• Nuclear Engineering and Technology
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• v.41 no.8
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• pp.1053-1064
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• 2009

The existence of a large sodium pool in the KALIMER, a pool-type LMR developed by the Korea Atomic Energy Research Institute, plays an important role in reactor safety and operability because it determines the grace time for operators to cope with an abnormal event and to terminate a transient before reactor enters into an accident condition. A two-dimensional hot pool model has been developed and implemented in the SSC-K code, and has been successfully applied for the assessment of safety issues in the conceptual design of KALIMER and for the analysis of anticipated system transients. The other important models of the SSC-K code include a three-dimensional core thermal-hydraulic model, a reactivity model, a passive decay heat removal system model, and an intermediate heat transport system and steam generation system model. The capability of the developed two-dimensional hot pool model was evaluated with a comparison of the temperature distribution calculated with the CFX code. The predicted hot pool coolant temperature distributions obtained with the two-dimensional hot pool model agreed well with those predicted with the CFX code. Variations in the temperature distribution of the hot pool affect the reactivity feedback due to an expansion of the control rod drive line (CRDL) immersed in the pool. The existing CRDL reactivity model of the SSC-K code has been modified based on the detailed hot pool temperature distribution obtained with the two-dimensional pool model. An analysis of an unprotected transient over power with the modified reactivity model showed an improved negative reactivity feedback effect.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.129-132
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• 2006

A Pacific Ocean circulation model based on the RIAM Ocean Model (RIAMOM) with $1/6^{\circ}C\;and\;1/12^{\circ}C$ horizontal resolution successfully reproduced the peculiar circulation structures of the Pacific Ocean. The volume transports of model agree very well with the results of observations in the northwestern Pacific Ocean. Also our model successfully reproduced the observed structures of the northeastward Ryukyu Current with a subsurface core at $500{\sim}600m$. A Possible mechanism for the subsurface current core of the Ryukyu Current is proposed focusing on the blocking effect of the Ryukyu Island Chain.

• Journal of Advanced Research in Ocean Engineering
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• v.4 no.4
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• pp.174-184
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• 2018

We herein propose a new design procedure of a flexible container ship model where the vertical bending and torsional vibration modes are similar to its prototype. To achieve similarity in torsional vibration mode shapes, the height of the shear center of the model must be located below the bottom hull, similar to an actual container ship with large opening decks. Therefore, we designed a ship model by imparting appropriate stiffness to the hull, using urethane foam without a backbone. We built a container ship model according to this design strategy and validated its dynamic elastic properties using a decay test. We measured wave-induced structural vibrations and present the results of tank experiments in regular and freak waves.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2844-2853
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• 2023

A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

• Journal of Environmental Impact Assessment
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• v.12 no.4
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• pp.271-279
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• 2003

Temperature and humidity forecasting have been performed using artificial neural networks model(ANN). We composed ANN with multi-layer perceptron which is 2 input layers, 2 hidden layers and 1 output layer. Back propagation algorithm was used to train the ANN. 6 nodes and 12 nodes in the middle layers were appropriate to the temperature model for training. And 9 nodes and 6 nodes were also appropriate to the humidity model respectively. 90% of the all data was used learning set, and the extra 10% was used to model verification. In the case of temperature, average temperature before 15 minute and humidity at present constituted input layer, and temperature at present constituted out-layer and humidity model was vice versa. The sensitivity analysis revealed that previous value data contributed to forecasting target value than the other variable. Temperature was pseudo-linearly related to the previous 15 minute average value. We confirmed that ANN with multi-layer perceptron could support pollutant dispersion model by computing meterological data at real time.

• Atmosphere
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• v.16 no.4
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• pp.259-267
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• 2006

In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• Journal of Environmental Impact Assessment
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• v.23 no.3
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• pp.187-196
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• 2014

The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.355-361
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• 2022

In order to produce model ice sheets having targeted physical properties in accordance with the law of similitude, the ice model basin of Korea Research Institute of Ships and Ocean Engineering carries out a series of processes such as cooling, seeding, freezing, and tempering. Performance in ice field of ice going ships or marine structures is evaluated from model tests in ice conditions made out of a model ice sheet such as level ice, pack ice, brash ice, and ice rubble field, etc. In this study, we investigated effects of micro-bubble layers and seeding of ice nuclei included in the process generating a model ice sheet on change in physical properties of thickness, density, and flexural strength.