• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.2 s.107
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• pp.115-123
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• 2006

A feasibility of using the topology optimization method for structural damage identification is investigated for the first time. The frequency response functions (FRFs) are assumed to be constructed by the finite element models of damaged and undamaged structures. In addition to commonly used resonances, antiresonances are employed as the damage identifying modal parameters. For the topology optimization formulation, the modal parameters of the undamaged structure are made to approach those of the damaged structure by means of the constraint equations, while the objective function is an explicit penalty function requiring clear black-and-white images. The developed formulation is especially suitable for damage identification problems dealing with many modal parameters. Although relatively simple numerical problems were considered in this investigation, the possibility of using the topology optimization method for structural damage identification is suggested through this research.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.39-74
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• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2207-2212
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• 2008

The next generation of Korean high-speed train under development will be designed for the maximum operating speed of 350km/h and maximum speed of 400km/h. This high-speed operation may cause the noise and vibration problems around tunnel exit due to the higher micro-pressure wave than present level. In this study, the nose shape optimization was conducted for the countermeasure against these problems. Axi-symmetric solver was used for numerical simulation, and response surface was used for efficiency of optimization process. Also the multi-step optimization was conducted to find out more accurate optimal shape. Through these analysis and optimization, it was found out that the optimal nose shapes for minimization of micro-pressure wave are definitely different along the nose length variation. And the mechanism of micro-pressure wave reduction was closely investigated by the analysis of generation process of compression wave in tunnel. The results are expected to be used as design guideline for performance improvement of the next generatin of Korean high-speed train.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1032-1037
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• 2003

Although the holes on the shell case are very important fer the acoustic performance, it is difficult to solve the problem because the case includes thin bodies. Hence, in the past, only the method of trial and error, which depends on the engineer's intuition and experience, was available fur the design of holes. Many researchers have tried to solve the thin-body acoustic problems, since the conventional boundary element method (BEM ) using the Helmholtz integral equation fails to yield a reliable solution fer the numerical modelling of radiation anti scattering of sound from thin bodies. In the area of the analysis of thin-body acoustic problem, three approaches are generally used; the multi-domain BEM, the indirect variational BEM, and the normal derivative integral equation And there has been just a f9w study reported on the design optimization for the acoustic radiation problems by using only the conventional BEM. For the thin-body acoustics, however, no further study in the optimization fields has been reported. In this research, the normal derivative integral equation is adopted as an analysis formulation in the thin-body acoustics, and then used fur the optimization. The analytical approaches for the design of holes are proposed by using a topology optimization technique and a genetic algorithm. The proposed approaches are implemented and validated using numerical examples.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.370-374
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• 2015

Various protective equiptments are used for the power system control and protection. Numerous facilities are monitored at the same time in real time and introduction of optimization method and analysis of the method are required for generation control and facility management considering the demand fluctuations. However, the existing system analysis programs are difficult to link with the other sw and there are some problems with user convenience. To solve these problems the present conditions of the system are figured out in real time and the equipment insert method was estimated by optimization method, and the system that showed the system analysis program is developed. PSS/E has been used as system anlysis program for stabilizing system development which applied the optimization. method and Python language is applied in order to link the input and output values with the DB automatically. Lastly, DLL of matlab has been made included in C++ for solving the objective function using opmization method.By linking this to DB, power flow was calculated in PSS/E and the result was represented by Intouch screen.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.2
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• pp.109-117
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• 2004

Optimization has been successfully applied to systems with a single discipline. As many disciplines are involved in coupled fashion, MDO (multidisciplinary design optimization) technology has been developed. MDO algorithms are trying to solve the coupled aspects generated from interdisciplinary relationship. In a general MDO algorithms, a large design problem is decomposed into small ones which can be easily solved. Although various methods have been proposed for MDO, the research is still in the early stage. This research proposes a new MDO method which is named as MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Many real engineering problems consist of physically separate components and they can be independently designed. The inter-relationship occurs through coupled physics. MDOIS is developed for such problems. In MDOIS, a large system is decomposed into small subsystems. The coupled aspects are solved via system analysis which solves the coupled physics. The algorithm is mathematically validated by showing that the solution satisfies the Karush-Kuhn-Tucker condition.

• Smart Structures and Systems
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• v.18 no.3
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• pp.425-448
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• 2016

In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2840-2851
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• 2022

Electric boilers (EBs) are the backup steam source for the auxiliary steam system of high-temperature gas-cooled reactor nuclear power plants. When the plant is in normal operations, the EB is always in hot standby status. However, the current hot standby operation strategy has problems of slow response, high power consumption, and long operation time. To solve these problems, this study focuses on the optimization of hot standby operations for the EB system. First, mathematical models of an electrode immersion EB and its accompanying deaerator were established. Then, a control simulation platform of the EB system was developed in MATLAB/Simulink implementing the established mathematical models and corresponding control systems. Finally, two optimization strategies for the EB hot standby operation were proposed, followed by dynamic simulations of the EB system transient from hot standby to normal operations. The results indicate that the proposed optimization strategies can significantly speed up the transient response of the EB system from hot standby to normal operations and reduce the power consumption in hot standby operations, improving the dynamic performance and economy of the system.

• Steel and Composite Structures
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• v.45 no.4
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• pp.579-590
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• 2022

One of the biggest problems in structural steel calculation is the design of structures using the lowest possible material weight, making this a slow and costly process. To achieve this objective, several optimization methods have been developed and tested. Nevertheless, a method that performs very efficiently when applied to different problems is not yet available. Based on this assumption, this work proposes a hybrid metaheuristic algorithm for geometric and dimensional optimization of space trusses, called Simulated Squirrel Search Algorithm, which consists of an association of the well-established neighborhood shifting algorithm (Simulated Annealing) with a recently developed promising population algorithm (Squirrel Search Algorithm, or SSA). In this study, two models are tried, being respectively, a classical model from the literature (25-bar space truss) and a roof system composed of space trusses. The structures are subjected to resistance and displacement constraints. A penalty function using Fuzzy Logic (FL) is investigated. Comparative analyses are performed between the Squirrel Search Algorithm (SSSA) and other optimization methods present in the literature. The results obtained indicate that the proposed method can be competitive with other heuristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.