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Ahmad BahooToroody
University of Florence
Statistical modelReliability engineeringMetering modeBayesian networkNatural gas
6Publications
3H-index
39Citations
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Publications 6
Newest
#1Ahmad BahooToroody (UniFI: University of Florence)H-Index: 3
#2Filippo De Carlo (UniFI: University of Florence)H-Index: 5
Last. P.H.A.J.M. van Gelder (TU Delft: Delft University of Technology)H-Index: 22
view all 5 authors...
Abstract The probabilistic analysis on condition monitoring data has been widely established through the energy supply process to specify the optimum risk remediation program. In such studies, the fluctuations and uncertainties of the operational data including the variability between source of data and the correlation of observations, have to be incorporated if the efficiency is of importance. This study presents a novel probabilistic methodology based on observation data for signifying the imp...
Source
#1Ahmad BahooToroody (UniFI: University of Florence)H-Index: 3
#2Mohammad Mahdi Abaei (University of Exeter)H-Index: 7
Last. Rouzbeh Abbassi (Macquarie University)H-Index: 21
view all 7 authors...
Abstract Failure modelling and reliability assessment of repairable systems has been receiving a great deal of attention due to its pivotal role in risk and safety management of process industries. Meanwhile, the level of uncertainty that comes with characterizing the parameters of reliability models require a sound parameter estimator tool. For the purpose of comparison and cross-verification, this paper aims at identifying the most efficient and minimal variance parameter estimator. Hierarchic...
2 CitationsSource
#1Saeed KhalajH-Index: 2
Last. Rouzbeh Abbassi (Macquarie University)H-Index: 21
view all 6 authors...
Abstract Strong earthquakes lead to slopes instability in mountainous regions and subsequently trigger landslides. Landslides may cause serious damage to infrastructure such as roads and railways, and may also lead to human injuries and death. The severity of the direct and indirect consequences of damage caused by landslides is inevitable and needs a more reliable approach for risk analysis associated with this phenomenon. In this paper, a novel methodology is employed to estimate the probabili...
4 CitationsSource
#1Ahmad BahooToroody (UniFI: University of Florence)H-Index: 3
#2Mohammad Mahdi Abaei (University of Exeter)H-Index: 7
Last. Saeed KhalajH-Index: 2
view all 6 authors...
Abstract Condition monitoring of natural gas distribution networks is a fundamental prerequisite for evaluating safety of the operation during the lifetime of the system. Due to the high level of uncertainty in the observed data, predicting the operational reliability of the networks is complicated. Moreover, there is a fluctuation in most of the monitoring data in different time scales, as most of the derived data tend to be of non-stationary nature and are complex to model or forecast. Therefo...
1 CitationsSource
#1Ahmad BahooToroody (UniFI: University of Florence)H-Index: 3
#2Mohammad Mahdi Abaei (University of Exeter)H-Index: 7
Last. Rouzbeh Abbassi (Macquarie University)H-Index: 21
view all 6 authors...
Abstract In this paper, a risk-based optimization methodology for a maintenance schedule considering Process Variables (PVs), is developed within the framework of asset integrity assessment. To this end, an integration of Dynamic Bayesian Network, Damage Modelling and sensitivity analysis are implemented to clarify the behaviour of failure probability, considering the exogenous undisciplinable perturbations. Discrete time case is considered through measuring or observing the PVs. Decision config...
12 CitationsSource
#1Leonardo Leoni (UniFI: University of Florence)H-Index: 1
#2Ahmad BahooToroody (UniFI: University of Florence)H-Index: 3
Last. Nicola Paltrinieri (NTNU: Norwegian University of Science and Technology)H-Index: 15
view all 4 authors...
Abstract During the last decades, the vital role of maintenance activities in industries including natural gas distribution system has cleared up progressively. High costs may induce to reduced maintenance and, in turn, lead to a lower availability and high risk of undesired events. Therefore, a probabilistic model, based on an acceptable level of risk, is required to avoid under and over estimation of maintenance time interval. This paper presents an advanced Risk-based Maintenance (RBM) method...
6 CitationsSource
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