• Proceedings of the KSME Conference
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• 2008.11a
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• pp.603-608
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• 2008

It is well known that the topology optimization for plastic problem is not easy since the iterative analyses to evaluate the objective and cost function with respect to the design variation are very time-consuming. The finite element limit analysis is an efficient tool which is possible to predict collapse modes and sequential collapse loads of a structure considering not only large deformation but also plastic material behavior with moderate computing cost. In this paper, the optimum topology of a structure considering large and plastic deformation is obtained using the finite element limit analysis. To verify the constructed optimization code, topology optimizations of some typical problems are performed and the optimal topologies by elastic design and plastic design are compared.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.84-89
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• 2003

The finite element method (FEM) is typically used in the process of motor design. However, the FEM requires computation time, Therefore, decreasing the number of FEM simulations may also decrease the simulation cost. Several optimal design methods overcoming this problem have been recently studied. This paper investigates the optimal design of the magnet pole of a BLDC motor through reducing simulation cost. The optimization minimizes the magnet volume and limits the average and cogging torques to certain values. In this paper, the response surface methodology and Taguchi's table for reducing the number of FEM simulations are used to approximate two constraints. The optimization result shows that the presented strategy is satisfactorily performed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1429-1433
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• 2008

In this paper, we consider the design method of robust guaranteed cost controller for discrete-time singular systems with norm-bounded time-varying parameter uncertainty. In order to get the optimum(minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) approach. The sufficient condition for the existence of controller and the upper bound of guaranteed cost function are proposed in terms of strict LMIs without decompositions of system matrices. Numerical examples are provided to show the validity of the presented method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.860-867
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• 2015

This paper presents a control method for energy cost saving in the water reuse pumping system. An optimize horizon switching strategy is proposed to implement an pump control. And Particle Swarm Optimization (PSO) algorithm is used to solve optimal problems in each time step. Energy costs are calculated for electricity on both TOU in the light, heavy, and maximum load time period and peak charges. The control method in water reuse pumping systems is determined to reduce the TOU cost. The simulation results show a energy cost saving for water reuse pumping systems.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.62.4-62
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• 2001

In this paper, we propose a delay-dependent guaranteed cost controller design method for uncertain linear systems with time delay. The uncertainty is norm bounded and time-varying. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, sufficient condition, which guarantees that the closed-loop system is asymptotically stable and the upper bound value of the closed-loop cost function is not more than a specied one, is derived in terms of Linear Matrix Inequalities(LMIs) that can be solved sufficiently. A convex optimization problem can be formulated to design a guaranteed cost controller, which minimizes the upper bound value of the cost function. Numerical examples show the activeness of the proposed method.

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.41-46
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• 2015

This paper describes study results on the development of an automatic program for generating surface-panel grid for the aircraft optimal design. The aerodynamic analysis is combined into a PIDO tool in conjunction with a number of programs in order to integrate processes for the optimal design. Due to design optimization's iterative feature, it may require lots of time and cost. To relieve this problem, cost-reduction of computation time for aerodynamic analysis is pursued by using the Panel-method, and reduction of grid generation time by automating surface panelling.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.396-417
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• 2018

GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.438-445
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• 2007

In this paper, we consider the problem of optimum selection of quality-of-service(QoS) classes in interworking between the networks in a next-generation-network(NGN) environment. After introducing the delay-cost and loss-cost characteristics, we discuss the time-invariant(TI) and time-variant(TV) scenarios. For the TI case, we show that under nearly lossless transmission condition, each network can make its own optimization regardless of other networks. For the TV case, we present sufficient conditions under which the optimum QoS class of each network can be considered fixed with respect to time without considerable degradation in the optimization target. Therefore, under the conditions presented in this paper, the QoS of a flow in each network can be determined solely by considering the characteristics of that network and this QoS class can be held fixed during the flow period.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.104-116
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• 2024

A satellite is ultimately verified by performing a coupled load analysis with the launch vehicle. To increase the accuracy of the coupled load analysis results, it is important to have good accuracy of the finite element model. Therefore, finite element model correlation is essential. In general, model correlation is performed by changing the material properties and thickness one by one, but this process takes a lot of time and cost. The current paper proposes an efficient model correlation method using optimization. Significant variables were selected through analysis of variance, and the time and cost required for analysis and optimization were reduced by using the Kriging surrogate model. The method proposed in this paper can be applied only with the vibration test results, and it has a great advantage in terms of efficiency in that it can significantly reduce the numerical calculation cost and time required.