Qualitative temporal analysis: Towards a full implementation of the Fault Tree Handbook

Walker, Martin; Papadopoulos, Yiannis

doi:10.1016/j.conengprac.2008.10.003

Cited by 81 publications

(77 citation statements)

References 9 publications

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“…3c shows the State Machine (SM) for the non-repairable PS system. For the dynamic qualitative analysis, Pandora and its temporal laws [11] are applied to the SM in Fig. 3c.…”

Section: Running Example: Repairable Ps Systemmentioning

confidence: 99%

“…HiP-HOPS failure expressions may include temporal operators in Pandora logic [11]. Pandora operators allow specifying sequence-dependent and relative temporal ordered events and thus modelling of dynamic systems.…”

Section: Overview Of Approachmentioning

confidence: 99%

“…These expressions may include redundant terms. Using the reduction rules in [11] the TFT minimization (#10) activity is performed. Redundant terms are removed and structure function is produced, which contains only non-redundant MCSQ sets.…”

Section: Overview Of Approachmentioning

confidence: 99%

“…Using algorithms, local effects of failure and repair are then propagated among all the interconnected components. In the course of this, and using Pandora temporal operators [11], sequences of failure and repair that lead to hazards are captured in Temporal Fault Trees (TFTs). TFTs are analysed and MCSQs are determined.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Explicit Modelling and Treatment of Repair in Prediction of Dependability

Aizpurua

Papadopoulos

Merle

2020

IEEE Trans. Dependable and Secure Comput.

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The Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Abstract-In engineering practice, multiple repair actions are considered carefully by designers, and their success or failure defines further control actions and the evolution of the system state. Such treatment is not fully supported by the current state-of-the-art in dependability analysis. We propose a novel approach for explicit modelling and analysis of repairable systems, and describe an implementation, which builds on HiP-HOPS, a method and tool for model-based synthesis of dependability evaluation models. HiP-HOPS is augmented with Pandora, a temporal logic for the qualitative analysis of Temporal Fault Trees (TFTs), and capabilities for quantitative dependability analysis via Stochastic Activity Networks (SAN). Dependability prediction is achieved via explicit modelling of local failure and repair events in a system model and then by: (i) propagation of local effects through the model and synthesis of repair-aware TFTs for the system, (ii) qualitative analysis of TFTs that respects both failure and repair logic and (iii) quantification of dependability via translation of repair-aware TFTs into SAN. The approach provides insight into the effects of multiple and alternative failure and repair scenarios, and can thus be useful in reconfigurable systems that typically employ software to utilise functional redundancies in a variety of ways.

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“…3c shows the State Machine (SM) for the non-repairable PS system. For the dynamic qualitative analysis, Pandora and its temporal laws [11] are applied to the SM in Fig. 3c.…”

Section: Running Example: Repairable Ps Systemmentioning

confidence: 99%

Section: Overview Of Approachmentioning

confidence: 99%

Section: Overview Of Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Explicit Modelling and Treatment of Repair in Prediction of Dependability

Aizpurua

Papadopoulos

Merle

2020

IEEE Trans. Dependable and Secure Comput.

Self Cite

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“…In dynamic dependability analysis we are interested in finding the minimal (temporal) combination of failures of assets that causes the system failure, i.e., minimal cut-sequence sets [23]. A number of techniques have been proposed for calculating these sets, so in this paper we will focus on the prognostic-updated quantification of already established minimal cut-sequence sets.…”

Section: An Approach To Dynamic Dependability Analysis Encompassimentioning

confidence: 99%

Improved Dynamic Dependability Assessment Through Integration With Prognostics

et al. 2017

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This version is available at https://strathprints.strath.ac.uk/60422/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Abstract-The use of average data for dependability assessments results in a outdated system-level dependability estimation which can lead to incorrect design decisions. With increasing availability of online data, there is room to improve traditional dependability assessment techniques. Namely, prognostics is an emerging field which provides asset-specific failure information which can be reused to improve the system level failure estimation. This paper presents a framework for prognosticsupdated dynamic dependability assessment. The dynamic behaviour comes from runtime updated information, asset interdependencies, and time-dependent system behaviour. A case study from the power generation industry is analysed and results confirm the validity of the approach for improved near real-time unavailability estimations.

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Probability and Frequency Derivation Using Dynamic Fault Trees

Hamaidia

Kara

Innal

2018

Process Safety Progress

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Dynamic Fault Tree (DFT) is suitable to capture functional and dynamic dependencies among events leading to system failure. There exist several approaches for analyzing DFTs, each of them suffers from drawbacks that limit its practical use. This paper presents a comprehensive methodology based on the structure function determination. It consists in performing both qualitative and quantitative analysis to establish failure sequences and to calculate the likelihood (probability and frequency) of dynamic systems failure. Failure sequences are extracted from the minimal canonical form of the top event and allow getting disjunctive failure sequences. From the quantitative point of view, the probability and frequency of any DFT top event are developed to make the proposed model able to quantify the failure probability and frequency of dynamic systems and the frequency of accident scenarios. The proposed procedure is applied on two benchmark examples: the first one is a safety‐related system while the second one is an accident scenario with dependent protection layers. In order to check the validity of the proposed method, the derived numerical results are compared with those obtained from Markov Chains models. © 2018 American Institute of Chemical Engineers Process Saf Prog 37: 535–552, 2018

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Qualitative temporal analysis: Towards a full implementation of the Fault Tree Handbook

Cited by 81 publications

References 9 publications

Explicit Modelling and Treatment of Repair in Prediction of Dependability

Explicit Modelling and Treatment of Repair in Prediction of Dependability

Improved Dynamic Dependability Assessment Through Integration With Prognostics

Probability and Frequency Derivation Using Dynamic Fault Trees

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