• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.1
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• pp.98-105
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• 2010

Squeal, a kind of self-excited vibration, is generated by the friction between the disc and the friction materials. It occurs at the ending stage of the braking process, and radiates and audible frequency range of 1 kHz to 10 kHz. Squeal is generated from unstability because of the coupling between the translation and rotation of the system. This instability is caused by the follower force and follower force is normal component of the friction force. In this paper modal analysis of wheel brake system was performed in order to predict the squeal phenomenon. It was shown that the prediction of system instability is possible by FEM. A finite element model of that brake system was made. Some parts of a real brake was selected and modeled. Modal analysis method performs analyses of each brake system component. Experimental modal analysis was performed for each brake components and experimental results were compared with analytical results from FEM. To predict the dynamic unstability of a whole system, the complex eigenvalue analysis for assembly modeling of components confirmed by modal analysis is performed. The finite element models of the disk brake assembly have been constructed, and the squeal noise problems have been solved by complex eigenvalue analysis. The complex eigenvalue analysis results compared with real train test.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.213-218
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• 2001

VR (Virtual reality) technologies have given engineers the ability to design, test, and evaluate engineering systems in a virtual environment. The virtual plant is the highlight of the application of the VR technology to plant engineering. Plant design, maintenance, control, management, operation are integrated in the virtual plant. The VR monitoring system including the concept of the virtual plant is developed to replace a current control room that has number of gages and warning lamps in two-dimensional panels which shows the operating status of a plant. The operating status of the plant is displayed in the VR monitoring system through the realistic computer graphics. Sophisticated, realistic and prompt control becomes possible. The VR monitoring system consists of advanced visualization, walk-through simulation and navigation. In the virtual environment, a user can navigate and interact with each component of a plant. In addition, the user can access the information by just clicking interesting component. The VR monitoring system is operated with various modules, such as (1) virtual plant constructed with Graphic Management System (GMS), (2) Touch & Tell System, and (3) Equipment DB System of Part. In order to confirm the usefulness of the VR monitoring system, a pilot gas plant which is currently being used for plant operator training is taken as application. The end of the paper gives an outlook on the future work and a brief conclusion.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.7
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• pp.2409-2420
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• 1996

This paper describes the development of a general program for the design and part load performance analysis of single-shaft-heavy-duty gas turbines. Efforts are made to fully represent the real component features by the characteristic models and special emphasis is put on the modeling of cooled turbine stages. The design analysis routine is applied to simulate the performance of current gas turbines and its appropriateness for system analysis is validated. Meanwhile, the component parameters of real engines which describe the technology level are obtained. The program is extended to predicting the part load operation of gas turbines with the aid of models for the off-design characteristics of compressor, turbine and other main components. Part load simulation can be carried out only with limited numbers of input data. It is demonstrated that the program accurately estimates the part load characteristics of real turbines.

• Environmental Engineering Research
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• v.22 no.3
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• pp.302-311
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• 2017

Nowadays, with the burgeoning development of economy, $CO_2$ emissions increase rapidly in China. It has become a common concern to seek effective methods to forecast $CO_2$ emissions and put forward the targeted reduction measures. This paper proposes a novel hybrid model combined principal component analysis (PCA) with regularized extreme learning machine (RELM) to make $CO_2$ emissions prediction based on the data from 1978 to 2014 in China. First eleven variables are selected on the basis of Pearson coefficient test. Partial autocorrelation function (PACF) is utilized to determine the lag phases of historical $CO_2$ emissions so as to improve the rationality of input selection. Then PCA is employed to reduce the dimensionality of the influential factors. Finally RELM is applied to forecast $CO_2$ emissions. According to the modeling results, the proposed model outperforms a single RELM model, extreme learning machine (ELM), back propagation neural network (BPNN), GM(1,1) and Logistic model in terms of errors. Moreover, it can be clearly seen that ELM-based approaches save more computing time than BPNN. Therefore the developed model is a promising technique in terms of forecasting accuracy and computing efficiency for $CO_2$ emission prediction.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.699-702
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• 2001

The increasing demand in industry to produce rectangular cans at the reduction by the rectangular backward extrusion process involves better understanding of this process. In 2-D die deflection and dimensional variation of the component during extrusion, punch retraction, component injection and cooling was conducted using a coupled thermal-mechanical approach for the forward extrusion of aluminum alloy and low-carbon steel in tools of steel. Backward extrusion FE simulation and experimental simulation by physical modeling using wax as a model material have been performed. These simulations gave good results concerning the prediction of th flow modes and the corresponding surface expansions of the material occuring at the contact surface between the can and the punch. There prediction are the limits of the can height, depending on the reduction, the punch geometry, the workpiece material and the friction factor, in order to avoid the risk of damage caused by sticking of the workpiece material to the punch face. The influence of these different parameter on the distribution of the surface expansion along the inner can wall and bottom is already determined. This paper deals with the influence of the geometry changes of the forming tool and the work material in the rectangular backward using the 3-D finite element method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.11
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• pp.849-855
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• 2008

The paper addresses modeling and analysis of the part load performance of a hybrid fuel cell system integrating a polymer electrolyte membrane fuel cell(PEMFC) and a gas turbine(GT). The system is a pressurized one where the working pressure of the PEMFC is higher than the ambient pressure. In addition to the two major components, the system also includes auxiliary parts such as a steam reformer, a humidifier, and afterburner and so on. Based on design analysis, component off-design models are incorporated in the analysis program and part load operation is simulated. The mode for the part load operation of the PEMFC/GT hybrid system is a variable rotational speed operation. The operating characteristics and variations in the system efficiency and component performance parameters at part load are analyzed.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• Journal of Korean Library and Information Science Society
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• v.34 no.1
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• pp.91-109
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• 2003

One of the main issues in developing a digital library is how to implement an open digital library which can be interoperable, and diverse concepts, technology and protocols have been introduced to deal with this issue. In this study, it is analysed in terms of 'metadata interoperability', and based on the analysis, 5 basic component technologies are defined as follows: application profiles, modeling, implementation, resource discovery, portal service. Therefore it explains concepts of those core features, characteristics, cases in point, standardization and technical trends.

• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.389-394
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• 2007

This study suggests that it dynamically generates semantic Web services from Java and C++ components in order to supporting semantic Web service by using ontology. And the semantic Web should enable greater access not only to content but also to services on the Web. It needs semantic service discovery for components. So, we add ontology-based framework to Web service generation system from components. Especially, components and ontologies are transformed UML model so that it makes WSDL documents to support a generation of dynamic Web service using object modeling. The main contribution of this study is to generate web service dynamically from components and to support semantic Web environment by using ontology. In other words, this study integrates semantic Web service based on ontology and CBD method.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.258-265
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• 2006

DEVS formalism is advantageous in modeling large-scale complex systems and it reveals good readability, because it can specify discrete event systems in a hierarchical manner. In contrast, it has drawback in that the simulation speed of DEVS models is comparably slow since it requires frequent message passing between the component models in run-time. This paper proposes a method, called model composition, for simulation speedup of DEVS models. The method is viewed as a compiled simulation technique which eliminates run-time interpretation of communication paths between component models. Experimental results show that the simulation speed of transformed DEVS models is about 18 times faster than original ones.