• Journal of ILASS-Korea
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• v.23 no.2
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• pp.49-57
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• 2018

Numerical study under single-injection on bi-swirl coaxial injectors with different recess lengths was performed using ANSYS Fluent. The bi-swirl coaxial injectors which consisted of inner closed-type and outer open-type swirl injectors, had three different recess lengths. By changing mass flow rates, numerical simulation was repeated using the Reynolds stress BSL turbulent model. The numerical results such as discharge coefficient and spray angle were compared with previous experimental data and were found to be approximately matched well with them, irrespective of recess length. Quantitative data which was hard to be measured from experiments, were successfully obtained through the present numerical study.

• Journal of Astronomy and Space Sciences
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• v.40 no.1
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• pp.11-18
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• 2023

The ionosphere is one of the key components of the near-Earth's space environment and has a practical consequence to the human society as a nearest region of the space environment to the Earth. Therefore, it becomes essential to specify and forecast the state of the ionosphere using both the observations and numerical models. In particular, numerical modeling of the ionosphere is a prerequisite not only for better understanding of the physical processes occurring within the ionosphere but also for the specification and forecast of the space weather. There are several approaches for modeling the ionosphere, including data-based empirical modeling, physics-based theoretical modeling and data assimilation modeling. In this review, these three types of the ionospheric model are briefly introduced with recently available models. And among those approaches, fundamental aspects of the physics-based ionospheric model will be described using the basic equations governing the mid-latitude ionosphere. Then a numerical solution of the equations will be discussed with required boundary conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2817-2834
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• 2016

The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

• The Plant Pathology Journal
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• v.36 no.1
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• pp.54-66
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• 2020

This study was conducted to evaluate usefulness of numerical weather prediction data generated by the Unified Model (UM) for plant disease forecast. Using the UM06- and UM18-predicted weather data, which were released at 0600 and 1800 Universal Time Coordinated (UTC), respectively, by the Korea Meteorological Administration (KMA), disease forecast on bacterial grain rot (BGR) of rice was examined as compared with the model output based on the automated weather stations (AWS)-observed weather data. We analyzed performance of BGRcast based on the UM-predicted and the AWS-observed daily minimum temperature and average relative humidity in 2014 and 2015 from 29 locations representing major rice growing areas in Korea using regression analysis and two-way contingency table analysis. Temporal changes in weather conduciveness at two locations in 2014 were also analyzed with regard to daily weather conduciveness (C_i) and the 20-day and 7-day moving averages of C_i for the inoculum build-up phase (C_inc) prior to the panicle emergence of rice plants and the infection phase (C_inf) during the heading stage of rice plants, respectively. Based on C_inc and C_inf, we were able to obtain the same disease warnings at all locations regardless of the sources of weather data. In conclusion, the numerical weather prediction data from KMA could be reliable to apply as input data for plant disease forecast models. Weather prediction data would facilitate applications of weather-driven disease models for better disease management. Crop growers would have better options for disease control including both protective and curative measures when weather prediction data are used for disease warning.

• Ocean Science Journal
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• v.42 no.1
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• pp.1-8
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• 2007

Acoustic volume backscattering strength data were collected and Conductivity Temperature Depth (CTD) measurements were conducted in the southern Yellow Sea in summer 2005 and 2006. The high temporal and vertical resolution acoustic data measured with a 307 kHz Acoustic Doppler Current Profiler (ADCP) and a 250 kHz acoustic Doppler profile (ADP) had dominant diel variation, which resulted from vertical migration of sound scatterers. Some scatterers congregating in the bottom layer in the daytime migrated upward at dusk, and migrated downward into the bottom layer at dawn. The migration speeds were estimated. More than 33 days data show that the diel migration varies with time. The feature of migration measured with ADCP and ADP is consistent to some extent with what is described in the study on vertical migration of zooplankton in the southern Yellow Sea with conventional net samples.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.2
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• pp.120-125
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• 2011

As an effort to secure economically viable heat recovery units, innovative fin shapes for industrial boilers are studied for better performance. In the present study a numerical modeling for the analysis of heat exchanger performance is conducted using a commercial software, ANSYS CFX and the results are compared with the experimental data. Out of several candidate fin shapes curved wavy fin is selected for the present study. Both numerical and experimental data are directly compared for heat transfer rate and pressure drop with the assumed constant surface temperature of $60^{\circ}C$. Exhaust gas is obtained from a test apparatus which supplies variable flow rates. The numerical results show reasonable agreements with the experimental data within 10% in terms of both total heat transfer and pressure loss.

