This paper uses the reliability polynomial, introduced by Moore and Shannon in 1956, to analyze the effect of network structure on diffusive dynamics such as the spread of infectious disease. We exhibit a representation for the reliability polynomial in terms of what we call structural motifs that is well suited for reasoning about the effect of a network's structural properties on diffusion ac...

The failure prediction requirements and the pertinent accept/reject criteria for structural ceramics are derived, and the available failure prediction techniques are examined, vis-a-vis the failure prediction relations , in order to highlight the capabilities and limitations of each technique. The need for additional techniques is thereby demonstrated. The capabilities of the ultrasonic techniq...

Large scale systems, common in cloud computing, rely on redundancy for reliability and availability. Modern clouds have become ever-increasingly complex and diverse creating large messes that experience long outages when failures occur. While there exist significant effort in resolving faults after they occur, we propose a novel approach to untangling this mess before it occurs by auditing the ...

A new class of computational methods, referred to as decomposition methods, has been developed for predicting failure probability of structural and mechanical systems subject to random loads, material properties, and geometry. The methods involve a novel function decomposition that facilitates univariate and bivariate approximations of a general multivariate function, response surface generatio...

Formulation of structural reliability requires selection of probabilistic or physical models, which usually involve parameters to be estimated through statistical inference — a process that invariably introduces uncertainties in parameter estimates. The measure of reliability that incorporates these parameter uncertainties is termed the predictive reliability index. Methods for computing this m...

The prediction of the behavior and reliability of engineering structures and systems is often plagued by uncertainty and imprecision caused by sparse data, poor measurements and linguistic information. Accounting for such limitations complicates the mathematical modeling required to obtain realistic results in engineering analyses. The framework of imprecise probabilities provides a mathematica...

Based on two procedures for efficiently generating conditional samples, i.e. Markov chain Monte Carlo (MCMC) simulation and importance sampling (IS), two reliability sensitivity (RS) algorithms are presented. On the basis of reliability analysis of Subset simulation (Subsim), the RS of the failure probability with respect to the distribution parameter of the basic variable is transformed as a s...

Structural systems are often subjected to the risk of fatigue-induced failures caused by repeated loadings during their service lifetime (Byers et al. 1997, Karamchandani et al. 1992). The reliability of such structural systems can be sustained through effective structural maintenance as well as proper structural design. It is thus essential to update the reliability of a structure against fati...

Many studies have been made on optimum structural design based on the reliability concept. However, they are limited to a simple type of structures. This may be attributable to the difficulty of reliability analysis and the lack of efficient algorithm to obtain optimum solutions for optimum design problems. Murotsu et al. developed an effective method of reliability analysis for redundant truss...

In many instances, information on engineering systems can be obtained through measurements, monitoring or direct observations of system performances and can be used to update the system reliability estimate. In structural reliability analysis, such information is expressed either by inequalities (e.g. for the observation that no defect is present) or by equalities (e.g. for quantitative measure...