• Title/Summary/Keyword: 신뢰성 최적설계

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Reliability-Based Design Optimization Considering Variable Uncertainty (설계변수의 변동 불확실성을 고려한 신뢰성 기반 최적설계)

  • Lim, Woochul;Jang, Junyong;Kim, Jungho;Na, Jongho;Lee, Changkun;Kim, Yongsuk;Lee, Tae Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.6
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    • pp.649-653
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    • 2014
  • Although many reliability analysis and reliability-based design optimization (RBDO) methods have been developed to estimate system reliability, many studies assume the uncertainty of the design variable to be constant. In practice, because uncertainty varies with the design variable's value, this assumption results in inaccurate conclusions about the reliability of the optimum design. Therefore, uncertainty should be considered variable in RBDO. In this paper, we propose an RBDO method considering variable uncertainty. Variable uncertainty can modify uncertainty for each design point, resulting in accurate reliability estimation. Finally, a notable optimum design is obtained using the proposed method with variable uncertainty. A mathematical example and an engine cradle design are illustrated to verify the proposed method.

Reliability-based Design Optimization using MD method (곱분해기법을 적용한 신뢰성 기반 최적 설계)

  • Lee, Tae-Hee;Kim, Tae-Kyun
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2009.04a
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    • pp.101-104
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    • 2009
  • 최적설계는 설계자가 요구하는 제한조건을 만족시키는 범위에서 목적함수가 최소가 되는 설계점을 찾는 방법이다. 그러나 기존의 최적설계는 불확실성의 영향을 고려하지 않아 최적해가 제한조건의 경계에 위치하고 이것은 모델링과정이나 가공 등으로 인한 오차에 대한 영향을 고려하지 않는 문제점이 있다. 신뢰성 기반 최적설계는 불확실성을 정량화하면서 신뢰도를 계산하는 신뢰도 해석과정과 최적설계과정을 포함한다. 일반적으로 신뢰성 해석은 크게 추출법, 급속 확률 적분법, 모멘트 기반 신뢰성해석이 있다. 가장 널리 사용되는 급속 확률 적분법 중 최대 손상 가능점(MPP) 방법은 많은 MPP점이 존재하는 경우 수치적 비용이 증가하는 문제점과 표준 정규분포 공간으로 변환하는 과정에서 제한조건의 비선형성을 증가시켜 큰 오차를 발생시키는 문제점이 있다. 본 논문에서는 RBDO를 수행하기에 앞서 선행되어야 할 신뢰성해석 방법으로 곱분해기법을 사용하였고 이로부터 민감도 정보를 유도하여 기울기 기반 최적화 알고리즘을 적용하였다.

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Reliability Based Design Optimization with Variation of Standard Deviation (표준편차의 변동을 고려한 신뢰성 최적설계)

  • Lim, O-Kaung;Kim, Hyung-Wook;Choi, Eun-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.5
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    • pp.413-419
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    • 2008
  • Deterministic design optimization (DO) does not explicitly deal with a variety of factors from inherent randomness and uncertainties. Reliability based design optimization(RBDO) is necessary to use in engineering systems in order to guarantee quality and performance of product. In this paper, design variables are considered as random variables. Standard deviation according to change of design variables have changed as much as coefficient of variation. And, if the standard deviation is error of manufacturing, standard deviation-mean relation is concave form. We obtain reliability index using advanced first order second moment method(AFOSM). This paper is examined by solving two examples and the results are compares with DO, RBDO and suggested RBDO.

Reliability Based Design Optimization for the Pressure Recovery of Supersonic Double-Wedge Inlet (이중 쐐기형 초음속 흡입구의 압력회복률에 대한 신뢰성 기반 최적설계)

  • Lee, Chang-Hyuck;Ahn, Joong-Ki;Bae, Hyo-Gil;Kwon, Jang-Hyuk
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.11
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    • pp.1067-1074
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    • 2010
  • In this study, RBDO(Reliability Based Design Optimization) was performed for a supersonic double-wedge inlet. By considering uncertainty of design with given design space, the pressure recovery was transformed into the probabilistic constraint while the inlet drag was considered as a deterministic objective function. To save computational analysis cost and to search good design space, Latin-Hypercube design of experiment and the Kriging model were incorporated and then RBDO was performed. Monte-Carlo simulation was performed to verify the accuracy of AFORM(Advanced First Order Reliability Method). It was found that AFORM result agreed very well with the Monte-Carlo simulation result. The system reliability was guaranteed by considering uncertainty of the design variables. In case of considering diverse uncertainty of system design, RBDO was found to be useful.

