• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.1254-1255
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• 2006

For precise property control of sintered products, it is important to understand accurately the packing density of the powder. We developed a packing simulation program that could make a packed bed of spherical particles having particle size distribution. In addition, the influence of the particle shape of the actual powder on the packing density was quantitatively analyzed. The predicted packing densities corresponded well to the actual data.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.219-224
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• 2003

An analysis procedure for the MCFC channel flow has been developed to predict the fuel cell performance. As for the electrochemical reaction, among several chemical reaction models, one that fits the data best is adopted after a comprehensive comparative study. The Wavier-Stokes, energy, and species equations are solved to obtain the velocity, temperature and concentration fields for a specified average current density. The procedure is iterative as the local current density, or the reaction rate, is allowed to vary with the gas composition. A series of calculations are then carried out to examine the effects of gas flow rate, gas composition, gas usage rate, inlet gas temperature, and average current density on the fuel cell performance. The fuel cell characteristics, such as the temperature, current density distributions, and the concentration fields, for various operating conditions are presented and discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.48-49
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• 2009

This study predicts and compares the evacuation times of a training ship, which is easily influenced by gathering patterns of crews' onboard life style. As the results, the evacuation times of the high density, like meal time, take 1.5 times longer than the low density, like normal time. And it is also evaluated that the evacuation times of high density affected by evacuation speeds show 4 times higher than the low density.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.130-136
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• 2011

Since out of a lot of traffic problems traffic accidents cause damage to life and properties of people, it stands out as one of traffic problems which needs improvement, and the loss due to traffic accident negatively affects not only the parties to the accident but also the national economy. Thus, continual concern of the government toward traffic safety is getting bigger and lately each local government is preparing a basic plan for traffic safety and vitalizing traffic safety policies. As expanding the responsibility and role of local governments for traffic safety, traffic safety measures which are based on the characteristics of each local government should be studied. Most of analytical methods in the existing traffic accidents prediction models with macroscopic vision focus on socioeconomic variables such as local population and the number of registered vehicles, and present a great deal of prediction error when they are applied in practice. In this context, this study proposed a traffic accident prediction model in respect of macroscopic level for autonomous districts (administrative districts) of Seoul City. The model development was not based on the entire city but on the type of local land usage (development density) whose relationship with traffic accident frequency was analyzed.

• ETRI Journal
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• v.22 no.4
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• pp.32-39
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• 2000

In low earth orbit (LEO) satellite communication systems, more severe phase distortion due to Doppler shift is frequently detected in the received signal than in cases of geostationary earth orbit (GEO) satellite systems or terrestrial mobile systems. Therefore, an estimation of Doppler shift would be one of the most important factors to enhance performance of LEO satellite communication system. In this paper, a new adaptive Doppler compensation scheme using location information of a user terminal and satellite, as well as a weighting factor for the reduction of prediction error is proposed. The prediction performance of the proposed scheme is simulated in terms of the prediction accuracy and the cumulative density function of the prediction error, with considering the offset variation range of the initial input parameters in LEO satellite system. The simulation results showed that the proposed adaptive compensation algorithm has the better performance accuracy than Ali's method. From the simulation results, it is concluded the adaptive compensation algorithm is the most applicable method that can be applied to LEO satellite systems of a range of altitude between 1,000 km and 2,000 km for the general error tolerance level, M = 250 Hz.

• Journal of ILASS-Korea
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• v.12 no.3
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• pp.146-153
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• 2007

The prediction of diesel spray penetration has been the subject of several works and intensive investigations are still underway by many researchers. It is required to summarize the correlations developed before 1990 days and to introduce the correlations reported recently in the literature. The existing zero-dimensional models for the prediction of diesel fuel spray penetration can be classified as theoretical and empirical correlations. Of various correlations, the models considered in this paper were selected as based on the evaluation results of previous reviews and the recently published works in the literature. The existing theoretical correlations can be classified into seven categories and the existing empirical ones as two categories in this review. According to the review of existing models, the dominating factors for the prediction of spray tip penetration are the spray angle, discharge coefficient, pressure drop across nozzle, ambient density and orifice diameter and time after the start of injection. Especially, the definition for the measurement of spray angle is different with researchers. It is required to evaluate the existing spray tip penetration models for the very high injection pressure and other fuel sprays such as DME. It is also required to evaluate the correlations for the prediction of diesel spray penetration with the connection of liquid-phase penetration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.821-827
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• 2008

This paper presents the prediction model of attenuation characteristics of satellite communication signals operating in the range from 1 to 20GHz, associated with the effects of the Asian Dust. And this paper analyze the effects of the Asian Dust in theory that dust particles size and density, OPC, signal levels, exponentail distribution and the permittivity. The prediction model of the dust attenuation was got, combining the formula of the complex dielectric constant of Asian dust. Expressions for specific attenuation and attenuation are derived in terms of the height, visibility. Therefore it make an investigate to the prediction model of attenuation characteristics continuously.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.319-328
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• 2021

In this paper, we perform prediction of amount of electric power plant for complex of wind plant using multi-layer perceptron in order to calculate exact calculation of capacity of ESS to maximize profit through generation and to minimize generation cost of wind generation. We acquire wind speed, direction of wind and air density as variables to predict the amount of generation of wind power. Then, we merge and normalize there variables. To train model, we divide merged variables into data as train and test data with ratio of 70% versus 30%. Then we train model by using training data, and we alsouate the prediction performance of model by using test data. Finally, we present the result of prediction in amount of wind power.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.162-172
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• 2011

In this paper, simulation was used to determine accuracies of genomic breeding values for polygenic traits associated with many thousands of markers obtained from high density genome scans. The statistical approach was based upon stochastically simulating a pedigree with a specified base population and a specified set of population parameters including the effective and noneffective marker distances and generation time. For this population, marker and quantitative trait locus (QTL) genotypes were generated using either a single linkage group or multiple linkage group model. Single nucleotide polymorphism (SNP) was simulated for an entire bovine genome (except for the sex chromosome, n = 29) including linkage and recombination. Individuals drawn from the simulated population with specified marker and QTL genotypes were randomly mated to establish appropriate levels of linkage disequilibrium for ten generations. Phenotype and genomic SNP data sets were obtained from individuals starting after two generations. Genetic prediction was accomplished by statistically modeling the genomic relationship matrix and standard BLUP methods. The effect of the number of linkage groups was also investigated to determine its influence on the accuracy of breeding values for genomic selection. When using high density scan data (0.08 cM marker distance), accuracies of breeding values on juveniles were obtained of 0.60 and 0.82, for a low heritable trait (0.10) and high heritable trait (0.50), respectively, in the single linkage group model. Estimates of 0.38 and 0.60 were obtained for the same cases in the multiple linkage group models. Unexpectedly, use of BLUP regression methods across many chromosomes was found to give rise to reduced accuracy in breeding value determination. The reasons for this remain a target for further research, but the role of Mendelian sampling may play a fundamental role in producing this effect.