• 한국항공우주학회지
• /
• 제34권8호
• /
• pp.24-32
• /
• 2006

결정론적인 최적 설계 방법을 이용하는 경우 불확실성의 영향으로 인하여 제약조건의 위반이나 목표 성능의 저하를 초래할 수 있다. 이러한 까닭에 불확실성하에서 제약 조건에 대한 신뢰성을 보장하고 목적함수의 강건성을 확보하는 설계가 필요하다. 그러므로 본 연구에서는 강건성과 신뢰성을 평가하기 위하여 Monte Carlo Simulation(MCS)을 이용하였으며, 계산 효율의 증가를 위하여 MCS에 적합한 근사모델을 선정하는 과정을 거쳐 신경망 모델을 채택하게 되었다. 이를 공력-구조가 연동된 항공기 날개 설계 문제에 적용하여 봄으로써 그 가능성을 타진하였다. 불확실성을 고려한 최적 설계를 수행한 결과 요구되는 신뢰도 수준을 만족시키면서 baseline보다 강건한 최적해를 탐색하는 것이 가능하였다.

• Journal of Magnetics
• /
• 제19권1호
• /
• pp.78-83
• /
• 2014

This paper proposes an efficient reliability-based optimization method for designing a superconducting magnetic energy system in presence of uncertainty. To evaluate the probability of failure of constraints, samplingbased reliability analysis method is employed, where Monte Carlo simulation is incorporated into dynamic Kriging models. Its main feature is to drastically reduce the numbers of iterative designs and computer simulations during the optimization process without sacrificing the accuracy of reliability analysis. Through comparison with existing methods, the validity of the proposed method is examined with the TEAM Workshop Problem 22.

• 품질경영학회지
• /
• 제23권4호
• /
• pp.148-156
• /
• 1995

많은 Buyer들이 품질의 기본조건으로 요구하는 완제품 Burn-in 시간은 실제 필요 이상으로 긴 시간일 수 있으며 생산자 입장에서 Cost, Delivery, Capacity 등의 제약으로 이행하기 어려운 경우가 종종 있다. 본 연구는 생산자에게 실무적으로 적용이 용이하고 Buyer에게 설득력있는 최적 Burn-in 시간 근거를 제시할 수 있도록, 구간개념과 Curve Fitting 방법을 적용하여 최적 Burn-in 시간을 추정하고 시간대별 Reliability를 산출 비교해 봄으로서 생산자 입장에서 Burn-in 시간을 결정하고 Reliability 추정 Model을 결정해 갈 수 있도록 하였다. 향후 제시된 Burn-in 시간의 최적여부는 Field Data로부터 검증되어야 할 것이다.

• Structural Engineering and Mechanics
• /
• 제70권1호
• /
• pp.81-96
• /
• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

• 한국공작기계학회논문집
• /
• 제16권4호
• /
• pp.36-44
• /
• 2007

This paper is focused on the optimum design for decreasing volume and increasing reliability of multi-stage gear drive. For the optimization on volume and reliability, multi-objective optimization is used. The genetic algorithm is introduced to multi-objective optimization method and it is used to develop the optimum design program using exterior penalty function method to solve the complicated subject conditions. A 5 staged gear drive(geared motor) is chosen to compare the result of developed optimum design method with the existing design. Each of the volume objective, reliability objective, and volume-reliability multi-objectives are performed and compared with existing design. As a result, optimum solutions are produced, which decrease volume and increase reliability. It is shown that the developed design method is good for multi-stage gear drive design.

• Structural Engineering and Mechanics
• /
• 제62권2호
• /
• pp.125-138
• /
• 2017

Reliability-based design optimization (RBDO) is a powerful tool for design optimization when considering probabilistic characteristics of design variables. However, it is often computationally intensive because of the coupling of reliability analysis and cost minimization. In this study, the concept of reliability mapping function is defined based on the relationship between the reliability index obtained by using the mean value first order reliability method and the failure probability obtained by using an improved response surface method. Double-loop involved in the classical RBDO can be converted into single-loop by using the reliability mapping function. Since the computational effort of the mean value first order reliability method is minimal, RBDO by using reliability mapping functions should be highly efficient. Engineering examples are given to demonstrate the efficiency and accuracy of the proposed method. Numerical results indicated that the proposed method has the similar accuracy as Monte Carlo simulation, and it can obviously reduce the computational effort.

• 대한기계학회논문집A
• /
• 제31권1호
• /
• pp.113-120
• /
• 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.

• 한국가스학회지
• /
• 제6권1호
• /
• pp.86-91
• /
• 2002

본 연구에서는 장치가 가지고 있는 신뢰도 데이터와 가격을 고려하여 공정에서 요구하는 신뢰도에 도달할 수 있도록 최적화 분석을 수행하여 어떠한 장치를 선택하는가에 대한 방법을 제시하였다. 이산함수를 이용한 목적함수와 제한 조건을 이용하여 보다 실질적인 최적화 문제를 구성하였다. 재? 반응기를 대상으로 하여 시스템에서 요구하는 신뢰도 목표 값에 도달하기 위해 가격에 따라 다른 고장률을 가지는 장치에 대하여 최적화 분석을 수행하였다. 이러한 최적화 분석을 수행하기 위해 mixed-integer programming(MIP) 방법을 사용하였다. 재? 반응기의 신뢰도 목표값이 $1.65{\times}10^{-04}$일 경우에 최적화 분석 수행결과는 가격과 고장률이 모두 좋은 장치로 분석되었다. 그러나 신뢰도 목표값이 낮을 경우 최적화 분석의 수행결과는 비싼 장치의 선택보다 가격과 신뢰도가 낮은 장치를 선택함으로써 원하는 신뢰도 목표값에 도달할 수 있었다.

• International Journal of Automotive Technology
• /
• 제8권6호
• /
• pp.713-722
• /
• 2007

Design variables for suspension systems cannot always be realized in the actual suspension systems due to tolerances in manufacturing and assembly processes. In order to deal with these tolerances, design variables associated with kinematic configuration and compliance characteristics of suspensions are treated as random variables. The reliability of a design target with respect to a design variable is defined as the probability that the design target is in the acceptable design range for all possible values of the design variable. To compute reliability, the limit state, which is the boundary between the acceptable and unacceptable design, is expressed mathematically by a limit state function with value greater than 0 for acceptable design, and less than 0 for unacceptable design. Through reliability analysis, the acceptable range of design variables that satisfy a reliability target is specified. Furthermore, through sensitivity analysis, a general procedure for optimization of the design target with respect to the design variables has been established.

• Structural Engineering and Mechanics
• /
• 제32권1호
• /
• pp.127-145
• /
• 2009

A novel approach is proposed to effectively estimate the quantile functions of normalized performance indices of reliability constraints in a reliability-based optimization (RBO) problem. These quantile functions are not only estimated as functions of exceedance probabilities but also as functions of the design variables of the target RBO problem. Once these quantile functions are obtained, all reliability constraints in the target RBO problem can be transformed into non-probabilistic ordinary ones, and the RBO problem can be solved as if it is an ordinary optimization problem. Two numerical examples are investigated to verify the proposed novel approach. The results show that the approach may be capable of finding approximate solutions that are close to the actual solution of the target RBO problem.