• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1195-1201
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• 2009

In this study, effective methods for reliability estimation and reliability-based design optimization(RBDO) are proposed using kriging metamodel and genetic algorithm. In our previous study, we proposed the accurate method for reliability estimation using two-staged kriging metamodel and genetic algorithm. In this study, the possibility of applying the previously proposed method to RBDO is investigated. The efficiency and accuracy of that method were much improved than those of the first order reliability method(FORM). Finally, the effective method for RBDO is proposed and applied to numerical examples. The results are compared to the existing RBDO methods and shown to be very effective and accurate.

• 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.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.369-379
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• 2023

Reliability-Based Design Optimization (RBDO) is an appropriate framework for obtaining optimal designs by taking uncertainties into account. Large-scale problems with implicit limit state functions and problems with discrete design variables are two significant challenges to traditional RBDO methods. To overcome these challenges, this paper proposes a hybrid method to perform RBDO of structures that links Firefly Algorithm (FA) as an optimization tool to advanced (finite element) reliability methods. Furthermore, the Genetic Algorithm (GA) and the FA are compared based on the design cost (objective function) they achieve. In the proposed method, Weighted Simulation Method (WSM) is utilized to assess reliability constraints in the RBDO problems with explicit limit state functions. WSM is selected to reduce computational costs. To performing RBDO of structures with finite element modeling and implicit limit state functions, a First-Order Reliability Method (FORM) based on the Direct Differentiation Method (DDM) is utilized. Four numerical examples are considered to assess the effectiveness of the proposed method. The findings illustrate that the proposed RBDO method is applicable and efficient for RBDO problems with discrete and continuous design variables and finite element modeling.

• Composites Research
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• v.26 no.1
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• pp.29-35
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• 2013

Composite sandwich structure can improve the specific bending stiffness significantly and save the weight nearly 30 percent compared with the composite laminates. However, it has more inherent uncertainties of the material property caused by manufacturing process than metals. Therefore, the reliability-based probabilistic design approach is required. In this paper, the PMS(Probabilistic Margin of Safety) is calculated for the simplified fuselage structure made of composite sandwich to provide the probabilistic reasonable evidence that the classical design method based on the safety factor cannot ensure the structural safety. In this phase, the probability density function estimated by CMCS(Crude Monte-Carlo Simulation) is used. Furthermore, the RBDO(Reliability-Based Design Optimization) under the probabilistic constraint are performed, and the RBDO-MPDF(RBDO by Moving Probability Density Function) is proposed for an efficient computation. The examined results in this paper can be helpful for advanced design techniques to ensure the reliability of structures under the uncertainty and computationally inexpensive RBDO methods.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1016-1021
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• 2008

In this study, effective methods for reliability estimation and reliability-based design optimization(RBDO) are proposed using kriging metamodel and genetic algorithm. In our previous study, we proposed the accurate method for reliability estimation using two-staged kriging metamodel and genetic algorithm. In this study, the possibility of applying the previously proposed method to RBDO is examined. The accuracy of that method is much improved than the first order reliability method with similar efficiency. Finally, the effective method for RBDO is proposed and applied to numerical examples. The results are compared to the existing RBDO methods and shown to be very effective and accurate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1464-1470
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• 2009

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.1-16
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• 2010

When Deterministic Design Optimization (DDO) methods are used, deterministic optimum designs are frequently pushed to the design constraint boundary, leaving little or no room for tolerances (or uncertainties) in design, manufacture, and operating processes. In the Reliability-Based Design Optimization (RBDO) model for robust system design, the mean values of uncertain system variables are usually used as design variables, and the cost is optimized subject to prescribed probabilistic constraints as defined by a nonlinear mathematical programming problem. Therefore, a RBDO solution that reduces the structural weight in uncritical regions does not only provide an improved design but also a higher level of confidence in the design. In this work, we seek to improve the quality of RBDO processes using efficient optimization techniques with object of improving the resulting objective function and satisfying the required constraints. Our recent RBDO developments show its efficiency and applicability in this context. So we present some recent structural engineering applications demonstrate the efficiency of these developed RBDO methods.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.187-191
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• 2004

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, single loop methods have been proposed. These need less function calls than that of RBDO but much more than that of DO. In this study, the approximate reliability method is proposed that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this method, the 3-D viscous aerodynamic shape design optimization with uncertainty is performed very efficiently.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.81-96
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• 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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.1
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• pp.51-59
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• 2005

SLSV (single loop single vector) method is to solve the excessive computational cost problem in RBDO (reliability-based design optimization) by decoupling the nested iteration loops. However, the practical use of SLSV method to RBDO case is limited by the instability or inaccuracy of the method since it often diverges or converges to a wrong solution. Thus, in this paper, a new modified SLSV method is proposed. This method improves its convergence capability effectively by utilizing Inactive Design and Active MPP Design together with modified HMV (hybrid mean value) method. The usefulness of the proposed method is also verified through numerical examples.