• Structural Engineering and Mechanics
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• 제32권1호
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• pp.55-69
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• 2009

A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

• Structural Engineering and Mechanics
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• 제85권3호
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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.

• 한국조경학회지
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• 제23권1호
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• pp.23-38
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• 1995

ELEECTRE is a less demanding and potentially Bffective multiattribute evaluation method for pre-editing proeedure. The method, however, was developed based on probabilistic mathematicsand its reliability has never'been emprieally tested. This article examined the reliability of ELECTRo under various conditions of linear and non-linear utility func- tions using a Monte-Carlo shnulation, and found the method eausea a considerably high rate of error. To enhance the reliability of ELECTRE, two ways of modi(ication - adjust- ment of threshold values of concordance and discordance matrices, and adjustment of the required nunlber of probably-dominant alternatives to eliminate a probably-dominated alternative - were suggested, and their effctiveness was also tesed by a Monte-Carlo simulation. The simulation result chows that these modifications cponsiderably improve the reliability of ELECTRE, and yet maintain a reasonably high level of efficiency. Through these modifications, ELECTRE can be used as an efficient and feliable pre-editing method. Ways to implement ELECTRE in the construction of plainning decision support systens were discussed. The impli(els combination of this method and other multiattribute evaluation methods will help to create more effective decision suport systems.

• Journal of Magnetics
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• 제17권4호
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• pp.291-297
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• 2012

This paper presents an efficient methodology for accurate reliability assessment of electromagnetic devices. To achieve the goal, elaborate surrogated models to approximate constraint functions of interest are generated based on the dynamic Kriging method and a hypercube local window. Then, the Monte Carlo simulation scheme is applied to the surrogate models. This leads to reducing computational cost dramatically without degrading accuracy of the reliability analysis. The validity of the proposed method is tested and examined with a mathematical example and a loudspeaker design.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.751-760
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• 2018

Damages in concrete structures due to aging and other factors could be a serious and immense matter. Making the best selection of the most viable and practical repairing and strengthening techniques are relatively difficult tasks using traditional methods of structural analyses. This is due to the fact that the traditional methods used for assessing aging structure are not fully capable when considering the randomness in strength, loads and cost. This paper presents a reliability-based methodology for assessing reinforced concrete members. The methodology of this study is based on probabilistic analysis, using statistics of the random variables in the performance function equations. Principles of reliability updating are used in the assessment process, as new information is taken into account and combined with prior probabilistic models. The methodology can result in a reliability index ${\beta}$ that can be used to assess the structural component by comparing its value with a standard value. In addition, these methods result in partial safety factor values that can be used for the purpose of strengthening the R/C elements of the existing structure. Calculations and computations of the reliability indices and the partial safety factors values are conducted using the First-order Reliability Method and Monte Carlo simulation.

• Journal of Magnetics
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• 제17권1호
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• pp.46-50
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• 2012

A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.

• Wind and Structures
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• 제27권3호
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• pp.149-161
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• 2018

A reliability analysis method is proposed in this paper based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of the fractional moments instead of integer moments. Then a multiplicative dimensional reduction method (M-DRM) is introduced to compute the fractional moments. The method is applicable for both explicit and implicit limit state functions of complex structures. After two examples illustrate the accuracy and efficiency of this method in comparison to the Monte Carlo simulation (MCS), the method is used to analyze the flutter reliability of suspension bridge. The results show that the empirical formula method in which the limit state function is explicitly represented as a function of variables is only a too conservative estimate for flutter reliability analysis but is not accurate adequately. So it is not suitable for reliability analysis of bridge flutter. The actual flutter reliability analysis should be conducted based on a finite element method in which limit state function is implicitly represented as a function of variables. The proposed M-DRM provide an alternate and efficient way to analyze a much more complicated flutter reliability of long span suspension bridge.

• 대한기계학회논문집A
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• 제33권10호
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• pp.1163-1170
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• 2009

Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• 터널과지하공간
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• 제20권1호
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• pp.39-48
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• 2010

본 연구에서는 확률론적 기법을 토대로 터널 지보시스템의 신뢰성을 평가할 수 있는 프로그램을 개발하였다. 개발된 프로그램은 솔버로서 FLAC2D를 사용하며 수치해석과 확률론적 해석의 전 과정을 자동적으로 처리할 수 있다. 지반을 모델링한 수치해석시 상당한 계산시간이 소요되므로 시뮬레이션 기법을 적용하여 터널 지보시스템의 신뢰성을 확률론적으로 평가하는 것은 현실적으로 불가능하다. 따라서 본 연구에서는 샘플의 수를 시뮬레이션 기법에 비해 상당히 줄일 수 있어 확률론적 해석을 하는 데 효율적인 점추정법을 사용하였다. 본 연구에서 개발한 프로그램을 터널 프로젝트에 적용하여 결정론적 접근법에 의한 결과와 비교 분석하였다. 이로부터 확률론적 접근법은 파괴확률을 토대로 터널 지보시스템의 신뢰성을 정량적으로 평가할 수 있고 터널 지보설계시 의사결정의 도구로서 활용될 수 있다는 것을 확인하였다.