• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.2
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• pp.339-348
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• 1990

Techniques which are able to predict and control dynamic characteristics, not affecting the vibrational characteristics on the modification of structural design, are being studied. As one of these techniques, experimental modal analysis is widely applied by many researchers. In this study, modal analysis is performed using transfer matrix method by a macro computer. The developed program would estimate the structural modal parameters precisely, and the validity of this program is certified by comparing with the experimental results of .GAMMA A. structure. Estimated modal parameters(natural frequency, vibrational mode, equivalent mass, etc.) are in accord with the experimental results. Also, the optimal location of the additive mass is determined by the evaluation of the vibrational mode and the equivalent mass. The relation between the additive mass and the equivalent mass is specified, and we come to know that the ratio of equivalent mass to additive mass alter linearly within the range of 20%.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.184-192
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• 2014

The resistance of a high speed monohull can be dramatically increased at the high speed range due to the severe stern trim, spray formation and hull bottom pressure irregularity etc. In order to avoid these demerits associated with this resistance increase, various appendages such as the stern wedge, vertical wedge, stern flap, spray strip etc. have been studied. Each of appendage can control the trim angle and/or improve the resistance performance. If these appendages are combined for finding the maximal resistance reduction, there are enormous combination selections. This paper presents the DOE(Design of experiment) using an orthogonal array in order to decrease the model tests finding the optimum appendage combination. And we evaluate that the method introduced in this paper makes the optimal combination of appendages efficient and time-saving by applying to high speed semi-planing monohull. Here, the maximum speed and the least fuel expense are adopted as the decision criteria.

• International Journal of Air-Conditioning and Refrigeration
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• v.8 no.2
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• pp.39-50
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• 2000

Thermodynamic cycle analysis is presented to estimate the maximum liquefaction rate of hydrogen for various systems using a Gifford-McMahon(GM) cryocooler. Since the present authors` previous experiments showed that the gaseous hydrogen was liquefied approximately at the rate of 5.1 mg/s from the direct contact with a commercial two-stage GM refrigerator, this study has been proposed to predict how much the liquefaction rate can be increased in different configurations using the GM cooler and with improved heat exchangers. The optimal operating conditions have been analytically sought with real properties of normal hydrogen for the Linde-Hampson(L-H) system precooled by single-stage GM, the direct-contact system with two-stage GM, the L-H system precooled by two-stage GM, and the direct-contact system with helium GM-JT (Joule-Thomson). The maximum liquefaction rate has been predicted to be only about 7 times greater than the previous experiment, even though the highly effective heat exchangers may be employed. It is concluded that the liquefaction rate is limited mainly because of the cooling capacity of the commercially available GM cryocoolers and a practical scale of hydrogen liquefaction is possible only if the GM cooler has a greater capacity at 70-100 K.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• The Journal of Industrial Distribution & Business
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• v.14 no.6
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• pp.17-25
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• 2023

Purpose: This study observes how the consignment performs over time and proposes the proper way to operate the consignment to bring its best benefit to the supply chain system. Research design, data, and methodology: The supply chain system is represented as the mathematical model where a manufacturer and a retailer trade one type of products to maximize their own profits. In the numerical examples of the proposed models, the consignment is compared with the fully coordinated system as well as the traditional system, and both advantages and limitations of the consignment are detected. Results: The consignment makes greater profit than the traditional system after a certain time period. The consignment is still outperformed by the fully coordinated system. The numerical examples also show that the performance of the consignment is sensitive to the consignment ratio. Conclusions: This study finds out that a certain time period must be spent until the consignment brings the benefit to the supply chain system. The numerical outcomes also imply that the consignment requires additional features to be a completely effective supply chain collaboration program. To obtain the best result from the consignment, the supply chain members are recommended to decide the appropriate consignment ratio by consent.

• Membrane Journal
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• v.27 no.4
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• pp.291-312
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• 2017

Seawater desalination is currently considered to be one of the primary technologies to resolve the global water scarcity problem. A basic understanding of membrane filtration phenomena is significant not only for further technological development but also for integrated design, optimal control, and long-term maintenance. In this vein, the present work reviews the major transport and filtration models, specifically related to reverse osmosis phenomena, provides theoretical insights based on statistical mechanics, and discusses model-based physical meanings as related to their practical implications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.699-702
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• 2000

The automation and control of robotic welding process is a very complex assignment because the system is affected by a number of variables which are very difficult to determine or predict in practice. Not only the optimization of the robotic welding process is considered from the point of view of the time and the cost of manufacturing. as well as quality of the weldment. the human factors of the production and many other factors must taken into consideration. hi order to determine the optimal parameters of robotic welding process, it is necessary to build a computer model representing all parameters influencing the welding process as well as the mutual dependence between them. This paper presents an approach to modeling the robotic welding process in which all parameters affecting the welding process are included using a neural network. A detailed analysis of the simulation results has been carried out to evaluate the proposed neural network model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.302-307
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• 2001

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller can be tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.30-36
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• 2016

The battery pack which is a main component of E-scooter needs the cooling system because it is the matter of battery safety in spite of the incresing of charge efficiency due to decress the internal resistence in the condition of high temperature. The purpose of this study is to analyse the effects of cooling methods which is the control of air's inlet and outlet operating timing. When each battery had large temperature deviation in the battery pack, the difference of battery's performance and efficiency were appeared. In this study, the cooling performance of battery pack has been improved by changing the operation timing of inlet and outlet fan, it improved the performance and efficiency of battery. The numerical analysis using a commercial code ANSYS CFX version 17.0 were used for the study.

• Journal of ILASS-Korea
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• v.20 no.1
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• pp.14-19
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• 2015

Recently, R&D demand for environmental friendly vehicle has rapidly increased due to its global environmental issues such as global warming, energy and economic crisis. Under this situation, the most realistic alternative way for environmental friendly vehicle is a clean diesel vehicle. The common-rail fuel injection system, as key technology of clean diesel vehicle, consists of a high pressure pump, common-rail, high pressure fuel line and electronic control injector. In common-rail high-pressure fuel injection system, high pressure wave of injection system and geometry of injector elements have a major effects on high-pressure fuel spray. Therefore, in this study, the numerical model was developed for analysis about the common-rail fuel pressure pulsation by using AMESim code. We could secure stability of common-rail high-pressure fuel injection system through optimal design of fuel line.