initialized every November from 1960 to 2020, consisting of 61 initializations with ten ensemble members. The prediction skill is quantitatively evaluated using the deterministic and probabilistic metrics, particularly for annual mean near-surface temperature, land precipitation, and sea level pressure. The near-term climate predictions for May~September and November~March averages over the five years are also assessed. DePreSys4 successfully predicts the annual mean and the five-year mean near-surface temperatures in East Asia, as the long-term trend sourced from external radiative forcing is well reproduced. However, land precipitation predictions are statistically significant only in very limited sporadic regions. The sea level pressure predictions also show statistically significant skills only over the ocean due to the failure of predicting a long-term trend over the land.

• Advanced Composite Materials
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• v.18 no.3
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• pp.233-249
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• 2009

Safe installation and operation of high-pressure composite cylinders for hydrogen storage are of primary concern. It is unavoidable for the cylinders to experience temperature variation and significant thermal input during service. The maximum failure pressure that the cylinder can sustain is affected due to the dependence of composite material properties on temperature and complexity of cylinder design. Most of the analysis reported for high-pressure composite cylinders is based on simplifying assumptions and does not account for complexities like thermo-mechanical behavior and temperature dependent material properties. In the present work, a comprehensive finite element simulation tool for the design of hydrogen storage cylinder system is developed. The structural response of the cylinder is analyzed using laminated shell theory accounting for transverse shear deformation and geometric nonlinearity. A composite failure model is used to evaluate the failure pressure under various thermo-mechanical loadings. A back-propagation neural network (NNk) model is developed to predict the maximum failure pressure using the analysis results. The failure pressures predicted from NNk model are compared with those from test cases. The developed NNk model is capable of predicting the failure pressure for any given loading condition.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.301-306
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• 1996

To predict the average liquid level under the condition of the countercurrent stratified two-phase flow in a pipe, an analytical model has been suggested. This is made by introducing the interfacial level gradient into the liquid-phase and the gas-phase momentum equations. The analytical method for the gas-phase pressure drop calculation with f$_i$ $\neq$ f$_G$ has also been described using the liquid level prediction model developed in the present study.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.3
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• pp.581-587
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• 2001

Plate heat exchange(PHE) will be applied to the refrigeration and air conditioning systems as evaporators or condensers for their high efficiency and compactness. The purpose of this study is the analyze the characteristics of heat transfer and pressure drop of plate heat exchanger. Numerical work was conducted using the FLUENT code k-$\varepsilon$model. Also the dependence of heat transfer coefficient and friction factor on Reynolds number was investigated. As the Reynolds number increases, it is found that heat transfer coefficient also increases, but friction factor decreases. The study examines the internal flow, thermal distribution and the pressure distribution in the channel of plate heat exchanger. The results of CFD analysis compared with experimental data, and the difference of friction factor and Nusselt number in plate heat exchanger are 10% and 20%, respectively, Therefore the CFD analysis model is effective for the performance prediction of plate heat exchanger.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.131-134
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• 2007

This numerical analysis was performed in order to validate adoption of the sheet breakup model in high-pressure environment, which were used for prediction of spray characteristics in atmosphere environment. In experiments the higher environment pressure the shorter breakup length; the results of new sheet breakup model predicted the breakup length in good agreement with experimental results qualitatively and quantitatively. Also the shape of spray calculated by numerical analysis were agreed well with experiments quantitatively.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.6
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• pp.470-476
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• 1989

In order to develop a mathematical model which can predict the operating voltage and current of a discharge lamp, the properties and the physical phenomena of a low pressure gas discharge are investigated. Fluorescent lamp which uses a low pressure mercury-argon gas discharge is used in the model development. In a low pressure mercur-argon gas discharge, the continuity equation for each excited atom and electron, and the electron energy balance equation can predict the physical quantities of discharge. By coupling these equations and the circuit equation, the electrical characteristics of the discharge lamp can be predicted. To verify the validity of the suggested model, we calculated the voltage and current of a fluorescent lamp operating with inductor ballast for source frequency of 5KHz, 8KHz, 10KHz, and 13KHz. The results show good agreements in wave forms between the measured voltage and current, and the difference between the measured and calculated one is less than 5%.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.77-87
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• 2004

In this paper a back-propagation neural network model is developed to estimate the preconsolidation pressure of Korean soft soils based on 176 oedometer tests and 63 piezocone test results, which were compiled from 11 sites - western and southern parts of Korea. Only 147 data were used for the training of the neural network and 29 data, which were not used during the training phase, were used for the verification of trained network. Empirical and theoretical models were compared with the developed neural network model. A simple 4-4-9-1 multi-layered neural network has been developed. The cone tip resistance $q_T$ penetration pore pressure $u_2$, total overburden pressure $\sigma_{vo}$ and effective overburden pressure $\sigma'_{vo}$ were selected as input variables. The developed neural network model was validated by comparing the prediction results of the proposed neural network model for the new data which were not used for the training of the model with the measured preconsolidation pressures. It can also predict more precise and reliable preconsolidation pressures than the analytical and empirical model. Furthermore, it can be carefully concluded that neural network model can be used as a generalized model for prediction of preconsolidation pressure throughout Korea since developed model shows good performance for the new data which were not used in both training and testing data.

• 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.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1126-1135
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• 2022

The MARS code has been assessed for the prediction of onset of flow instability (OFI) in a vertical channel. For assessment, we built an experiment database that consists of experiments under various geometry and thermal-hydraulic condition. It covers pressure from 0.12 to 1.73 MPa; heat flux from 0.67 to 3.48 MW/m²; inlet sub-cooling from 39 to 166 ℃; hydraulic diameters between 2.37 and 6.45 mm of rectangular channels and pipes. It was shown that the MARS code can predict the OFI mass flux for pipes reasonably well. However, it could not predict the OFI in a rectangular channel well with a mean absolute percentage error of 8.77%. In the cases of rectangular channels, the error tends to depend on the hydraulic diameter. Because the OFI is directly related to the subcooled boiling in a flow channel, we suggest a modified subcooled boiling model for better prediction of OFI in a rectangular channel; the net vapor generation (NVG) model and the modified wall evaporation model were modified so that the effect of hydraulic diameter and heat flux can be accurately considered. The assessment of the modified model shows the prediction of OFI mass flux for rectangular channels is greatly improved.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.573-579
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• 2021

In this study, flow analysis was performed on three types of strainers for ships with different flow rates to predict the pressure drop of the strainer due to the filter of strainer. In the case of flow analysis, the flow analysis was performed by applying the porous media method by applying the resistance value derived by Ergun's equation to the filter position. As a result of the analysis, it was found that when the dimensions of the strainer body were small, the influence of the flow rate on the pressure drop was large. In addition, the amount of pressure drop and the flow rate are almost linearly proportional, and an analysis formula that can predict the amount of pressure drop was derived. In order to predict the amount of pressure drop of the strainer when blockage exist in the strainer filter, the analysis was performed by introducing the resistance ratio to derive the prediction equation. Using this equation, it is thought that it will be possible to predict the performance of the strainer due to blockage in the future strainer design and field application.