• Composites Research
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• v.33 no.1
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• pp.13-18
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• 2020

Recently, the fire rescue truck in problem proceed research it for the fast works action and for pass the small road. So we were research for weight reduction. In this study, the (NO. 5) fifth boom of the fire rescue truck have 288 mm(W) × 299 mm(D) × 3,691 mm(L) with a maximum load of 876 kg and the thickness of 3 mm of the Steel Boom. This changing of Steel (STRENX960) to CFRP was weave Carbon Fiber NCF (±45°, 2axis) and then it make the NCF Prepreg. This process was designed based on structural analysis, the effects of NCF Prepreg (±45°) on torsion were identified, and the optimal design was made with Stacking Pattern (b). Stack patterns were optimized for levels equal or higher than existing Steel Boom and CFRP Boom stacked in the UD direction, and finally, the lightening effect on weight of approximately 49.6% of the steel was identified.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.145-156
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• 2000

In this paper, we propose a new methodology which includes the optimal design procedure of Polynomial Neural Networks(PNN) structure for model identification of complex and nonlinear system. The proposed PNN algorithm is based on GMDA(Group Method of Data handling) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. In other words, the PNN uses high-order polynomial as extended type besides quadratic polynomial used in GMDH, and the number of input of its node in each layer depends on that of variables used in the polynomial. The design procedure to obtain an optimal model structure utilizing PNN algorithm is shown in each stage. The study is illustrated with the aid of pH neutralization process data besides representative time series data for gas furnace process used widely for performance comparison, and shows that the proposed PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and prediction capabilities of model is evaluated and also discussed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.357-362
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• 2002

Most of battery industries are growing explosively as a core strategy industry for the development of the semi-conductor, the LCD, and the mobile communication device. In this thesis, dynamic characteristics of the steel can labeling machine on the automatic cell assembly line are studied. Dynamic characteristic analysis consists of dynamic behavior analysis and finite element analysis and is necessary for effective design of machines. In the dynamic behavior analysis, the displacement, velocity, applied force and angular velocity of each components are simulated according to each part. In the FEA, stress analysis, mode analysis, and frequency analysis are performed for each part. The results of these simulations are used for the design specification investigation and compensation for optimal design of cell manufacturing line. Therefore, Virtual Engineering of the steel can labeling machine on the automatic cell assembly line systems are modeled and simulated. 3D motion behavior is visualized under real-operating condition on the computer window. Virtual Prototype make it possible to save time by identifying design problems early in development, cut cost by reducing making hardware prototype, and improve quality by quickly optimizing full-system performance. As the first step of CAE which integrates design, dynamic modeling using ADAMS and FEM analysis using NASTRAN are developed.

• Journal of Drive and Control
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• v.21 no.2
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• pp.1-7
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• 2024

This paper proposes a novel cooling system for hydrogen fuel cell cooling systems by integrating heat pump technology to enhance operational efficiency. The study analyzed the cooling efficiency of the fuel cell cooling system. With the increasing focus on eco-friendly vehicle technologies to address environmental concerns and global warming, the transportation sector, a major contributor to greenhouse gas emissions, needs technological enhancements for better efficiency. The proposed cooling system was modeled through 1-D simulations. The analysis results of parameters such as thermal balance, temperature, and pressure of each component confirmed the stable operation of the system. By examining variations in the cooling system's flow rate, compressor RPM, and the Coefficient of Performance (COP) based on different refrigerants, initial research was conducted to derive optimal operating conditions and parameter values.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.447-448
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.481-482
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.365-366
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.685-686
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.543-544
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• 2008