• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.482-489
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• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.408-413
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• 2001

The structural optimization is carried out in the continuous design space or discrete design space. Methods for discrete variables such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions for constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.10
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• pp.1621-1626
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• 2001

The structural optimization have been carried out in the continuous design space or in the discrete design space. Methods fur discrete variables such as genetic algorithms , are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete des inn space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions leer constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.611-617
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• 2010

A complex system involves a large number of design variables, and its operation is non-linear. To explore the characteristics in its design space, a Kriging meta-model can be utilized; this model has replaced expensive computational analysis that was performed in traditional parametric design optimization. In this study, a Kriging meta-model with a computational orthogonal array for the design of experiments was developed to optimize the fatigue life of a turbine blade whose behavior under cyclic rotational loads is significantly non-linear. The results not only show that the maximum fatigue life is improved but also indicate that the accuracy of computational analysis is achieved. In addition, the robustness of the results obtained by six-sigma optimization can be verified by comparison with the results obtained by performing Monte Carlo simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1967-1974
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• 2005

The butterfly valve has been used to control a flow effectively in the industrial because of its lightweight, simple structure and the rapidity of its manipulation. However, it is difficult to have the existing structural optimization using field analysis from CFD to structure analysis when the structure is influenced by fluid. This paper is evaluated the specificity to get the flow characteristic and stability of the butterfly valve using FEM and CFD. Also, it accomplished the shape optimization design using the orthogonal arrangement and characteristic function. Research result, a few experiments showed the optimal results of three dimensional structures to be multi-objective.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.9
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• pp.182-194
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• 1999

Occupant injury in rear end impact is rapidly becoming one of the most aggravating traffic safety problems with high human suffering and societal costs. Although rear end impact occurs at relatively low speed , it may cause permanent disability due to neck injuries resulting from an abrupt moment, shear force , and tension/compression force at the occipital condyles. The analysis is performed for a combined occupant-eat model response, using the SAFE(Safety Analysis for occupant crash Environment) computer program. The computational results are verified by those from sled tests. A parameter study is conducted for many physical and mechanical properties. Seat design has been performed based on the design of experiment process with respect to five parameters; seat-back upholstery stiffness, torsional stiffness of the seat-back. An orthogonal array is selected from the parameter study. A good design has been found from the analysis results based on the orthogonal array. The results show that reductions of stiffness in seat-back upholstery and joint are the most effective for preventing neck injuries.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1097-1104
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• 2008

Working condition is one of the most important factors in precision working. In this study, we optimized the vibration acceleration of working progress direction using RSM(response surface methodology) by table of orthogonal array. RSM was well adapted to make analytic model for minimizing vibration acceleration, created the objective function and saved a great deal of computational time. Therefore, it is expected that the proposed optimization procedure using RSM can be easily utilized to solve the optimization problem of working condition. The experimental results of the surface roughness and vibration acceleration showed the validity of the proposed working condition of side wall end-milling as it can be observed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• Journal of Ocean Engineering and Technology
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• v.19 no.3
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• pp.59-65
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• 2005

In today's industry, the butterfly valve has been used to control a flow effectively. However, it is difficult to have the existing structural optimization using field analysis from CFD to structure analysis when the structure is influenced by fluid. Therefore, an initial model of this study is to evaluate the stability of the valve using FEM and CFD. And, it selected variable using initial analysis results. Also, it accomplished the shape optimization design using the orthogonal arrangement and characteristic function. Research result, a few experiments showed the optimal results of there dimensional structures to be multi-objective.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1323-1328
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• 2011

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.