• Journal of Mechanical Science and Technology
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• 제20권10호
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• pp.1662-1669
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• 2006

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1991년도 봄 학술발표회 논문집
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• pp.34-42
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• 1991

This study is directed for the development of an efficient system-level Importance Sampling Technique for system reliability analysis of bridge structures Many methods have been proposed for structural reliability assessment purposes, such as the First-order Second-Moment Method, the Advanced Second-Moment Method, Computer Simulation, etc. The Importance Sampling Technique can be employed to obtain accurate estimates of the required probability with reasonable computation effort. Based on the observation and the results of application, it nay be concluded that Importance Sampling Method is a very effective tool for the system reliability analysis.

• 한국구조물진단유지관리공학회 논문집
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• 제17권6호
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• pp.1-10
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• 2013

복합재료가 신재생 에너지 산업 관련 구조물 및 해양 구조물에서 좀 더 신뢰도 있는 주 하중 부재로 사용되기 위하여 복합재료평판의 확률론적 비선형 초기 파단 하중과 원공과 곡률이 있는 복합재료판의 확률론적 비선형 좌굴 하중이 평가되었다. 주어진 설계 추출점에서의 확정론적 유한요소해석 결과를 바탕으로 반응면기법을 이용하여 한계상태면을 확률변수로 이루어진 2차 다항식으로 근사하였다. 또한, MPFP 근처에서 좀 더 정확하게 한계상태면을 근사하기 위하여 반복적 선형보간법이 적용되었다. 파괴확률을 평가하기 위하여 근사된 한계상태면 상에서 향상된 일계이차모멘트법과 몬테카를로법이 수행되었다. 마지막으로 파단에 영향을 주는 주요한 확률변수를 파악하기 위하여 변환된 확률변수에 대한 신뢰도지수의 감도를 계산하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제12권6호
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• pp.129-139
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• 2008

콘크리트 구조물의 내구성 해석 변수들의 변동성과 불확실성으로 인해 확률론적인 접근법의 사용이 증가되어 왔다. 특히, 몬테칼로시뮬레이션 방법(Level III 방법)은 접근성의 용이함으로 인해 많은 내구신뢰성 해석에 사용되어왔지만, 결과를 얻기위해서는 수 십만번의 반복계산이 필요하다. Level II 수준의 신뢰성 해석법인 일계이차모멘트법(FOSM)은 MCS법과 비교할 수 없을 정도의 짧은 시간에 신뢰도지수나 파괴확률을 계산할 수 있어, 유효성만 검증된다면 편리성과 신속성으로 인해 폭넓은 사용이 가능할 것이다. 본 연구에서는 FOSM법과 MCS법에 의한 부식확률(내구성 파괴확률)을 서로 비교하여 FOSM법의 유효성을 검증하고 각 내구성 해석변수들의 변동성이 부식확률에 미치는 영향을 검토하였다.

• 대한기계학회논문집A
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• 제24권1호
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• pp.215-224
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• 2000

In order to reduce the variation effects of uncertainties in the engineering environments, new robust optimization method, which considers the uncertainties in design process, is proposed. Both design variables and system parameters are considered as random variables about their nominal values. To ensure the robustness of performance function, a new objective is set to minimize the variance of that function. Constraint variations are handled by introducing probability constraints. Probability constraints are solved by the advanced first order second moment (AFOSM) method based on the reliability theory. The proposed robust optimization method has an advantage that the second derivatives of the constraints are not required. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• 산업기술연구
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• 제5권
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• pp.37-46
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• 1985

Recently-used structural reliability models are studied, and the usage and characteristics of each method are discussed. Although the First-Order Second Moment method may be efficient in structural reliability analysis, it has limitations which the limit state equation is linear and all the variables are normal. In that point, the Advanced Second-Moment(ASM) method have many good results, but computation of iterative method are trublesome. The results of ASM method similar to Variance Reduction Techniques(VRT), which is one of the Monte Carlo simulation methods. As a results, it is concluded that ASM method and VRT method are most efficient one.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 추계 학술발표회 제16권2호
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• pp.433-436
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• 2004

The safety of buildings is generally estimated by analyzing a plane frame ignoring a minor bending moment. In this paper, uncertainties of reinforced concrete shear wall subjected to a biaxial bending are considered. First, major parameters are selected from all parameters of general shear wall design to perform a reliability analysis in their practical ranges, means and standard derivations of selected design parameters for the reliability analysis are calculated by a data mining as a simulation method. The bi-section method is used to find inclined neutral axis and its limit state using MATLAB subjected to the concept on strength design method. The reliability index $\beta$ as a safety index is calculated based on AFOSM(Advanced First-Order Second Moment) method. Also, if target reliability index $\beta_T$ is decided by an engineer an amount of reinforcement can be calculated by subtracting the reliability index $\beta$ from the target reliability index $\beta_T$.

• 전산구조공학
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• 제4권2호
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• pp.119-129
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• 1991

본 논문은 교량구조의 체계신뢰도를 추정하기 위한 효율적인 중요도 표본추출기법의 개발을 목적으로 한다. 기존의 체계신뢰성 해석을 위한 방법은 1차 모멘트법, 2차 모멘트법, AFOSM 근사해법, 그리고 시뮬레이션 방법등이 있다. 중요도 표본추출기법은 아주 적은 경비와 노력으로 정확한 해를 구하는 시뮬레이션 방법이다. 적용 예를 통하여 중요도 표본추출기법은 교량구조의 체계신뢰성해석에 아주 효과적인 방법임을 알 수 있었다.

• Smart Structures and Systems
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• 제18권6호
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• pp.1233-1250
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• 2016

Cracks in plate-like structures are some of the main reasons for destruction of the entire structure. In this study, a novel two-stage methodology is proposed for damage detection of flexural plates using an optimized artificial neural network. In the first stage, location of damages in plates is investigated using curvature-moment and curvature-moment derivative concepts. After detecting the damaged areas, the equations for damage severity detection are solved via Bat Algorithm (BA). In the second stage, in order to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, multiple damage location assurance criterion index based on the frequency change vector of structures are evaluated using properly trained cascade feed-forward neural network (CFNN) as a surrogate model. In order to achieve the most generalized neural network as a surrogate model, its structure is optimized using binary version of BA. To validate this proposed solution method, two examples are presented. The results indicate that after determining the damage location based on curvature-moment derivative concept, the proposed solution method for damage severity detection leads to significant reduction of computational time compared with direct finite element method. Furthermore, integrating BA with the efficient approximation mechanism of finite element model, maintains the acceptable accuracy of damage severity detection.

• 한국지능시스템학회논문지
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• 제26권5호
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• pp.343-350
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• 2016

Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.