• Structural Engineering and Mechanics
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• 제66권6호
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• pp.677-691
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• 2018

Reliability assessment of complex structures using simulation methods is time-consuming. Thus, surrogate models are usually employed to reduce computational cost. AK-MCS is a surrogate-based Active learning method combining Kriging and Monte-Carlo Simulation for structural reliability analysis. This paper proposes three modifications of the AK-MCS method to reduce the number of calls to the performance function. The first modification is related to the definition of an initial Design of Experiments (DoE). In the original AK-MCS method, an initial DoE is created by a random selection of samples among the Monte Carlo population. Therefore, samples in the failure region have fewer chances to be selected, because a small number of samples are usually located in the failure region compared to the safe region. The proposed method in this paper is based on a uniform selection of samples in the predefined domain, so more samples may be selected from the failure region. Another important parameter in the AK-MCS method is the size of the initial DoE. The algorithm may not predict the exact limit state surface with an insufficient number of initial samples. Thus, the second modification of the AK-MCS method is proposed to overcome this problem. The third modification is relevant to the type of regression trend in the AK-MCS method. The original AK-MCS method uses an ordinary Kriging model, so the regression part of Kriging model is an unknown constant value. In this paper, the effect of regression trend in the AK-MCS method is investigated for a benchmark problem, and it is shown that the appropriate choice of regression type could reduce the number of calls to the performance function. A stepwise approach is also presented to select a suitable trend of the Kriging model. The numerical results show the effectiveness of the proposed modifications.

• 콘크리트학회논문집
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• 제14권2호
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• pp.266-274
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• 2002

콘크리트 구조물 또는 조적식 구조물을 비파괴적으로 평가하는 충격반향시험은 타 기법과 비교하였을 때, 현장 적용면에서 탁월하게 우수하며, 그 신뢰성도 매우 높게 평가되고 있다 그러나 경우에 따라서 충격반향기법은 낮은 신뢰성을 나타내고 있다. 본 연구에서는 충격반향기법의 신뢰성을 수치해석에 의해 검토하였다. 유한요소해석 및 이론을 근거로 하는 동강성행렬법을 이용하여 균질한 강성구조 깊이에 따라 증가 또는 감소하는 전단강성구조, 샌드위치형 전단강성구조 등 대표적 유형의 전단강성구조를 가지는 콘크리트 터널벽체에 대해 충격반향실험의 수치 모사를 수행하였다. 이를 바탕으로 충격반향기법의 실험자료 분석 및 해석에 있어서 보다 신뢰성 있는 결과 도출을 위한 제언을 하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1993년도 가을 학술발표회논문집
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• pp.248-255
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• 1993

Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.

• 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.

• International Journal of Aeronautical and Space Sciences
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• 제12권4호
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• pp.385-395
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• 2011

An ejector was developed for man-portable missiles. The ejector can be separated from the missile after the completion of the ejection function even without any additional separation devices. This paper introduces the particular separation mechanism of the ejector and presents the methodology, based on a probabilistic design method, to predict the ejection-and-separation reliability. This approach using Monte Carlo simulation can also be applicable to the reliability prediction of one-shot items suffering from difficulties in estimating or in demonstrating their reliability due to the lack of the number of tests available.

• Structural Engineering and Mechanics
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• 제80권6호
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• Geomechanics and Engineering
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• 제21권6호
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• pp.513-525
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• 2020

Slopes stabilised with piles are seldom analysed considering uncertainties in the parameters of the pile-slope system. Reliability analysis of the pile-slope system quantifies the degree of uncertainties and evaluates the safety of the system. In the present study, the reliability analysis of a slope stabilised with piles is performed using the first-order reliability method (FORM) based on Hasofer-Lind approach. The implicit performance function associated with the factor of safety (FS) of the slope is approximated using the response surface method. The analyses are carried out considering the design matrices formulated based on both the 2^k factorial design augmented with a centre run (2^k fact-centred design) and face-centered cube design (FCD). The finite element method is used as the deterministic model to compute the FS of the pile-slope system. Results are compared with the results of the Monte Carlo simulation. It is observed that the optimum location of the row of piles is at the middle of the slope to achieve the maximum FS. The results show that the reliability of the system is not uniform for different pile configurations, even if the system deterministically satisfies the target factor of safety (FS_t) criterion. The FS_t should be selected judiciously as it is observed that the reliability of the system changes drastically with the FS_t level. The results of the 2^k fact-centred design and FCD are in good agreement with each other. The procedure of the FCD is computationally costly and hence the use of 2^k fact-centred design is recommended, provided the response of the system is sufficiently linear over the factorial space.

• Smart Structures and Systems
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• 제33권3호
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• Journal of Magnetics
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• 제19권1호
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• pp.78-83
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• 2014

This paper proposes an efficient reliability-based optimization method for designing a superconducting magnetic energy system in presence of uncertainty. To evaluate the probability of failure of constraints, samplingbased reliability analysis method is employed, where Monte Carlo simulation is incorporated into dynamic Kriging models. Its main feature is to drastically reduce the numbers of iterative designs and computer simulations during the optimization process without sacrificing the accuracy of reliability analysis. Through comparison with existing methods, the validity of the proposed method is examined with the TEAM Workshop Problem 22.

• 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 $\beta_T$.