• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Computational Structural Engineering
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• v.4 no.2
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• pp.119-129
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• 1991

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

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.91-102
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• 2000

Nowadays, every kind of system is changed so complex and enormous, it is necessary to assure system reliability, product liability and safety. Fault tree analysis(FTA) is a reliability/safety design analysis technique which starts from consideration of system failure effect, referred to as “top event”, and proceeds by determining how these can be caused by single or combined lower level failures or events. So in fault tree analysis, it is important to find the combination of events which affect system failure. Minimal cut sets(MCS) and minimal path sets(MPS) are used in this process. FTA-I computer program is developed which calculates MCS and MPS in terms of Gw-Basic computer language considering Fussell's algorithm. FTA-II computer program which analyzes importance and function cost of VE consists. of five programs as follows : (l) Structural importance of basic event, (2) Structural probability importance of basic event, (3) Structural criticality importance of basic event, (4) Cost-Failure importance of basic event, (5) VE function cost analysis for importance of basic event. In this study, a method of initiation such as failure, function and cost in FTA is suggested, and especially the priority rank which is calculated by computer-aided decision analysis program developed in this study can be used in decision making determining the most important basic event under various conditions. Also the priority rank can be available for the case which selects system component in FMEA analysis.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.663-670
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• 2015

In most public transportation related master plans, decisions for investment priorities are initially made by facilities with lower installation rates or lower satisfaction (performance) levels. In general, the decisions are made without conducting importance factor analysis. In this study, a combined method of importance-performance analysis (IPA) model for bus users related in travel time is proposed by using Structural Equation Model (SEM). The results of the IPA for Metropolitan users show that the categories need improvement are number of bus stops, number of intersections, headways, waiting times for boarding and traffic signal operations in order. On the other hand, Non-Metropolitan uses show that the categories need improvement are traffic signal operations, waiting times for boarding, headways, bus exclusive lanes and number of intersections that is in reverse order to Metropolitan users.