Showing papers in "Reliability Engineering & System Safety in 2014"

TL;DR: To better understand CISs to support planning, maintenance and emergency decision making, modeling and simulation of interdependencies across CISs has recently become a key field of study and this paper reviews the studies in the field and broadly groups the existing modeling and Simulation approaches into six types.

TL;DR: It is shown that the proposed resilience analysis framework and metric promote the development of methodologies for investigating “deep” uncertainties in resilience assessment while retaining the use of probability for expressing uncertainties about highly uncertain, unforeseeable, or unknowable hazards in design and management activities.

TL;DR: The modification allows overcoming an important limitation of the original AK-IS in that it provides the algorithm with the flexibility to deal with multiple failure regions characterized by complex, non-linear limit states.

TL;DR: This paper focuses on sampling techniques and, considering the recent adaptation of the EGRA method for systems, a strategy is presented to adapt the AK-MCS method for system reliability.

TL;DR: In this article, the authors present a systematic, transferable and proactive framework estimating the risk for maritime transportation systems, meeting the requirements stemming from the adopted formal definition of risk, which requires a proactive approach when it comes to risk modelling.

TL;DR: The proposed systemic decision support approach for safety risk analysis under uncertainty in tunnel construction can be used to provide guidelines for safety analysis and management in construction projects, and thus increase the likelihood of a successful project in a complex environment.

TL;DR: A new integrated perspective, a new way of thinking, capturing all these approaches is presented, which provides new insights as well as practical guidelines for how to understand, assess and manage the unforeseen and (potential) surprises in a practical operational setting.

TL;DR: A Bayesian analysis of inverse Gaussian process models for degradation modeling and inference and a classic example is presented to demonstrate the applicability of the Bayesian method for degradation analysis with the inverse Gaussia process models.

TL;DR: This work presents an adaptive method of RL estimation based on a generalized Wiener degradation process which subsumes several existing models as limiting cases and demonstrates the validity of the proposed method with an illustrative example concerning fatigue cracks.

TL;DR: A Column-and-Constraint Generation algorithm is designed and implemented to derive its optimal solutions for power grid vulnerability and shows that it significantly outperforms the existing exact algorithm.

TL;DR: An extensive review of some discrete and continuous versions of the modifications of the Weibull distribution to allow for non-monotonic hazard functions.

TL;DR: This paper aims at practical challenges of online diagnostics and prognostics of mechanical systems under unobservable degradation, and the elements of a multistate degradation structure are reviewed and a model selection framework is introduced.

TL;DR: In this article, the authors address the problem of estimating, quantifying and planning for economic resilience of interdependent infrastructures, where interconnectedness adds to problem complexity, and propose static and dynamic measures for resilience that confirm well-known resilience concepts of robustness, rapidity, redundancy, and resourcefulness.

TL;DR: This study uses copula to model the dependent stochastic degradation of components, and forms the optimal decision problem based on the minimum expected cost rule and the Stochastic dominance rules.

TL;DR: A genetic algorithm is used to solve the optimization models for multi-state series–parallel systems with economically dependent components based on the maintenance objective, resource availabilities and how dependent the repair time and cost are.

TL;DR: A methodology has been proposed based on hierarchical Bayesian analysis and accident precursor data to risk analysis of major accidents and its outperformance compared to conventional approaches is demonstrated.

TL;DR: A novel strategy, that is a combination of traditional active and standby strategies, is introduced which uses both active and cold-standby strategies in one subsystem simultaneously and is implemented on a well-known test problem which leads to interesting results.

TL;DR: A probabilistic framework for scenario-based resilience assessment of infrastructure systems will enable port stakeholders to systematically assess the most-likely performance of the system during expected future earthquake events.

TL;DR: In this second part of the study a distinct, advanced, infinite horizon POMDP formulation with 332 states is cast and solved, related to a corroding reinforced concrete structure and its minimum life-cycle cost.

TL;DR: Evaluating the nodal vulnerability of WDNs under cascading failures revealed that the network vulnerability should be evaluated with the consideration of hydraulic analysis and network topology.

TL;DR: A cost model and a heuristic optimization scheme are proposed since the optimization of maintenance grouping strategy for multi-component systems leads to a NP-complete problem and a finite horizon (dynamic) model is proposed in order to optimize online the maintenance strategy in the presence of dynamic contexts.

TL;DR: The S ACADA data taxonomy, the theoretical foundation, the prospective data to be generated from the SACADA raw data to inform human reliability and human performance, and the considerations on the use of simulator data for HRA are discussed.

TL;DR: This paper considers the demand-based PMS with parallel structure, where the system components function in parallel with different capacities in each phase of the mission and the mission is successful if and only if the total system capacity meets the predetermined mission demand in eachphase.

TL;DR: Since the problem under study is combinatorial in nature involving several non-linear decision variables, a simulated annealing algorithm is employed to provide good solutions within reasonable search time.

TL;DR: This paper integrates noncyclical preventive maintenance with tactical production planning in multi-state systems and determines an integrated lot-sizing and preventive maintenance strategy of the system that will minimize the sum of preventive and corrective maintenance costs, setup costs, holding costs, backorder costs, and production costs, while satisfying the demand for all products over the entire horizon.

TL;DR: This paper presents a methodology of resilience analysis of systems of systems, with infrastructures as a special instance, and a conceptual representation of the infrastructure, based on the functional relationships among its components, is given and then analyzed with respect to its structural and dynamic properties.

TL;DR: In this paper, reliability for multi-component systems subject to dependent competing risks of degradation wear and random shocks, with distinct shock sets is studied, and a new model to classify random shocks into different sets based on their sizes or function is developed.

TL;DR: Multilayer feedforward neural networks based on multi-valued neurons (MLMVN), a specific type of complex valued neural networks, are proposed to be applied to reliability and degradation prediction problems, formulated as time series.

TL;DR: In this article, the authors investigated probabilistic approaches based on the annual reliability index, annual risk, and lifetime distributions for life-cycle maintenance of structural systems, and obtained maintenance schedules for representative series, parallel, and series-parallel systems considering total restoration of component resistances whenever a prescribed threshold, based on a selected performance indicator, is reached.

TL;DR: Polynomial Chaos Expansion (PCE) is used for an efficient GSA with multivariate output and the results indicate that PCE allows efficient estimation of the covariance matrix and GSA on the coefficients in the approach defined by Campbell et al.