System Reliability-Based Design Optimization Using Performance Measure Approach (성능치 접근법을 이용한 시스템 신뢰도 기반 최적설계)

  • Kang, Soo-Chang;Koh, Hyun-Moo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.193-200
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    • 2010
  • Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

Reliability-based Design Optimization using Multiplicative Decomposition Method (곱분해기법을 이용한 신뢰성 기반 최적설계)

  • Kim, Tae-Kyun;Lee, Tae-Hee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.22 no.4
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    • pp.299-306
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    • 2009
  • Design optimization is a method to find optimum point which minimizes the objective function while satisfying design constraints. The conventional optimization does not consider the uncertainty originated from modeling or manufacturing process, so optimum point often locates on the boundaries of constraints. Reliability based design optimization includes optimization technique and reliability analysis that calculates the reliability of the system. Reliability analysis can be classified into simulation method, fast probability integration method, and moment-based reliability method. In most generally used MPP based reliability analysis, which is one of fast probability integration method, if many MPP points exist, cost and numerical error can increase in the process of transforming constraints into standard normal distribution space. In this paper, multiplicative decomposition method is used as a reliability analysis for RBDO, and sensitivity analysis is performed to apply gradient based optimization algorithm. To illustrate whole process of RBDO mathematical and engineering examples are illustrated.

Reliability-Based Design Optimization of 130m Class Fixed-Type Offshore Platform (신뢰성 기반 최적설계를 이용한 130m급 고정식 해양구조물 최적설계 개발)

  • Kim, Hyun-Seok;Kim, Hyun-Sung;Park, Byoungjae;Lee, Kangsu
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.5
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    • pp.263-270
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    • 2021
  • In this study, a reliability-based design optimization of a 130-m class fixed-type offshore platform, to be installed in the North Sea, was carried out, while considering environmental, material, and manufacturing uncertainties to enhance its structural safety and economic aspects. For the reliability analysis, and reliability-based design optimization of the structural integrity, unity check values (defined as the ratio between working and allowable stress, for axial, bending, and shear stresses), of the members of the offshore platform were considered as constraints. Weight of the supporting jacket structure was minimized to reduce the manufacturing cost of the offshore platform. Statistical characteristics of uncertainties were defined based on observed and measured data references. Reliability analysis and reliability-based design optimization of a jacket-type offshore structure were computationally burdensome due to the large number of members; therefore, we suggested a method for variable screening, based on the importance of their output responses, to reduce the dimension of the problem. Furthermore, a deterministic design optimization was carried out prior to the reliability-based design optimization, to improve overall computational efficiency. Finally, the optimal design obtained was compared with the conventional rule-based offshore platform design in terms of safety and cost.

Reliability-Based Design Optimization Using Akaike Information Criterion for Discrete Information (이산정보의 아카이케 정보척도를 이용한 신뢰성 기반 최적설계)

  • Lim, Woo-Chul;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.8
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    • pp.921-927
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    • 2012
  • Reliability-based design optimization (RBDO) can be used to determine the reliability of a system by means of probabilistic design criteria, i.e., the possibility of failure considering stochastic features of design variables and input parameters. To assure these criteria, various reliability analysis methods have been developed. Most of these methods assume that distribution functions are continuous. However, in real problems, because real data is often discrete in form, it is important to estimate the distributions for discrete information during reliability analysis. In this study, we employ the Akaike information criterion (AIC) method for reliability analysis to determine the best estimated distribution for discrete information and we suggest an RBDO method using AIC. Mathematical and engineering examples are illustrated to verify the proposed method.

Reliability Based Design Optimization using Moving Least Squares (이동최소자승법을 이용한 신뢰성 최적설계)

  • Park, Jang-Won;Lee, Oh-Young;Im, Jong-Bin;Lee, Soo-Yong;Park, Jung-Sun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.5
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    • pp.438-447
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    • 2008
  • This study is focused on reliability based design optimization (RBDO) using moving least squares. A response surface is used to derive a limit-state equation for reliability based design optimization. Response surface method (RSM) with least square method (LSM) or Kriging will be used as a response surface. RSM is fast to make the response surface. On the other hand, RSM has disadvantage to make the response surface of nonlinear equation. Kriging can make the response surface in nonlinear equation precisely but needs considerable amount of computations. The moving least square method (MLSM) is made of both methods (RSM with LSM+Kriging). Numerical results by MLSM are compared with those by LMS in Rosenbrock function and six-hump carmel back function. The RBDO of engine duct of smart UAV is pursued in this paper. It is proved that RBDO is useful tool for aerospace structural optimal design problems.

신뢰성 기반 최적설계 및 적용사례

  • Lee, Ik-Jin
    • Journal of the KSME
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    • v.54 no.2
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    • pp.28-34
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    • 2014
  • 이 글에서는 신뢰성 기반 최적설계(RBDO: Reliability-Based Design Optimization)의 필요성을 설명하고, RBDO를 위해 필요한 기술을 소개하며, RBDO기술이 산업계에 적용되는 사례연구를 통해 기술적 어려움과 향후 연구방향을 제시하고자 한다.

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