• 전기의세계
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• 제24권5호
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• pp.72-80
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• 1975

In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2007년도 학술대회
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• pp.407-410
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• 2007

In the RRH (Radio Remote Head) of a WCDMA Node B System, an HPA (High Power Amplifier) is used in order to amplify the transmission RF signal. Upon designing an HPA, the design requirements demand that the intermodulation characteristics are optimized during design and that the stability of the characteristics is maintained in the field. In this DOE (Design of Experiments) research, a few vital factors that affect intermodulation characteristics were first selected; then, an optimal solution was produced for high reliability in a noisy environment in the field by employing the Taguchi Method, a statistical method used for a robust design. Furthermore, by employing HALT(High Accelerated Life Test) during the verification test, this experiment has verified that an HPA that was designed using the Taguchi Method proved to be a far more robust design than an HPA that was designed without using the method.

• Structural Engineering and Mechanics
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• 제56권4호
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• pp.549-567
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• 2015

A first-order moment method (FORM) reliability analysis is commonly used for structural stability analysis. It requires the values and partial derivatives of the performance to function with respect to the random variables for the design. These calculations can be cumbersome when the performance functions are implicit. A Gaussian process (GP)-based response surface is adopted in this study to approximate the limit state function. By using a trained GP model, a large number of values and partial derivatives of the performance functions can be obtained for conventional reliability analysis with a FORM, thereby reducing the number of stability analysis calculations. This dynamic renewed knowledge source can provide great assistance in improving the predictive capacity of GP during the iterative process, particularly from the view of machine learning. An iterative algorithm is therefore proposed to improve the precision of GP approximation around the design point by constantly adding new design points to the initial training set. Examples are provided to illustrate the GP-based response surface for both structural and non-structural reliability analyses. The results show that the proposed approach is applicable to structural reliability analyses that involve implicit performance functions and structural response evaluations that entail time-consuming finite element analyses.

• 한국신뢰성학회지:신뢰성응용연구
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• 제12권2호
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• pp.105-119
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• 2012

In this paper, we have proposed a methodology which can make effective test for system integration of complex guided missile system. System integration test play a significant role in the development of weapon system, providing the means to detect and isolate faults on first linkage between sub-systems. Integration tests for domestic weapon system has executed not a technology-intensive method based on tool but labor-intensive method based on experience. Higher cost, longer period, and more resource are required to execute system integration test for complex guided missile system comparing with past weapon systems, because recently weapon systems have more complex and more networked functions. Because the proposed design method for system integration test decreases number of test case, it lead to a decrease of cost, period, and resource for integration test of weapon system. The proposed configuration for system integration test will ensure reliability through detection and isolation of fault on linkage between sub-systems.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권1호
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• pp.49-55
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• 2018

Purpose: To propose improved method for normalization, compare to the de facto international standard which is IESNA TM-21 or conventional normalization methods. Methods: Firstly, we analysed conventional methods and specified the problem of normalization method which is based on first measured data. Secondly, we proposed our approach which is based on the design specification. Lastly, we studied a real degradation data which is conducted for 15,000 hours. Conclusion: Proposed normalization method is better approach because it can reflect real data and design specification, and reduce distortion when analysing degradation data. Also, It is appliable to other long-life reliability items.

• Geomechanics and Engineering
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• 제12권2호
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• pp.313-326
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• 2017

Based on the reliability theory and limit analysis method, the roof stability of a shallow tunnel is investigated under the condition of surface settlement. Nonlinear Hoek-Brown failure criterion is adopted in the present analysis. With the consideration of surface settlement, the internal energy and external work are calculated. Equating the rate of energy dissipation to the external rate of work, the expression of support pressure is derived. With the help of variational approach, a performance function is proposed to reliability analysis. Improved response surface method is used to calculate the Hasofer-Lind reliability index and the failure probability. In order to assess the validity of the present results, Monte-Carlo simulation is performed to examine the correctness. Sensitivity analysis is used to estimate the influence of different variables on reliability index. Among random variables, the unit weight significantly affects the reliability index. It is found that the greater coefficient of variation of variables lead to the higher failure probability. On the basis of the discussions, the reliability-based design is achieved to calculate the required tunnel support pressure under different situations when the target reliability index is obtained.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2028-2030
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• 2003

This paper describes the results of reliability prediction analysis of control rod control system, which is being developed as part of KNICS project. The results of reliability prediction indicate MTBF(Mean Time Between Failure) of cards for control rod control system. A purpose of reliability prediction is to evaluate MTBF of cards, identify the design drawbacks of cards, and propose design improvement to a designer to help design the more reliable control rod control system. This reliability prediction analysis used the the part count and part stress method in the basis of MIL-HDBK-217F.

• 한국항공우주학회지
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• 제44권2호
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• pp.181-188
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• 2016

액체로켓 엔진의 신뢰도는 설계 추력, 추진제, 연소 사이클, 및 연소시험 시간의 영향을 받는다. 기존 연구에 따르면 신규 개발하는 엔진과 같은 추진제 및 연소 사이클을 가지는 참조 엔진들의 연소시험 자료가 알려져 있다면 참조 엔진들의 설계 추력과 연소시험 시간을 보정하여 신규 엔진의 신뢰도를 예측할 수 있다. 본 연구에서는 신규 개발하는 엔진과 같은 추진제 및 연소 사이클을 가지는 참조 엔진의 자료가 존재하지 않은 경우를 고려하여 두 엔진 사이의 유사성 분석을 통하여 고장률을 보정한 후 신뢰도를 예측하는 방법을 제시하였다. 또한 액체산소/케로신 추진제와 가스 발생기 사이클을 사용하는 한국형 발사체의 1단 엔진을 이용하여 제안된 방법을 예시하였다.

• 한국생산제조학회지
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• 제19권5호
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• pp.589-595
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

• 한국안전학회지
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• 제27권5호
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• pp.148-157
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• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.