Quantifying the Impact of Correlated Failures on Stochastic Flow Network Reliability

2012 ◽  
Vol 61 (3) ◽  
pp. 692-701 ◽  
Author(s):  
Yi-Kuei Lin ◽  
Ping-Chen Chang ◽  
L. Fiondella
Keyword(s):  
Network Reliability ◽  
Stochastic Flow ◽  
Flow Network ◽  
Correlated Failures ◽  
The Impact

Modeling and Applications on Timed Stochastic-Flow Networks

2015 ◽  
Vol 22 (05) ◽  
pp. 1550023
Author(s):  
Shin-Guang Chen
Keyword(s):  
Network Reliability ◽  
Daily Life ◽  
Transportation Network ◽  
Stochastic Flow ◽  
Production Network ◽  
Flow Networks ◽  
Stochastic Behavior ◽  
Flow Network ◽  
Numerical Examples ◽  
Time Consumption

A stochastic-flow network (SFN) is a network whose flow has stochastic behavior or probabilistic multi-states. A timed stochastic-flow network (TSFN) is a SFN whose flow spends time to go through the network. Traditionally, the evaluation of network reliability does not consider time consumption for the flow to get through the network. However, there are lots of daily-life networks which can be regarded as TSFNs, such as the transportation network, the production network, etc. Their flow spends time to get through the network, and they are not yet explored in the literature. This paper proposes approaches to evaluate the reliability of such networks. Some numerical examples are discussed to illustrate the proposed method.

scholarly journals Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures, I: Methodology

2014 ◽  
Vol 30 (2) ◽  
pp. 795-817 ◽  
Author(s):  
Jayadipta Ghosh ◽  
Keivan Rokneddin ◽  
Jamie E. Padgett ◽  
Leonardo Dueñas-Osorio
Keyword(s):  
Network Reliability ◽  
Reliability Assessment ◽  
Highway Bridges ◽  
Seismic Reliability ◽  
Construction Methods ◽  
Field Instrumentation ◽  
Correlated Failures ◽  
Bridge Failure ◽  
The Impact ◽  
Deterioration Parameters

The state-of-the-practice in seismic network reliability assessment of highway bridges often ignores bridge failure correlations imposed by factors such as the network topology, construction methods, and present-day condition of bridges, among others. Additionally, aging bridge seismic fragilities are typically determined simply using historical estimates of deterioration parameters. This research presents a methodology to estimate bridge fragilities using spatially interpolated and updated deterioration parameters from a limited set of instrumented bridges in the network, while incorporating the impacts of overlooked correlation factors in bridge fragility estimates. Simulated samples of correlated bridge failures are used in an enhanced Monte Carlo method to assess bridge network reliability, and the impact of different correlation structures on the network reliability is discussed. The presented methodology aims to provide more realistic estimates of seismic reliability of aging transportation networks and to potentially help network stakeholders to more accurately identify critical bridges for maintenance and retrofit prioritization.

scholarly journals Efficient Estimation of Stochastic Flow Network Reliability

2019 ◽  
Vol 68 (3) ◽  
pp. 954-970 ◽  
Author(s):  
Hector Cancela ◽  
Leslie Murray ◽  
Gerardo Rubino
Keyword(s):  
Network Reliability ◽  
Efficient Estimation ◽  
Stochastic Flow ◽  
Flow Network

The impact of China's import ban on global copper scrap flow network and the domestic copper sustainability

2021 ◽  
Vol 169 ◽  
pp. 105525
Author(s):  
Sen Liu ◽  
Wei Liu ◽  
Quanyin Tan ◽  
Jinhui Li ◽  
Wenqing Qin ◽  
...  
Keyword(s):  
Flow Network ◽  
The Impact

Optimal Reliability and Cost of Non-Repairable Systems Subject to Two Failure Modes Considering Correlated Failures

2018 ◽  
Vol 25 (05) ◽  
pp. 1850024
Author(s):  
Anusha Krishna Murthy ◽  
Saikath Bhattacharya ◽  
Lance Fiondella
Keyword(s):  
Failure Mode ◽  
System Reliability ◽  
Failure Modes ◽  
Optimal Number ◽  
Optimal Designs ◽  
Repairable Systems ◽  
Independent Manner ◽  
Reliability Models ◽  
Correlated Failures ◽  
The Impact

Most reliability models assume that components and systems experience one failure mode. Several systems such as hardware, however, are prone to more than one mode of failure. Past two-failure mode research derives equations to maximize reliability or minimize cost by identifying the optimal number of components. However, many if not all of these equations are derived from models that make the simplifying assumption that components fail in a statistically independent manner. In this paper, models to assess the impact of correlation on two-failure mode system reliability and cost are developed and corresponding expressions for reliability and cost optimal designs derived. Our illustrations demonstrate that, despite correlation, the approach identifies reliability and cost optimal designs.

A Comparative Study of Different Approaches for Finding the Upper Boundary Points in Stochastic-Flow Networks

2014 ◽  
Vol 10 (3) ◽  
pp. 13-23 ◽  
Author(s):  
Seyed Mehdi Mansourzadeh ◽  
Seyed Hadi Nasseri ◽  
Majid Forghani-elahabad ◽  
Ali Ebrahimnejad
Keyword(s):  
Information System ◽  
Comparative Study ◽  
Test Problems ◽  
Stochastic Flow ◽  
Flow Networks ◽  
Flow Network ◽  
Random Test ◽  
Boundary Points ◽  
Exclusion Method ◽  
Upper Boundary

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approaches such as inclusion-exclusion method, sum of disjoint products, etc. However, most of the algorithms have been compared via complexity results or through one or two benchmark networks. Thus, comparing those algorithms through random test problems can be desired. Here, the authors first state a simple improved algorithm. Then, by generating a number of random test problems and implementing the algorithms in MATLAB, the proposed algorithm is demonstrated to be more efficient than some existing ones in medium-sized networks. The performance profile introduced by Dolan and More is used for analyzing the output of programs.

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