• Proceedings of the KSME Conference
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• 2004.11a
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• pp.870-875
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• 2004

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.211-216
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• 2002

실제적인 문제에서 신뢰성 기반 최적 설계(RBDO)를 구현하기 위해서는 유한요소 모델을 해석하기 위한 상용 프로그램과 설계한 것에 대한 신뢰성을 산정할 수 있는 프로그램을 통합하고 최적화 알고리듬을 적용하여야 최적화를 수행하여야만 한다. 또한 최적화 과정에서 최적상태에서 제약조건이 비활성 영역에서 놓이게 되는 것을 방지하기 위해서 제약조건 최적화 문제를 비제약 조건 최적화 문제로 바꾸어 주는 장애 함수를 사용하여 최적화를 수행하였다. 그리고 이 방법론을 기존의 신뢰성기반 최적화 방법론, 즉 신뢰도지수 접근방법과 목표성능치 접근방법과의 비교를 하였다.

• Proceedings of the Korean Geotechical Society Conference
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• 1998.05a
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• pp.3-34
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• 1998

The stability condition of rock slopes is greatly affected by the geometry and strength parameters of discontinuities in the rock masses. Rock slopes Involving movement of rock blocks on discontinuities are failed by one or combination of the three basic failure modes-plane, wedge, and toppling. In rock mechanics, practically all the parameters such as the joint set characteristics, the rock strength properties, and the loading conditions are always subject to a degree of uncertainty. Therefore, a reasonable assessment of the rock slope stability has to include the excavation of the multi-failure modes, the consideration of uncertainties of discontinuity characteristics, and the decision on stabilization measures with favorable cost conditions. This study was performed to provide a new numerical model of the deterministic analysis, reliability analysis, and reliability-based optimization for rock slope stability. The sensitivity analysis was carried out to verify proposed method and developed program; the parameters needed for sensitivity analysis are design variables, the variability of discontinuity properties (orientation and strength of discontinuities), the loading conditions, and rock slope geometry properties. The design variables to be optimized by the reliability-based optimization include the cutting angle, the support pressure, and the slope direction. The variability in orientations and friction angle of discontinuities, which can not be considered in the deterministic analysis, has a greatly influenced on the rock slope stability. The stability of rock slopes considering three basic failure modes is more influenced by the selection of slope direction than any other design variables. When either plane or wedge failure is dominant, the support system is more useful than the excavation as a stabilization method. However, the excavation method is more suitable when toppling failure is dominant. The case study shows that the developed reliability-based optimization model can reasonably assess the stability of rock slopes and reduce the construction cost.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.821-826
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• 2013

When the values of design variables change, mode switching can often occur. If the mode of interest is not tracked, the frequencies and modes for design optimization may be miscalculated owing to modes that differ from the intended ones. Thus, mode tracking must be employed to identify the frequencies and modes of interest whenever the values of design variables change during optimization. Furthermore, reliability-based design optimization (RBDO) must be performed for design problems with design variables containing uncertainty. In this research, we perform RBDO considering the mode tracking of a compressive coil spring, i.e., a component of the joint spring that supports a compressor, with design variables containing uncertainty by using only kriging metamodels based on multiple responses approach (MRA) without existing mode tracking methods. The reliability analyses for RBDO are employed using kriging metamodel-based Monte Carlo simulation.

• International Journal of CAD/CAM
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• v.2 no.1
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• pp.1-12
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• 2002

Computer-Aided Reliable and Optimal Design (CAROD) system is an efficient tool defining the best compromise between cost and safety. Using the concurrent engineering concept, it can supply the designer with all numerical information in the design process. This system integrates several fields such as multidisciplinary optimization, reliability analysis, finite element analysis, geometrical modeling, sensitivity analysis and concurrent engineering. When integrating these disciplines, many difficulties are found such as model coupling and computational time. In this paper, we propose a new concurrent methodology satisfying the reliability requirement, allowing the coupling of different models and reducing the computational time. Two applications (rotating disk and hook structures) demonstrate that CAROD system can be a practical concurrent engineering application for designers.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3595-3603
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• 2022

Nuclear safety-class DCS is used for nuclear reactor protection function, which is one of the key facilities to ensure nuclear power plant safety, the maintenance for DCS to keep system in a high reliability is significant. In this paper, Nuclear safety-class DCS system developed by the Nuclear Power Institute of China is investigated, the model of reliability estimation considering nuclear power plant emergency trip control process is carried out using Markov transfer process. According to the System-Subgroup-Module hierarchical iteration calculation, the evolution curve of failure probability is established, and the preventive maintenance optimization strategy is constructed combining reliability numerical calculation and periodic overhaul interval of nuclear power plant, which could provide a quantitative basis for the maintenance decision of DCS system.

• Journal of the Microelectronics and Packaging Society
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• v.17 no.4
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• pp.67-72
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• 2010

In this paper, a design optimization of ball grid array packaging geometry is studied based on the Taguchi method, which allowed robust design by considering the variance of the input parameters during the optimization process. Molding compound and substrate were modeled as viscoelastic, and finite element analyses were performed to calculate the strain energy densities of the eutectic solder balls. Six quality factors of the dimensions of the packaging geometry were chosen as control factors. After performing noise experiments to determine the dominant factors, main experiments were conducted to find the optimum packaging geometry. Then the strain energy densities between the original and optimized geometries were compared. It was found that the effects of the packaging geometry on the solder ball reliability were significant, and more than 40% of the strain energy density was reduced by the geometry optimization.

• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.19-24
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• 2006

A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

• Journal of Ocean Engineering and Technology
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• v.28 no.3
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• pp.218-226
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• 2014

Since the support structure of an offshore wind turbine has to withstand severe environmental loads such as wind, wave, and seismic loads during its entire service life, the need for a robust and reliable design increases, along with the need for a cost effective design. In addition, a robust and reliable support structure contributes to the high availability of a wind turbine and low maintenance costs. From this point of view, this paper presents a design process that includes design optimization and reliability analysis. First, the jacket structure of the NREL 5-MW offshore wind turbine is optimized to minimize the weight and stresses, while satisfying the design requirements. Second, the reliability of the optimum design is evaluated and compared with that of the initial design. Although the present study results in a new optimum shape for a jacket support structure with reduced weight and increased reliability, the authors suggest that the optimum design has to be accompanied by a reliability analysis during the design process, as well as reliability based design optimization if needed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.