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Reliability Assessment of Lifeline Systems with Radial Topology
Abstract: The increased susceptibility of lifeline systems to failure due to aging and external hazards requires efficient methods to quantify their reliability and related uncertainty. Monte Carlo simulation techniques for network‐level reliability and uncertainty assessment usually require large computational experiments. Also, available analytical approaches apply mainly to simple network topologies, and are limited to providing average values, low order moments, or confidence bounds of reliability metrics. This study introduces a closed form technique to obtain the entire probability distribution of a reliability metric of customer service availability (CSA) for generic radial lifeline systems. A special case of this general formulation reduces to a simple sum of products equation, for which a recursive algorithm that exploits its structure is presented. This special‐case algorithm computes the probability mass function (PMF) of CSA for systems with M elements in operations, relative to conventional operations, and opens the possibility of finding recursive algorithms for the general radial case. Parametric models that approximate the CSA metric are also explored and their errors quantified. The proposed radial topology reliability assessment tools and resulting probability distributions provide infrastructure owners with critical insights for informed operation and maintenance decision making under uncertainty.
Reliability Assessment of Lifeline Systems with Radial Topology
Abstract: The increased susceptibility of lifeline systems to failure due to aging and external hazards requires efficient methods to quantify their reliability and related uncertainty. Monte Carlo simulation techniques for network‐level reliability and uncertainty assessment usually require large computational experiments. Also, available analytical approaches apply mainly to simple network topologies, and are limited to providing average values, low order moments, or confidence bounds of reliability metrics. This study introduces a closed form technique to obtain the entire probability distribution of a reliability metric of customer service availability (CSA) for generic radial lifeline systems. A special case of this general formulation reduces to a simple sum of products equation, for which a recursive algorithm that exploits its structure is presented. This special‐case algorithm computes the probability mass function (PMF) of CSA for systems with M elements in operations, relative to conventional operations, and opens the possibility of finding recursive algorithms for the general radial case. Parametric models that approximate the CSA metric are also explored and their errors quantified. The proposed radial topology reliability assessment tools and resulting probability distributions provide infrastructure owners with critical insights for informed operation and maintenance decision making under uncertainty.
Reliability Assessment of Lifeline Systems with Radial Topology
Dueñas‐Osorio, Leonardo (Autor:in) / Rojo, Javier (Autor:in)
Computer‐Aided Civil and Infrastructure Engineering ; 26 ; 111-128
01.02.2011
18 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Reliability Assessment of Lifeline Systems with Radial Topology
Online Contents | 2011
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|Seismic topology optimization of lifeline systems
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|Seismic reliability of lifeline systems
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|Seismic Reliability Assessment of Critical Lifeline Equipment
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