• Wind and Structures
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• v.18 no.5
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• pp.549-566
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• 2014

In spite of progress in the numerical simulation of typhoon wind field in atmospheric boundary layer (ABL), using typhoon wind field model in conjunction with Monte Carlo simulation method can only accurately evaluate typhoon wind field over a general terrain. This method is not enough for a reliable evaluation of typhoon wind field over the actual complex terrain with surface roughness and topography variations. To predict typhoon wind field over the actual complex terrain in ABL, a hybrid numerical simulation method combined typhoon simulation used the typhoon wind field model proposed by Meng et al. (1995) and CFD simulation in which the Reynolds averaged Navier-Stokes (RANS) equations and k-${\varepsilon}$ turbulence model are used. Typhoon wind filed during typhoon Dujuan and Imbudo are simulated using the hybrid numerical simulation method, and compared with the results predicted by the typhoon wind field model and the wind field measurement data collected by Fugro Geotechnical Services (FGS) in Hong Kong at the bridge site from the field monitoring system of wind turbulence parameters (FMS-WTP) to validate the feasibility and accuracy of the hybrid numerical simulation method. The comparison demonstrates that the hybrid numerical simulation method gives more accurate prediction to typhoon wind speed and direction, because the effect of topography is taken into account in the hybrid numerical simulation method.

• Journal of Korea Water Resources Association
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• v.31 no.2
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• pp.189-198
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• 1998

Five dam-break floodwave models are t재 field data sets. The models included FLDWAV, SMPDBK, HEC-1, Tr66, and HEC Dimensionless Graph. The field data sets documented the disasters at Teton dam, and Yeunchun dam. The FLDWAV results are uesd to test the sensitivity of the floodwave to variations in Manning's roughness coefficient, breach size, and bottom slope. The HEC-1 analysis includes testing the sensitivity of the results to model parameters. The TR66 model and FLDWAV, with channel routing by TR66 in both cases. SMPDBK and the Dimensionless Graph procedure are applied without particular difficulties being encountered in both real world cases. It is necessary to analyze numerical limit of existing numerical models and then to apply the relatively accurate numerical model in real basin. It is found that FLDWAV model is superior in numerical accuracy and stability to any other model. This study will contribute to improve defect of numerical models and develop more precise numerical model for a efficient and rapid dam breach flood disaster predict.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1227-1229
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• 2003

Kojima Lake in Okayama prefecture is a freshing reservoir constructed adjacent to the oldest reclaimed land in Japan. This lake has a serious water quality problem because two urban rivers are flowing into it. In the present study, unsupervised classification was performed at intervals of several years using Landsat MSS data in the past 15 years. After geometric correction of these data, MSS data corresponding geographically to the field observation data were extracted and subjected to the multivariate analysis. Water quality distribution in the lake was estimated using the regression equation obtained as a result. In addition, two - dimensional and three-dimensional numerical simulations were performed and compared with the distribution obtained from the satellite images. Behavior of the reservoir flows is complicated and water quality distribution varies greatly with the flows. Here, I report the results of analysis on three factors, field observation, numerical simulation and satellite images.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.928-938
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• 2008

This study presents an approach for approximation an unknown function from a numerical data set based on the synthesis of a neuro-fuzzy model. An adaptive input data space parting method, which is used for building hyperbox-shaped clusters in the input data space, is proposed. Each data cluster is implemented here as a fuzzy set using a membership function MF with a hyperbox core that is constructed from a min vertex and a max vertex. The focus of interest in proposed approach is to increase degree of fit between characteristics of the given numerical data set and the established fuzzy sets used to approximate it. A new cutting procedure, named NCP, is proposed. The NCP is an adaptive cutting procedure using a pure function $\Psi$ and a penalty function $\tau$ for direction the input data space parting process. New algorithms named CSHL, HLM1 and HLM2 are presented. The first new algorithm, CSHL, built based on the cutting procedure NCP, is used to create hyperbox-shaped data clusters. The second and the third algorithm are used to establish adaptive neuro- fuzzy inference systems. A series of numerical experiments are performed to assess the efficiency of the proposed approach.