• Structural Engineering and Mechanics
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• 제9권6호
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• pp.557-568
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• 2000

As time-variant reliability approaches become increasingly used for service life prediction of the aging infrastructure, the demand for computer solution methods continues to increase. Effcient computer techniques have become well established for the reliability analysis of structural systems. Thus far, however, this is largely limited to time-invariant reliability problems. Therefore, the requirements for time-variant reliability prediction of deteriorating structural systems under time-variant loads have remained incomplete. This study presents a computer program for $\underline{REL}$iability of $\underline{T}$ime-Variant $\underline{SYS}$tems, RELTSYS. This program uses a combined technique of adaptive importance sampling, numerical integration, and fault tree analysis to compute time-variant reliabilities of individual components and systems. Time-invariant quantities are generated using Monte Carlo simulation, whereas time-variant quantities are evaluated using numerical integration. Load distribution and post-failure redistribution are considered using fault tree analysis. The strengths and limitations of RELTSYS are presented via a numerical example.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.803-808
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• 2007

LCCA module enabling to estimate LCC and analyze time-variant reliability index of a plate girder bridge was developed. The developed module was based on the designed data structure following the standardized methodology of ISO/STEP, LCCA module consisted of LCC estimation module, which is composed of six sub modules according to the cost category, and reliability index analysis module, which is composed of time-variant corrosion sub module, time-variant live load sub module, and element reliability analysis sub module, The effectiveness of the developed LCCA module was verified by estimating LCC and analyzing time-variant reliability index of a plate girder bridge on the basis of the constructed test database.

• 한국농공학회지
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• 제45권2호
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• pp.35-44
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• 2003

A system reliability method is proposed to decide reliable serviceability of agricultural irrigation system. Even though reliability method is applied to real engineering situations involving actual life environments and maintaining costs, a number of Issues arise as a modeling and analysis level. This article use concepts that can be described the probability of failure with time variant and series-parallel system reliability analysis model. A proposed method use survivor function that can simulate a time-variant performance function for a lifetime before it is required essential maintenance or replacement to define a target probability of failure in agricultural irrigation canal. In the further study, it is required a relationship between a state of probability of failure and current serviceability to make the optimum repair strategy to maintain appropriate serviceability of an irrigation system.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.173-179
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• 2018

Estimating reliability of a non-repairable system using the degradation data, variance assumption such as homogeneity (constant) or heteroscedasticity (time-variant) could affect accuracy of reliability estimation. This paper showed reliability estimation and comparison results under normal conditions using accelerated degradation data obtained from destructive measurements, according to variance assumption of the data at each measurement time. Degradation data from three accelerated conditions with stress factors of temperature and humidity were used to estimate reliability. The $B_{10}$ lifetime was estimated as 1243.8 years by constant variance assumption, and 18.9 years by time-variant variance. And variance assumption provided different analysis results of important stresses to reliability. Thus, accurate assumption of variance at each measurement time is required when estimating reliability using degradation data of a non-repairable system.

• Computers and Concrete
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• 제17권4호
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• pp.499-521
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• 2016

In this paper, a probabilistic- and finite element-based approach to evaluate and predict the lifetime performance of reinforced concrete (RC) bridges undergoing various maintenance actions is proposed with the time-variant system reliability being utilized as a performance indicator. Depending on their structural state during the degradation process, the classical maintenance actions for RC bridges are firstly categorized into four types: Preventive type I, Preventive type II, Strengthening and Replacement. Preventive type I is used to delay the onset of steel corrosion, Preventive type II can suppress the corrosion process of reinforcing steel, Strengthening is the application of various maintenance materials to improve the structural performance and Replacement is performed to restore the individual components or overall structure to their original conditions. The quantitative influence of these maintenance types on structural performance is investigated and the respective analysis modules are written and inputted into the computer program. Accordingly, the time-variant system reliability can be calculated by the use of Monte Carlo simulations and the updated the program. Finally, an existing RC continuous bridge located in Shanghai, China, is used as an illustrative example and the lifetime structural performance with and without each of the maintenance types are discussed. It is felt that the proposed approach can be applied to various RC bridges with different structural configurations, construction methods and environmental conditions.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2007년도 정기총회 및 학술발표대회
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• pp.497-500
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• 2007

Data structure was designed not only to estimate LCC but also to analyze time-variant reliability index of plate girder bridges. Information model for data structure was categorized into cost information, cost variable information, user cost information, and reliability analysis information according to the characteristic of data. EXPRESS language of STEP was adopted to describe the data structure for the electronic representation of LCC information. The suitability of the developed data structure was verified by estimating LCC and analyzing time-variant reliability index of a plate girder bridge considering corrosion on the basis of the constructed test database.

• Structural Engineering and Mechanics
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• 제5권2호
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• pp.115-126
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• 1997

Importance sampling methods have been developed with the aim of reducing the computational costs inherent in Monte Carlo methods. This study proposes a new algorithm called the adaptive kernel method which combines and modifies some of the concepts from adaptive sampling and the simple kernel method to evaluate the structural reliability of time variant problems. The essence of the resulting algorithm is to select an appropriate starting point from which the importance sampling density can be generated efficiently. Numerical results show that the method is unbiased and substantially increases the efficiency over other methods.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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• pp.154-156
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• 2017

종래에는 등분산 가정을 기반으로 가속열화시험 데이터로부터 저장수명을 예측하는 방식이 일반적이었다. 그러나, 실제로는 대부분의 탄약류의 특성치 데이터는 시간의 경과에 따라 산포가 증가한다. 따라서, 본 연구에서는 등분산과 이분산을 가정한 경우에 저장수명 예측 결과의 차이를 확인하고 향후 이분산 가정을 기반으로 데이터 분석을 수행함이 타당함을 제안한다.

• Structural Engineering and Mechanics
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• 제55권3호
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• pp.525-534
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• 2015

A new structural dynamic fuzzy reliability analysis under stochastic loads which are applied several times is proposed in this paper. The fuzzy reliability prediction models based on time responses with and without strength degeneration are established using the stress-strength interference theory. The random loads are applied several times and fuzzy structural strength is analyzed. The efficiency of the proposed method is demonstrated numerically through an example. The results have shown that the proposed method is practicable, feasible and gives a reasonably accurate prediction. The analysis shows that the probabilistic reliability is a special case of fuzzy reliability and fuzzy reliability of structural strength without degeneration is also a special case of fuzzy reliability with structural strength degeneration.

• 정보처리학회논문지D
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• 제8D권4호
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• pp.387-392
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• 2001

많은 소프트웨어 프로젝트는 시험이나 운영단계에서 고장시간이나 고장 수 데이타보다 그룹 고장 데이터(여러 고장 간격에서 또는 가변적인 시간 간격에서의 고장들)가 수집된다. 본 논문은 그룹 고장 데이터에 대해 가변적인 미래의 시간에서 누적 고장 수를 예측할 수 있는 신경망 모델을 제시한다. 2개의 변형된 캐스케이드-상관 학습 알고리즘을 제안하였다. 제안된 신경망 모델들은 다른 잘 알려진 신경망 모델과 통계적 소프트웨어 신뢰도 성장 모델과 비교되었다. 실험결과, 그룹 데이터에 대해 변형된 캐스케이드-상관 학습 알고리즘이 좋은 예측 결과를 나타내었다.