• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.58-61
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• 2015

Combustion instability in solid rocket motors is a long-term open problem since the first rockets were used. Based on the numerous previous studies, it is known that the limit cycle amplitude is one of the key characteristics of the nonlinear combustion instability in solid rocket motors. Flandro's extended energy balance corollary, aims to predict the limit cycle amplitude of complex, nonlinear pressure oscillations for rockets or air-breathing engines, and leads to a precise assessment of nonlinear combustion instability in solid rocket motors. However, based on the comparison with experimental data, it is revealed that the Flandro's method cannot accurately describe such a complex oscillatory pressure. Thus in this work we make modifications of the nonlinear term in the nonlinear wave equations which represents the interaction of different modes. Through this modified method, a numerical simulation of the cylindrical solid rocket has been carried out, and the simulated result consists well with the experimental data. It means that the added coefficient makes the nonlinear wave growth equations describe the experimental data better.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.2
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• pp.116-123
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• 2018

These days, geographic information system has released in everyday life and industries. However, the shipyard only uses it to manage the layout of the yard. In this study, we apply the Geographic Information System to shipbuilding block logistics simulation to analyse the behavior of bogies and forklifts carrying blocks and materials in the shipyard. The shipyard manages daily block logistics plans at the execution planning stage. However, since it is a daily plan, it is difficult to respond to an unexpected situation immediately, and application to judge a certain value or higher value is insufficient. Therefore, a simulation model was created using the shape and attribute information inherent in the geographic information system to verify and improve the block logistics of the mid-and long-term yards. Through this simulation model, we will analyse loads on the workplace, stockyard, and road, and contribute to overall logistics improvement from the point of view of resource planning. In addition, the results of the simulation are reflected in the planning, to help support various decisions.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.495-497
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• 1992

Hourly load forecasting has become indispensable for practical simulation of electric power system as the system become larger and more complicated. To forecast the future hourly load the cyclic behavior of electric load which follows seasonal weather, day or week and office hours is to be analyzed so that the trend of the recent behavioral change can be extrapolated for the short term. For the long term, on the other hand, the changes in the infra-structure of each electricity consumer groups should be assessed. In this paper the concept and process of hourly load forecasting for hourly load is introduced.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.1
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• pp.52-57
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• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.124-129
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• 2003

In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models fir simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.70-73
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• 1992

This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathematically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTNI Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.410-415
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• 2005

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits at a wide range of scales - Self-similarity. Self-similarity is expressed by long term dependency, this is contradictory concept with Poisson model that have relativity short term dependency. Therefore, first of all for design and dimensioning of next generation communication network, traffic model that are reflected burstness and self-similarity is required. Here self-similarity can be characterized by Hurst parameter. In this paper, when different many data traffic being integrated under various environments is arrived to communication network, Hurst Parameter's change is analyzed and compared with simulation results.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.3
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• pp.453-460
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• 2007

An overview of developments important in the future of animal breeding is discussed. Examples from the application of quantitative genetic principles to selection in chickens and mice are given. Lessons to be learned from these species are that selection for production traits in livestock must also consider selection for reproduction and other fitness-related traits and inbreeding should be minimized. Short-term selection benefits of best linear unbiased predictor methodology must be weighed against long-term risks of increased rate of inbreeding. Different options have been developed to minimize inbreeding rates while maximizing selection response. Development of molecular genetic methods to search for quantitative trait loci provides the opportunity for incorporating marker-assisted selection and introgression as new tools for increasing efficiency of genetic improvement. Theoretical and computer simulation studies indicate that these methods hold great promise once genotyping costs are reduced to make the technology economically feasible. Cloning and transgenesis are not likely to contribute significantly to genetic improvement of livestock production in the near future.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.105-129
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• 2002

IT companies make a lot of efforts for sharing and utilizing of experiences of their members and transforming them into the organizational knowledge as a competitive core. But they face a dilemma that they have to spend time and financial resource to perform activities around knowledge management for the long-term gains, while carrying field-works for making short-term profits. As an initial attempt to tackle this managerial problem, this paper try to investigate the mechanism of knowledge management in a small IT company in Korea with a synthetic view-point using system dynamics simulation model. It depicts the dynamic behaviors of knowledge management and presents some findings of political leverage. Although it has to be replenished further, the scheme for the dynamism of knowledge management and the findings presented in the paper could be useful for the decision makers particularly of knowledge-intensive organizations

• Water Engineering Research
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• v.1 no.3
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• pp.233-242
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• 2000

A system for regularly appraising the reliability of streamflow data, KORSAS (KOwaco's Regular Streamflow Appraising System) was developed on PC based Windows for hydrological specialists and engineers working in the Korea Water Resources Corporation (KOWACO). The reliability of streamflow rates can be evaluated with KORSAS in various as pects according to the evaluation duration and method. The former being selected as short term (event based) or long term(continus based), and the latter being classified into comparison methods of flow measurement, other stations results, and simulation. Rainfall-runoff models can be used together with KORSAS in order to evaluate the reliability of observed flow data by comparing with simulated flow data. The objective of this study is to develop a systematic methodology in various aspects to evaluate the reliability of streamflow data regularly.