• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.251-258
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• 2006

This study presents an idea of using analogy concept to the heat transfer studies regarding the HTGR development. Theoretical backgrounds regarding the idea were reviewed. In order to investigate the predictability of a mass transfer system for heat transfer system phenomenology, an electroplating system coupled with a limiting current technique was adopted. Test facilities for laminar forced convection and natural convections under laminar and turbulent conditions were constructed, for which heat transfer correlations are known. The test results showed a close agreement between mass transfer and heat transfer systems, which is an encouraging indication of the validity of the analogy theory and the experimental methodology adopted. This paper shows the potential of the experimental method that validates the little-understood heat transfer phenomena, even in complex geometries such as HTGR.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.205-214
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• 2018

The reliability test is a crucial step for ensuring robustness of high-cost and complex weapon systems. In this paper, we present a set of quantitative criteria to select critical parts or components in weapon systems for the reliability test, and implement a fuzzy inference system by applying developed criteria to fuzzy theory. We classify the selection criteria of critical parts or components into four fuzzy sets and membership functions. A fuzzy inference rule is proposed based on the AHP (Analytic Hierarchy Process) analysis technique so as to derive a convincing reliability test. The credibility of the fuzzy inference system is confirmed through a case study using actual equipment data exacted from an existent weapon system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.110-115
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• 1995

In this paper, the problem of non-linear torsional oscillation of a system incorporating a Hooke's joint is studied. Classical perturbation methods including higher order averaging and bifurcation theory are adopted for analysis. The equation of motion derived by Porter[1] is presented and the type of the system is identified. It has been found that two important cases deserve extensive study. Method of higher order averaging which is a main research tool in this study is introduced briefly. The averaged equations are studied analyticallyand numerically and the method of averaging has been found to be effective to study complex non-linear system.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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• pp.105-115
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• 1997

Fuzzy simulation predicts the behaviors of real system based on a model by qualitative reasoning methods and simulates the representation of ambiguous values on the real system variables using the theory of fuzzy sets. During the simulation, however, unnecessary behaviors due to the fuzzy representation are created, and the number of states of system variables changing temporally in the time axis is drastically increased. In this paper, we present a new algorithm which eliminates the spurious behaviors from the great number of result values due to the results of the fuzzy operation, and reduces the number of the states by transforming the complex state transition rules. This paper also shows the easy implementation of the simulation by using the existing package while it is difficult on the PC due to the complexities of the calculation.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1464-1478
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• 2021

Selective Production of Exotic Species is an innovative plant for advanced nuclear physic studies. A radioactive beam, generated by using an UCx target-ion source system, is ionized, selected and accelerated for experimental objects. Very high vacuum conditions and appropriate safety systems to storage exhaust gases are required to avoid radiological risk for operators and people. In this paper, Failure Mode, Effects, and Criticality Analysis of a preliminary design of high activity gas recovery system is performed by using a modified Fuzzy Risk Priority Number to rank the most critical components in terms of failures and human errors. Comparisons between fuzzy approach and classic application allow to show that Fuzzy Risk Priority Number is able to enhance the focus of risk assessments and to improve the safety of complex and innovative systems such as those under consideration.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.114-130
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• 2006

This paper deals with complexity theory to describe amphibious warfare situation using EINSTein (Enhanced ISAAC Neural Simulation Tool) simulation model. EINSTein model is an agent-based artificial "laboratory" for exploring self-organized emergent behavior in land combat. Many studies have shown that existing Lanchester equations used in most war simulation models does not describe changes of combat. Future warfare will be information warfare with various weapon system and complex combat units. We have compared and tested combat results with Lanchester models and EINSTein model. Furthermore, the EINSTein model has been applied and analyzed to amphibious warfare model such as amphibious assault and amphibious sudden attack. The results show that the EINSTein model has a possibility to apply and analyze amphibious warfare more properly than Lanchester models.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.37-45
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• 2004

With the rapid growth of the Web technologies, the Web has changed teaching and learning as well as our life in various ways. Web-based instruction (WBI) supports self-directed and creative learning at anytime anywhere. However, learners may experience the problems of disorientation and cognitive overload when the hyperspace that consists of learning materials is complex. In this paper, we present a Web-based adaptive hypermedia system based on cognitive load theory which can reduce cognitive loads that novices may experience when they learn programming

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.181-187
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• 2015

In this study, an LED emotional lighting algorithm optimized to the situation was implemented using fuzzy inference for users in exercise and resting situations in indoor environment. The fuzzy theory was used instead of the conventional simple color temperature control in order to control the colors and color temperatures of LED light sources in line with user environment under complex conditions. An LED emotional lighting system based on fuzzy theory was designed through a combination of colors according to the color and temperature of emotional language based on the user behavior. As a result, the color and color temperature can give a good effect on user's emotions for an emotional lighting that is effective for resting and exercise.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.131-136
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• 1997

This paper represent the variable structure adaptive mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in contiuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. the sampling process often forces the trajectory to oscillate in the neighborhood of the sliding surface. Adaptive control technique is particularly well-suited to robot manipulators where dynamic model is highly complex and may contain unknown parameters. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple sturcture is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control, Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.