• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.141-147
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• 2019

In this paper, a systematic beam splitter design for multi-beam forming is proposed. The objective of this research is to a design beam splitter that splits and focuses scattering microwaves into intense beams in multiple directions. It is difficult to split multi-beam to non-specific directions with theoretical approaches. Therefore, instead of using transformation optics(TO), which is a widely used process for controlling electromagnetic wave propagation, we used a systematic design process called the phase field design method to obtain an optimal topological structure of beam splitter. The objective function is to maximize the norm of electric field of the target areas of each direction. To avoid island structure and obtain the structure in one body, volume constraint is added to the optimization problem by using augmented Lagrangian. Target frequency is set to X-band 10GHz. The optimal beam splitter performed well in multi-beam forming and the transported electric energy of target areas improved. A frequency dependency test was conducted in the X-band to determine effective frequency range.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4697-4706
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• 2010

This paper suggested the optimal operating design method using simulation and ANP(Analytic Network Process) for mass-customization in the automotive component manufacturing industry. For this, first of all, we built the simulation model including various and complex factors in the field, and estimated the meta-model by RSM(Response Surface Method). Secondly using ANP, we calculated the weight of relative importance of evaluation factors gathered from decision makers. And then, we proposed the optimal operation designs by MOGA(Multi-Objective Genetic Algorithm), analyzed results of them. Moreover, by comparing the results with the consequences using AHP(Analytic Hierarchy Process), we showed its superiority of suggested method to the manner using AHP, because it reflects inner, outer dependency, and inter-relation among judgement factors. In conclusion, through this process, we can present the better way to serve mover effective, precise, and accurate information to decision makers when they build operation design for mass-customization system as automotive parts production system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.852-859
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• 1994

Optmal topology design is to search the optimal layout of the structure which can be used fot the shape of the conceptual design stage. Our objective is to maximize the stiffness of the structure under a material usage constraint. The density of each finite element is the design variable and its relationship with Young's modulus is expressed by quadratic form. The shape is represented by the entire density distribution, the structural analysis is performed by finite element method and the optimization is achieved by feasible direction method. Unlike optimality criteria method,feasible direction method can handle various problems simultaneously, that is, multi- objectives and multi-constraints. Total optimization time can be reduced by the approximation of the material property and fewer design variables than homogenization method. Topology optimization is applied to design the shape of ribs.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.3
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• pp.49-61
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• 2015

We study the problem of multiple response optimization (MRO) and focus on the selection of input levels which will produce desirable output quality. We propose an interactive multiple objective optimization approach to the input design. The earlier interactive methods utilized for MRO communicate with the decision maker only using the response variable values, in order to improve the current response values, thereby resulting in the corresponding design solution automatically. In their interaction steps of preference articulation, no account is taken of any active changes in design variable values. On the contrary, our approach permits the decision maker to change the design variable values in its interaction stage, which makes possible the consideration of the preference or economics of the design variable side. Using some typical value functions, we also demonstrate that our method converges reasonably well to the known optimal solutions.

• Earthquakes and Structures
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• v.7 no.3
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• pp.271-294
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• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1960-1965
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• 2001

In the practical design, it is important to extract the design space information of a complex system in order to optimize the design because the design contains huge amount of design conflicts in general. In this research FEA (finite element analysis) has been successfully implemented and integrated with a statistical approach such as DOE (design of experiments) based RSM (response surface model) to optimize the thermal deformation of an automotive disk brake. The DOE is used for exploring the engineer's design space and for building the RSM in order to facilitate the effective solution of multi-objective optimization problems. The RSM is utilized as an efficient means to rapidly model the trade-off among many conflicting goals existed in the FEA applications. To reduce the computational burden associated with the FEA, the second-order regression models are generated to derive the objective functions and constraints. In this approach, the multiple objective functions and constraints represented by RSM are solved using the sequential quadratic programming to archive the optimal design of disk brake.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.399-404
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• 2002

Analyzing acoustic-structural systems such as automobiles and aircraft the FRF-based substructuring method is one of the most powerful tools. In this paper, an optimization procedure far the engine mount system of passenger car has been presented using the design sensitivity analysis based on the multi-domain FRF-based substructuring formulation. The proposed method is applied to an optimization problem of the engine mount system, of which objective is to minimize the interior sound over the concerned rpm range. The design variables selected are the stiffnesses of the engine mounts and bushes. Plugging the gradient information calculated by the proposed method into nonlinear optimization software, we can obtain the optimal stiffnesses of the engine mounts and bushings through design iterations. The optimized interior noise in the passenger car shows that the proposed method is very useful in the realistic situation.

• Korean Journal of Hydrosciences
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• v.7
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• pp.61-75
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• 1996

The purpose of this study is to develop an efficient model for the least cost design of multi-site detention systems. The IDP (Incremental Dynamic Programming) model for optimal design is composed of two sub-models : hydrologic-hydraulic model and optimization model. The objective function of IDP is the sum of costs ; acquisition cost of the land, construction cost of detention basin and pumping system. Model inputs include channel characteristics, hydrologic parameters, design storm, and cost function. The model is applied to the Jung-Rang Cheon basin in Seoul, a watershed with cetention basins in multiple branching channels. The application results show that the detention system can be designed reasonably for various conditions and the model can be applied to multi-site detention system design.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.124-130
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• 2012

An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.75-82
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• 2019

In a highly urbanized area, land availability is limited for the installation of space consuming stormwater systems for best management practices (BMPs), leading to the consideration of underground stormwater treatment devices connected to the stormwater pipe system. The configuration of a stormwater pipe network determines the hydrological and pollutant transport characteristics of the stormwater discharged through the pipe network, and thus should be an important design consideration for effective management of stormwater quantity and quality. This article presents a multi-objective optimization approach for designing a stormwater pipe network with on-line stormwater treatment devices to achieve an optimal trade-off between the total installation cost and the annual removal efficiency of total suspended solids (TSS). The Non-dominated Sorted Genetic Algorithm-II (NSGA-II) was adapted to solve the multi-objective optimization problem. The study site used to demonstrate the developed approach was a commercial area that has an existing pipe network with eight outfalls into an adjacent stream in Yongin City, South Korea. The stormwater management model (SWMM) was calibrated based on the data obtained from a subcatchment within the study area and was further used to simulate the flow rates and TSS discharge rates through a given pipe network for the entire study area. In the simulation, an underground stormwater treatment device was assumed to be installed at each outfall and sized proportional to the average flow rate at the outfall. The total installation cost for the pipes and underground devices was estimated based on empirical formulas using the flow rates and TSS discharge rates simulated by the SWMM. In the demonstration example, the installation cost could be reduced by up to 9% while the annual TSS removal efficiency could be increased by 4% compared to the original pipe network configuration. The annual TSS removal efficiency was relatively insensitive to the total installation cost in the Pareto-optimal solutions of the pipe network design. The results suggested that the installation cost of the pipes and stormwater treatment devices can be substantially reduced without significantly compromising the pollutant removal efficiency when the pipe network is optimally designed.