• International Journal of Reliability and Applications
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• v.3 no.4
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• pp.173-184
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• 2002

This paper introduces the joint structural importance of two components in a coherent system. Some relationships between joint structural importance and marginal structural importance are presented. It is shown that the sign of Joint structural importance can be determined, in advance, without computation in some special structures. The joint structural importance of two components in some series-parallel and parallel-series systems are established. Some practical examples are presented to elucidate some of the derived results.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.04a
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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.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.125-140
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• 2011

This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.

• Structural Engineering and Mechanics
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• v.32 no.1
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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.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.577-582
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• 2007

A continuum structure function (CSF) is a non-decreasing mapping from the unit hypercube to the unit interval. A B-type CSF, defined in the text, is a CSF whose behaviour is modeled by its underlying binary structures. As the measure of importance of a system component for a B-type CSF, the structural and reliability importance of a component at a system level ${\alpha}$(0 < ${\alpha}$ < 1) are defined and their properties are deduced.

• Earthquakes and Structures
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• v.17 no.2
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• pp.131-141
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• 2019

Structural control systems have uncertainties in their structural parameters and control devices which by using reliability analysis, uncertainty can be modeled. In this paper, reliability of controlled structures equipped with semi-active Magneto-Rheological (MR) dampers is investigated. For this purpose, at first, the effect of the structural parameters and damper parameters on the reliability of the seismic responses are evaluated. Then, the reliability of MR damper force is considered for expected levels of performance. For sensitivity analysis of the parameters exist in Bouc- Wen model for predicting the damper force, the importance vector is utilized. The improved first-order reliability method (FORM), is used to reliability analysis. As a case study, an 11-story shear building equipped with 3 MR dampers is selected and numerically obtained experimental data of a 1000 kN MR damper is assumed to study the reliability of the MR damper performance for expected levels. The results show that the standard deviation of random variables affects structural reliability as an uncertainty factor. Thus, the effect of uncertainty existed in the structural model parameters on the reliability of the structure is more than the uncertainty in the damper parameters. Also, the reliability analysis of the MR damper performance show that to achieve the highest levels of nominal capacity of the damper, the probability of failure is greatly increased. Furthermore, by using sensitivity analysis, the Bouc-Wen model parameters which have great importance in predicting damper force can be identified.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.225-233
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• 2012

The research discusses interrelationship of structural and reliability importance measures which used in the probabilistic safety assessment. The most frequently used component importance measures, such as Birnbaum's Importance (BI), Risk Reduction (RR), Risk Reduction Worth (RRW), RA (Risk Achievement), Risk Achievement Worth (RAW), Fussel Vesely (FV) and Critically Importance (CI) can be derived from two structure importance measures that are developed based on the size and the number of Minimal Path Set (MPS) and Minimal Cut Set (MCS). In order to show an effectiveness of importance measures which is developed in this paper, the three representative functional structures, such as series-parallel, k out of n and bridge are used to compare with Birnbaum's Importance measure. In addition, the study presents the implementation examples of Total Productive Maintenance (TPM) metrics and alternating renewal process models with exponential distribution to calculate the availability and unavailability of component facility for improving system performances. System state structure functions in terms of component states can be converted into the system availability (unavailability) functions by substituting the component reliabilities (unavailabilities) for the component states. The applicable examples are presented in order to help the understanding of practitioners.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.45-53
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• 2011

The research proposes seven elimination rules of redundant gates and blocks in Fault Tree Analysis (FTA) and Reliability Block Diagram (RBD). The computational complexity of cut sets and path sets is NP-hard. In order to reduce the complexity of Minimal Cut Set (MCS) and Minimal Path Set (MPS), the paper classifies generation algorithms. Moreover, the study develops six implementation steps which reflect structural importance (SI) and reliability importance (RI) from Reliability Centered Maintenance (RCM) that a priority of using the functional logic among components is to reduce (improve) the system unavailability (or availability). The proposed steps include efficient generation of state structure function by Rare Event Enumeration (REA). Effective use of importance measures, such as SI and ill measures, is presented based on the number and the size of MCS and MPS which is generated from the reference[5] of this paper. In addition, numerical examples are presented for practitioners to obtain the comprehensive understanding of six steps that is proposed in this research.

• Structural Engineering and Mechanics
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• v.3 no.3
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• pp.201-213
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• 1995

At present Level 2 and importance sampling methods are the main tools used to estimate reliability of structural systems. But sometimes application of these techniques to realistic problems involves certain difficulties. In order to overcome the difficulties it is suggested to use Monte Carlo simulation in combination with two other techniques-extreme value and tail entropy approximations; an appropriate Pearson's curve is fit to represent simulation results. On the basis of this approach an algorithm and computer program for structural reliability estimation are developed. A number of specially chosen numerical examples are considered with the aim of checking the accuracy of the approach and comparing it with the Level 2 and importance sampling methods. The field of application of the approach is revealed.

• Structural Engineering and Mechanics
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• v.5 no.2
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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.