• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.1
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• pp.36-43
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• 2015

Optimizing multiple design characteristics which are usually in conflict with each other in the injection molding process is frequently becoming a critical problem for designers who work in this area. The purpose of this work is to develop an automated design methodology for optimizing two such design characteristics found in injection-molded parts. A value function based on decision-making theory is used as a means of evaluating the performance of a two-characteristic design alternative. Also, a design space reduction algorithm based on Taguchi's orthogonal arrays is utilized to discover an optimal design alternative. Verification of the developed design methodology is carried out for an actual model with two design characteristics, the weld line and the gate location, to be optimized in computer simulation experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.463-468
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• 2004

This paper was applied space harmonic method as a characteristic analysis technique for slotless PMLSM. There is advantages of active response to the change of design parameters as well as reduction of the calculation time. The method can be overcome disadvantages of finite element analysis that needs long times calculation, repetitions of pre and post-process. In this paper, 3D-space harmonic method was applied to consider the precise description of end turn coil shape and the changes of characteristic according to changes of length of z-axis direction. The thrust of optimal design was performed using genetic algorithm to enhance the thrust which is the disadvantage of slotless type PMLSM. For design parameters, width of permanent magnet, width of coil, width of coil inner and lengths of z-axis direction were selected. For objective functions. thrust per weight. thrust per volume. multi-objective function was selected.

• Journal of Integrative Natural Science
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• v.3 no.3
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• pp.143-147
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• 2010

Since it is of great importance to know how a ligand binds to a receptor, there have been a lot of efforts to improve the quality of prediction of docking poses. Earlier efforts were focused on improving search algorithm and scoring function in a docking program resulting in a partial improvement with a lot of variations. Although these are basically very important and essential, more tangible improvements came from the reduction of search space. In a normal docking study, the approximate active site is assumed to be known. After defining active site, scoring functions and search algorithms are used to locate the expected binding pose within this search space. A good search algorithm will sample wisely toward the correct binding pose. By careful study of receptor structure, it was possible to prioritize sub-space in the active site using "receptor-based pharmacophores" or "hot spots". In a sense, these techniques reduce the search space from the beginning. Further improvements were made when the bound ligand structure is available, i.e., the searching could be directed by molecular similarity using ligand information. This could be very helpful to increase the accuracy of binding pose. In addition, if the biological activity data is available, docking program could be improved to the level of being useful in affinity prediction for a series of congeneric ligands. Since the number of co-crystal structures is increasing in protein databank, "Ligand-Guided Docking" to reduce the search space would be more important to improve the accuracy of docking pose prediction and the efficiency of virtual screening. Further improvements in this area would be useful to produce more reliable docking programs.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.332-340
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• 2016

A design optimization is performed for the double-bolted joint in cylindrical composite structures by using a simplified analytical method. This method uses failure criteria for the major failure modes of the bolted composite joint. For the double-bolted joint with a zigzag arrangement, it is necessary to consider an interaction effect between the bolt arrays. This paper proposes another failure mode which is determined by angle and distance between two bolts in different arrays and define a failure criterion for the failure mode. The optimal design for the double-bolted joint is carried out by considering the interactive net-tension failure mode. The genetic algorithm (GA) is adopted to determine the optimized parameters; bolt spacing, edge distance, and stacking sequence of the composite laminate. A purpose of the design optimization is to maximize the burst pressure of the cylindrical structures by ensuring structural integrity. Also, a progressive failure analysis (PFA) is performed to verify the results of the optimal design for the double-bolted joint. In PFA, Hashin 3D failure criterion is used to determine the ply that would fail. A stiffness reduction model is then used to reduce the stiffness of the failed ply for the corresponding failure mode.

• Journal of KSNVE
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• v.7 no.2
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• pp.273-279
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• 1997

Reduction of number of actuators for independent modal space control In this paper, a new modified independent modal space control (IMSC), which relaxes the fundamental hardware limitation of IMSC, is suggested to handle the vibration and attitude control problem for flexible large structures. This method has adapted a new switching algorithm between controlled modes and a novel design technique for modal control force. The main advantage of this method is to minimize the discontinuity of the modal control forces and to assure the asymptotic stability of the closed-loop systems. This process is shown to be simple and efficient in a realistic example of vibration control of a cantiloever beam. It has been found that the modified IMSC suggested in this paper, which can reduce the number of actuators, is highly excellent compared to other previous methods in terms of the performance and stability of the vibration control systems.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.451-455
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• 2003

Major concern in modern industry is how to reduce the time and cost for product efficient production. Among many mechanical parts of a satellite, bracket plays an important role to support the load when the satellite is launched to space. so enough strength and stiffness. A designer could add unnecessary material and strength it so as not to fail when it used. But if mechanical part of satellite is over-designed, cost will rise and it also goes against to the aim of lightness. To achieve lightness and enough strength and stiffness, optimization algorithm should be introduced in design process. In this study, conceptual design of bracket is carried out to increase the performance of satellite. Some parameter which could change the weight of this part are selected as design variables. Total weight of bracket is to be minimized while displacement and stress should not exceed limit. Size optimization is done with 3D solid element and PLBA, the RQP algorithm. The weight of 0.262kg of initial model is reduced to 0.241kg after optimization process, so 9.8% of weight reduction is obtained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.973-982
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• 2007

In this paper, optimal design framework is developed by automatic mesh generation and PSO(Particle Swarm Optimization) algorithm based on parallel computing environment and applied to structural optimal design of satellite adapter module. By applying automatic mesh generation, it became possible to change the structural shape of adapter module. PSO algorithm was merged with parallel computing environment and for maximizing a computing performance, asynchronous PSO algorithm was developed and could reduce the computing time of optimization process. As constraint conditions, eigen-frequency and maximum stress was considered. Finally using optimal design framework, weight reduction of satellite adapter module is derived with satisfaction of structural safety.

• International Journal of Fluid Machinery and Systems
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• v.9 no.3
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• pp.265-276
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• 2016

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

• International Journal of Fluid Machinery and Systems
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• v.2 no.1
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• pp.1-12
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• 2009

Surrogate modeling is applied to a compressor blade shape optimization to modify its stacking line and thickness to enhance adiabatic efficiency and total pressure ratio. Six design variables are defined by parametric curves and three objectives; efficiency, total pressure and a combined objective of efficiency and total pressure are considered to enhance the performance of compressor blade. Latin hypercube sampling of design of experiments is used to generate 55 designs within design space constituted by the lower and upper limits of variables. Optimum designs are found by formulating a PRESS (predicted error sum of squares) based averaging (PBA) surrogate model with the help of a gradient based optimization algorithm. The optimum designs using the current variables show that, to optimize the performance of turbomachinery blade, the adiabatic efficiency objective is improved substantially while total pressure ratio objective is increased a very small amount. The multi-objective optimization shows that the efficiency can be increased with the less compensation of total pressure reduction or both objectives can be increased simultaneously.