• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.106-108
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• 1987

Until now, inflow has been handled an independent log-normal random variable in the problem of planning the long-term operation of a multi-reservoir hydrothermal electric power generation system. This paper introduces the detail study for making rule curve by applying weekly time interval for handling inflows. The hydro system model consists of a set of reservoirs and ponds. Thermal units are modeld by one equivalent thermal unit. Objective is minimizing the total cost that the summation of the fuel cost of equivalent thermal unit at each time interval. For optimization, stochastic dynamic programming(SDP) algorithm using successive approximations is used.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.214-216
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• 1999

This paper discussed an optimal designs of 2 pole fan motors in refrigerator using a Niching Algorithm. We applied a Niching method to multi-objective optimal design of air gap construct. This Niching genetic algorithm is called "Restricted Competition Selection"(RCS) that is suitable for real world problem such as shape or structural optimization of electromagnetic device. The finite element method being used for nonlinear numerical characteristic analysis is provided exact solution in the system. Through this process is reduced the cogging torque ripple in air gap.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.525-530
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• 2004

In this paper, the optimum design of tire sidewall contour consisted of double plies for improving automobile maneuverability and tire durability is considered and a GUI program is developed for the purpose of the practical design. Each improvement of maneuverability and durability depends on the cord tension and strain energy distribution of tire sidewall. Satisfing trade-off method, which requires the judgment of aspiration levels, is used for the multi-objective optimization problem. Also, this paper presents the application to the practical sidewall contour design with the GUI program developed using visual Fortran.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Advances in aircraft and spacecraft science
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• v.7 no.5
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• pp.441-458
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• 2020

Rectangular-to-Ellipse Shape Transition (REST) inlets are a class of inward turning inlets designed for hypersonic flight. The aerodynamic design of REST inlets involves very complex flows and shock-wave patterns. These inlets are used in highly integrated propulsive systems. Often the design of these inlets may require many geometrical constraints at different cross-section. In present work a design approach for hypersonic inward-turning inlets, adapted for REST inlets, is coupled with a multi-objective optimization procedure. The automated procedure iterates on the parametric representation and on the numerical solution of a base flow from which the REST inlet is generated by using streamline tracing and shape transition algorithms. The typical design problem of optimizing the total pressure recovery and mass flow capture of the inlet is solved by the proposed procedure. The accuracy of the optimal solutions found is discussed and the performances of the designed REST inlets are investigated by means of fully 3-D Euler and 3-D RANS analyses.

• Particle and aerosol research
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• v.17 no.3
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• pp.71-79
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• 2021

Ultrafine dust, which is emitted from industrial factories or all kinds of vehicles, threatens the human's respiratory system and our environment. In this regard, separating airborne particles is essential to mitigate the severe problem. In this work, an axial cyclone for the effective technology of eliminating harmful dust is investigated by numerical simulation using Ansys 2020, Fluent R2. In addition, the optimized structure of the cyclone is constructed by means of multi objective optimization based on the response surface method which is a representative method to analyze the effect of design parameter on response variables. Among several design parameters, the modified length of the vortex finder and dust collector is a main point in promoting the performance of the axial cyclone. As a result, the optimized cyclone exhibits remarkable performance when compared to the original model, resulting in pressure drop of 307 Pa and separator efficiency of 98.5%.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.253-261
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• 2004

Game theory is mathematical analysis developed to study involved in making decisions. In 1928, Von Neumann proved that every two-person, zero-sum game with finitely many pure strategies for each player is deterministic. As well, in the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Not the rationality but through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) introduced by Maynard Smith. Keeping pace with these game theoretical studies, the first computer simulation of co-evolution was tried out by Hillis in 1991. Moreover, Kauffman proposed NK model to analyze co-evolutionary dynamics between different species. He showed how co-evolutionary phenomenon reaches static states and that these states are Nash equilibrium or ESS introduced in game theory. Since the studies about co-evolutionary phenomenon were started, however many other researchers have developed co-evolutionary algorithms, in this paper we propose Game theory based Co-Evolutionary Algorithm (GCEA) and confirm that this algorithm can be a solution of evolutionary problems by searching the ESS.To evaluate newly designed GCEA approach, we solve several test Multi-objective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by co-evolutionary algorithm and analyze optimization performance of GCEA by comparing experimental results using GCEA with the results using other evolutionary optimization algorithms.

• Smart Structures and Systems
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• v.4 no.5
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• pp.641-653
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• 2008

This paper proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the lifetime performance and the life-cycle cost as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method using the life-cycle costs and the performance of bridges. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence and a corresponding algorithm has been implemented into the program. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.37-43
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• 2002

In this paper, an integrated optimum design method for hybrid structural control system is studied. Not only the distribution and the capacity of passive devices but also those of active devices, and the controllers are treated as design variables in the proposed approach. Multi-objective optimization problem is formulated by using the preference function, which is newly defined in this study. Genetic algorithm is adopted as a numerical searching technique in order to simultaneously find the optimum solutions. The validity of the proposed method is verified through the example designs and the numerical simulations of an earthquake excited multi-degrees-of-freedom structure.