• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.721-733
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• 2022

In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.113-120
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• 2007

Design optimization of layered plates bonding process is conducted by considering uncertainties in a manufacturing process, in order to reduce the crack failure arising due to the residual stress at the surface of the adherent which is caused by different thermal expansion coefficients. Robust optimization is peformed to minimize the mean as well as its variance of the residual stress, while constraining the distortion as well as the instantaneous maximum stress under the allowable reliability limits. In this optimization, the dimension reduction (DR) method is employed to quantify the reliability such as mean and variance of the layered plate bonding. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. The obtained robust optimal solution is verified by the Monte Carlo simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1051-1058
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• 2011

The military communication equipment is required the high reliability for operating adequate functions under severe conditions. This reliability is the essential element for the quality of the product, for the uncontrolled factors, such as the clearance, damage of the material, the reduction of stiffness, which are the designer is unable to handle. In this paper, the uncertainty for the dimension was supposed to the probability model for the military communication equipment, and the average of the objective function was minimized for reducing design uncertainty. The reliability-based design optimization which was implemented the limit state function was formulated into the mathematical model, so the reliable optimized structure was implemented than the base-line design.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.823-826
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• 2001

A shape optimization of a rib of a bolster of a bogie frame is attempted and a dimension optimization on upper and lower plates is also carried out for the reduction of the weight of bogie frame. In addition, the dynamic characteristics of the weight reduced model are investigated by an analysis of a natural frequency and a transient analysis. The results show that the first natural frequency of an optimized model is larger than that of the lowest design value. And the results of transit analysis based on the experimental stress also show smaller value than the yield stress. Thus the optimized model attempted in this study is considered to be structurally stable and useful for the improvement of railway carriages.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.836-840
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• 2006

Design optimization of layered plates bonding process is conducted to achieve high product quality by considering uncertainties in a manufacturing process. During the cooling process of the sequential sub-processes, different thermal expansion coefficients lead to residual stress and displacement. thus resulting in defects on the surface of the adherent. So robust process optimization is performed to minimize the residual stress mean and variation of the assembly while constraining the distortion as well as the instantaneous maximum stress to the allowable limits. In robust process optimization, the dimension reduction (DR) method is employed to quantify both reliability and quality of the layered plate bonding. Using this method. the average and standard deviation is estimated. Response surface is constructed using the statistical data obtained by the DRM for robust objectives and constraints. from which the optimum solution is obtained.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.529-540
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• 2020

Concurrent topology optimization of macrostructure and microstructure has attracted significant interest due to its high structural performance. However, most of the existing works are carried out under deterministic conditions, the obtained design may be vulnerable or even cause catastrophic failure when the load position exists uncertainty. Therefore, it is necessary to take load position uncertainty into consideration in structural design. This paper presents a computational method for robust concurrent topology optimization with consideration of load position uncertainty. The weighted sum of the mean and standard deviation of the structural compliance is defined as the objective function with constraints are imposed to both macro- and micro-scale structure volume fractions. The Bivariate Dimension Reduction method and Gauss-type quadrature (BDRGQ) are used to quantify and propagate load uncertainty to calculate the objective function. The effective properties of microstructure are evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The bi-directional evolutionary structural optimization (BESO) method is used to obtain the black-and-white designs. Several 2D and 3D examples are presented to validate the effectiveness of the proposed robust concurrent topology optimization method.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.17 no.4
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• pp.408-417
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• 1988

This study optimized the condenser dimension of heat pump system with the heat sources which are solar irradiation and ambient air. At first, the author selected the principal design factors influencing the performance of heat pump system. And the author considered the variation of condenser dimension according to the variation of the selected design factors, that is, ambient air temperature, condenser temperature, degree of superheating, degree of sub-cooling and irradiation. As a result this study, among refrigerants R12, R22 and R500, refrigerant R22 has more heating output than R12 and R500, and the coefficient of performance on this heat pump system is not greatly influenced by the degree of superheating and degree of sub cooling. The ambient air temperature is below $5^{\circ}C$ at balance point and the optimal tube length of condenser dimension is about 3.8 m. Also the author gained the optimal design diagram for the optimization of condenser dimension according to various design factors.

• Computers and Concrete
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• v.26 no.6
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• pp.505-513
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• 2020

Grading of aggregate influences significantly almost all of the concrete performances. The purpose of this paper is to propose practicable equations that express the optimized total aggregate gradation, by weight or by number of particles in a concrete mix. The principle is based on the fractal feature of the grading of combined aggregate in a solid skeleton of concrete. Therefore, equations are derived based on the so-called fractal dimension of the grain size distribution of aggregates. Obtained model was then applied in such a way a correlation between some properties of the dry concrete mix and the fractal dimension of the aggregate gradation has been built. This demonstrates that the parameter fractal dimension is an efficacious tool to establish a unified model to study the solid phase of concrete in order to design aggregate gradation to meet certain requirements or even to predict some characteristics of the dry concrete mixture.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.19-26
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• 2010

This study was conducted to find out the reasonable optimum design method of agricultural reinforced concrete structures. Selected design variables are the dimension of concrete section, reinforced steel area, and objective function is formulated by cost function. To test the reliability, efficiency, possibility of application and reasonability of optimum design method, both continuous optimization method and mixed-discrete optimization method were applied to the design of reinforced concrete superstructure of aqueduct and application results were discussed. It is proved that mixed-discrete optimization method is more reliable, efficient and reasonable than continuous optimization method for the optimum design of reinforced concrete agricultural structures.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.66-72
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• 2011

Injection pressure is an important factor in filling procedure for injection molded parts. In addition, weldlines should be avoided to successfully produce injection molded parts. In this study, we optimally obtained injection molding process parameters that minimize injection pressure. Then, we determined the thickness of the part to avoid weldlines. To solve the optimization problem proposed, we employed MAPS-3D (Mold Analysis and Plastics Solution-3 Dimension), a commercial CAE tool for injection molding analysis, and PIAnO (Process Integration, Automation, and Optimization) as a commercial PIDO (Process Integration and Design Optimization) tool. We integrated MAPS-3D into PIAnO, automated the analysis and design procedure, and performed optimization by employing PQRSM (Progressive Quadratic Response Surface Method) equipped in PIAnO. We successfully obtained optimization results, which demonstrates the effectiveness of our design method.