• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.293-297
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• 2021

Calibration of load-resistance factors for the limit state design of front covered caisson breakwaters were presented. Reliability analysis of the breakwaters which are constructed in Korean coast was conducted. Then, partial safety factors and load-resistance factors were sequentially calculated according to target reliability index. Load resistance factors were optimized to give one set of factor for limit state design of breakwater. The breakwaters were redesigned by using the optimal load resistance factor and verified whether reliability indices larger than the target value. Finally, load-resistance factors were compared with foreign country's code for verification.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.476-486
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• 2008

It is very important to design the input filter optimally in matrix converters. But, the input power factor is deteriorated in spite of the optimal filter design due to the existence of inductor and capacitor included in the filter, and it is hard to keep high power factor in the whole operating range which is one of the major advantages of the matrix converters because the power factor is changed according to the output frequency and the load current. In this paper, we introduce the new space vector modulation method which can preserve the input power factor almost unity even though the output load or the output frequency is varied. It is also presented how to implement the proposed method effectively.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.43-48
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• 2010

The performance of photovoltaic systems could be affected by various factors including installing conditions of modules, and their own efficiencies of solar cells and inverters. The installing conditions of a photovoltaic system including array types, tilting angles, azimuth, locations, quantities of sunshine, optimum angles of inclination and separated distance are analyzed using the SolarPro & Minitep SW simulation program, inorder to set up the installing conditions for improving system performance. The result from the simulation of the 500kWp PV system of Kochang with optimal installing conditions compared with normal conditions shows that the capacity factor has been increased from 11.02% to 12.06%.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.694-697
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• 2001

A optimal soft switching technique for A/DC full bridge converter is proposed. variable soft switching single stage AC/DC full bridge converter with unit power factor are presented in this paper. Using soft switching, we can reduce a switching losses. As a result, achieving good power factor and achieving a good efficiency. We search a optimal soft switching technique in this paper and to verify the theoretical analysis of the presented AC/DC full bridge converter, a design example is given with its Pspice and Psim simulation and experimental results.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.613-618
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• 2004

CCS was developed and applied to rotating machines because of accurately measuring the spindle error motion without significant efforts. However, researches on the CCS have been focused on ideal cases where circumferential gaps were ignored. This paper presents the effects of circumferential gaps and proposes an optimal CCS considering the circumferential gaps. First, electrostatic analysis of the CCS that includes the circumferential gaps is performed using the FEM, and an additional capacitance due to the circumferential gap can be approximated as an equivalent extended sensor length. Second, a mathematical model of the CCS considering the circumferential gaps is derived, and the optimal CCS is determined through minimization of the weighted error amplification factor. Finally, two CCSs, both considering and ignoring the circumferential gaps, are built, and the effectiveness of the optimal design is verified through simulation and experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1262-1269
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• 2005

Thrust of linear motor is one of the important factor to specify motor performance. Maximum thrust can be obtained by increasing the current in conductor and is relative to the sizes of conductor and magnet. But, the current and the size of conductor have an effect on temperature of linear motor. Therefore, it is practically important to find design results that can effectively maximize the thrust of linear motor within limited range of temperature. Finite element analysis was applied to calculate thrust and the temperature of the conductor was calculated by the thermal resistance. The diameter of copper wire among design variables has discrete value and number of turns must be integer. Considering these facts, special techinque for optimum design is presented. To reduce excessive computation time of thrust in optimization, the design variables was redefined by analysis of variance and second order regression model for thrust was determined by response surface metheodology. As a result, it is shown that the proposed method has an advantage in optimum design of linear motor.

• Structural Engineering and Mechanics
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• v.61 no.3
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• pp.325-334
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• 2017

In the present study, a numerical model for probability analysis of optimal design of fatigue non-uniform crack growth behaviour of a cracked aluminium 2024 T3 plate repaired with a bonded composite patch is investigated. The proposed 3D numerical model has advanced in literatures, which gathers in a unique study: problems of reliability, optimization, fatigue, cracks and repair of plates subjected to tensile loadings. To achieve this aim, a finite element modelling is carried out to determine the evolution of the stress intensity factor at the crack tip Paris law is used to predict the fatigue life for a give n crack. To have an optimal volume of our patch satisfied the practical fatigue life, a procedure of optimization is proposed. Finally, the probabilistic analysis is performed in order to a show that optimized patch design is influenced by uncertainties related to mechanical and geometrical properties during the manufacturing process.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.483-495
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• 2007

In a general fractional factorial design, the n-levels of a factor are coded by the $n^{th}$ roots of the unity. Pistone and Rogantin (2007) gave a full generalization to mixed-level designs of the theory of the polynomial indicator function using this device. This article discusses the optimal blocking scheme for nonregular designs. According to hierarchical principle, the minimum aberration (MA) has been used as an important criterion for selecting blocked regular fractional factorial designs. MA criterion is mainly based on the defining contrast groups, which only exist for regular designs but not for nonregular designs. Recently, Cheng et al. (2004) adapted the generalized (G)-MA criterion discussed by Tang and Deng (1999) in studying $2^p$ optimal blocking scheme for nonregular factorial designs. The approach is based on the method of replacement by assigning $2^p$ blocks the distinct level combinations in the column with different blocks. However, when blocking level is not a power of two, we have no clue yet in any sense. As an example, suppose we experiment during 3 days for 12-run Plackett-Burman design. How can we arrange the 12-runs into the three blocks? To solve the problem, we apply G-MA criterion to nonregular mixed-level blocked scheme via the mixed-level indicator function and give an answer for the question.