• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.115-121
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• 2012

This paper, being the second in a two-part series, presents the robust performance of the proposed design method which can enhance a reliability-based design optimization(RBDO) under the uncertainties of probabilistic models. The robust performances of the solutions obtained by the proposed method, described in the Part 1, are investigated through the parametric studies. A 10-bar truss example is considered, and the uncertain parameters include the number of data observed, and the variations of applied loadings and allowable stresses. The numerical results show that the proposed method can produce a consistent result despite of the large variations in the parameters. Especially, even with the relatively small data set, the analysis results show that the exact probabilistic model can be successfully predicted with optimized design sections. This consistency of estimating appropriate probability model is also observed in the case of the variations of other parameters, which verifies the robustness of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.32-39
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• 2000

Probabilistic structural design optimization, which is characterized by the so-called probabilistic. constraints which introduce permissible probability of violation, is preferred to deterministic design optimization since unpredictable inherent uncertainties and randomness in structural and environmental properties are to be taken quantitatively into account by probabilistic design optimization. In this paper, the well-known reliability index based MPFP(Most Probable Failure Point) search approach and the newly introduced target performance measure based MPTP(Minimum Performance Target Point) search approach are summarized and compared. The present comparison focuses on the number of iterations required for the estimation of probabilistic constraints and a technique for improvement which removes exhaustive iterations is presented as well. A 10 bar truss problem is examined for this.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.50-54
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• 2010

In this study, reliability-based design optimizations of airfoils were performed. PARSEC function was used to consider the uncertainty of the aerodynamic shape for the reliability-based shape optimization of airfoils. Among aerodynamic performance. The accuracy of the reliability analysis was compared with other method and it was found that the moment method predicts the probability accurately. Deterministic and reliability-based optimizations were performed for shape of the RAE2822 airfoil and it was demonstrated that reliability-based optimizations the aerodynamic performances under uncertainties of the shape of the airfoil.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.127-145
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• 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.

• 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.

• Structural Engineering and Mechanics
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• v.37 no.5
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• pp.543-560
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• 2011

In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

• 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.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.327-332
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• 2001

An experimental design technique is developed for estimating the moments of system response functions. It is easy to implement and provides accurate results compared with other traditional methods. It is based on the work of Taguchi, later improved by D'Errico and Zaino. The existing experimental techniques, however, is applicable only for normally distributed cases. In this article the three-level Taguchi method is extended to obtain optimum choice for levels and weights to handle nonnormal distributions. A systematic procedure for reliability analysis is then proposed by using the Pearson system and the narrow system reliability bounds. Illustrative examples including a tolerance optimization problem are shown very accurate comparing with those by Monte-Carlo simulations and the first-order reliability method.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.163-167
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• 2005

A research to evaluate efficiency of design optimization was performed 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 rather than a simultaneous distributed-analyses process 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 airfoil and to evaluate their efficiencies. One dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in distributed computing environment. The SAO was found quite suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the fittest for distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model are annoying and time-consuming so that they often impair the automatic capability of design optimization and also deteriorate efficiency from the practical point of view.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.229-239
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• 2018

Purpose: There is a difficulty in Environmental Stress Screening (ESS) test design for weapon system's electrical/electronic components/products in small and medium-sized enterprises. To overcome this difficulty, I propose an easy ESS test design approach algorithm that is optimized with only one environment tolerance design information parameter (${\Delta}T$). Methods: To propose the mass production weapon system ESS test design for cost-effective optimization, I define an optimum cost-effective mathematical model ESS test algorithm model based on modified MIL-HDBK-344, MIL-HDBK-2164 and DTIC Technical Report 2477. Results: I clearly confirmed and obtained the quantitative data of ESS effectiveness and cost optimization along our ESS test design algorithm through the practical case. I will expect that proposed ESS test method is used for ESS process improvement activity and cost cutting of mass production weapon system manufacturing cost in small and medium-sized enterprises. Conclusion: In order to compare the effectiveness of the proposed algorithm, I compared the effectiveness of the existing ESS test and the proposed algorithm ESS test based on the existing weapon system circuit card assembly for signal processing. As a result of the comparison, it was confirmed that the test time was reduced from 573.0 minutes to 517.2minutes (9.74% less than existing test time).