• Journal of Fisheries and Marine Sciences Education
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• v.26 no.5
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• pp.1108-1118
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• 2014

The purpose of this study was to spread the education of human creativity program and its possibility of consistency, and its application to school system by exploring the evaluation system that determines the valuable and useful decisions. This study was based on the evaluation system according to CIPP model regarding the program's general ideas and its role. The interest of the education of human creativity was increasing as well as its progress of program, and we searched 13 figures and 55 evaluation index according to increase the program's effectiveness and nation-wise situation of evaluation model. The conclusion of this study was that the human creativity program's evaluation was composed of six compartments. And the context evaluation was composed of three evaluation models and eleven index, and input evaluation was composed of three evaluation model and 15 index, while process evaluation is composed of three evaluation models and thirteen evaluation index. Lastly, output evaluation had four evaluation model and sixteen index.

• Journal of computational fluids engineering
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• v.12 no.2
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• pp.8-13
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• 2007

A general purpose program NUFLEX for the analysis 3-D thermo/fluid flow and pre/post processor in complex geometry has been developed, which consists of a flow solver based on FVM and GUI based pre/post processor. The solver employs a general non-orthogonal grid system with structured grid and solves laminar and turbulent flows with standard/RNG $k-{\varepsilon}$ turbulence model. In addition, NUFLEX is incorporated with various physical models, such as interfacial tracking, cavitation, MHD, melting/solidification and spray models. For the purpose of evaluation of the program and testing the applicability, many actual problems are solved and compared with the available data. Comparison of the results with that by STAR-CD or FLUENT program has been also made for the same flow configuration and grid structure to test the validity of NUFLEX.

• Fire Science and Engineering
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• v.24 no.4
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• pp.33-40
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• 2010

A numerical model considering the vapor pressure and the creep models, in the form of a analytical program, for tracing the behavior of high strength concrete (HSC) members exposed to fire is presented. The two stages, i.e., spalling procedure and fire resistance time, associated with the thermal, moisture flow, creep and structural analysis, for the prediction of fire resistance behavior are explained. The use of the analytical program for tracing the response of HSC member from the initial pre-loading stage to collapse, due to fire, is demonstrated. The validity of the numerical model used in this program is established by comparing the predictions from this program with results from others fire resistance tests. The analytical program can be used to predict the fire resistance of HSC members for any value of the significant parameters, such as load, sectional dimensions, member length, and concrete strength.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.47-54
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• 2015

Recently, rapid urbanization and industrialization had increased the air pollution in major cities by increasing the fuel consumption. Air pollution models have been widely used for air quality management in many countries. Also, a lot of related studies have been conducted using air dispersion models. In this study, The meteorological preprocessing program was developed to convert the korea meteorological data to the U.S. meteorological data and to expand the usability of air dispersion models of U.S. EPA. In addition, the usability evaluation was carried out through a case study. In the results of the evaluation of the program, this program was accurately convert the Korea meteorological data to the U.S. meteorological data, and the prediction was carried out without a error in air quality modeling. Therefore, the program showed a high utilization as meteorological data pre-processing tool.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1540-1553
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• 2019

A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.

• Genomics & Informatics
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• v.21 no.4
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• pp.50.1-50.9
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• 2023

Vaccine development is one of the key efforts to control the spread of coronavirus disease 2019 (COVID-19). However, it has become apparent that the immunity acquired through vaccination is not permanent, known as the waning effect. Therefore, monitoring the proportion of the population with immunity is essential to improve the forecasting of future waves of the pandemic. Despite this, the impact of the waning effect on forecasting accuracies has not been extensively studied. We proposed a method for the estimation of the effective immunity (EI) rate which represents the waning effect by integrating the second and booster doses of COVID-19 vaccines. The EI rate, with different periods to the onset of the waning effect, was incorporated into three statistical models and two machine learning models. Stringency Index, omicron variant BA.5 rate (BA.5 rate), booster shot rate (BSR), and the EI rate were used as covariates and the best covariate combination was selected using prediction error. Among the prediction results, Generalized Additive Model showed the best improvement (decreasing 86% test error) with the EI rate. Furthermore, we confirmed that South Korea's decision to recommend booster shots after 90 days is reasonable since the waning effect onsets 90 days after the last dose of vaccine which improves the prediction of confirmed cases and deaths. Substituting BSR with EI rate in statistical models not only results in better predictions but also makes it possible to forecast a potential wave and help the local community react proactively to a rapid increase in confirmed cases.

• Atmosphere
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• v.23 no.2
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• pp.231-235
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• 2013

We parallelized WRF major physics routines for Nvidia GP-GPUs with CUDA Fortran. GP-GPUs are originally designed for graphic processing, but show high performance with low electricity for calculating numerical models. In the CUDA environment, a data domain is allocated into thread blocks and threads in each thread block are computing in parallel. We parallelized the WRF program to use of thread blocks efficiently. We validated the GP-GPU program with the original CPU program, and the WRF model using GP-GPUs shows efficient speedup.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.505-509
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• 2005

Analysis program to estimate the dynamic characteristics of bridge is investigated by using three-dimensional analytical model considering vehicle-bridge interaction. A dynamic interaction models of the vehicle-bridge system are established, which is composed of a vehicle element model and a finite element bridge model. The vehicle models are established according to the structure and suspending properties of vehicle. The dynamic responses of the bridge are calculated. But the computer simulation program is being verified with field tests results, it must be corrected according to them.

• Journal of Engineering Education Research
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• v.4 no.2
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• pp.20-26
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• 2001

An academic advising program has been initiated by Yonsei University to help first-year students formulate sound educational and career plans. We analysed the program on the basis of organizational models of advising of American colleges. Represented by University college and academic advisor, it can be categorized as a compromised system of Split and Total-Intake models.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.647-664
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• 2022

The powerful data mapping capability of computational deep learning methods has been recently explored in academic works to develop strategies for structural health monitoring through appropriate characterization of dynamic responses. In many cases, these studies concern laboratory prototypes and finite element models to validate the proposed methodologies. Therefore, the present work aims to investigate the capability of a deep learning algorithm called Sparse Autoencoder (SAE) specifically focused on detecting structural alterations in real-case studies. The idea is to characterize the dynamic responses via SAE models and, subsequently, to detect the onset of abnormal behavior through the Shewhart T control chart, calculated with SAE extracted features. The anomaly detection approach is exemplified using data from the Z24 bridge, a classical benchmark, and data from the continuous monitoring of the San Vittore bell-tower, Italy. In both cases, the influence of temperature is also evaluated. The proposed approach achieved good performance, detecting structural changes even under temperature variations.