A framework to integrate software behavior into dynamic probabilistic risk assessment

Zhu, Dachang; Mosleh, Ali; Smidts, Carol

doi:10.1016/j.ress.2006.09.024

Cited by 22 publications

(12 citation statements)

References 24 publications

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“…In addition the methods utilized in [34] are based on a dynamic PRA philosophy rather than on integration of software contributions into the classic PRA framework (master logic diagram, event sequence diagrams, or event trees and fault trees) which is the object of this paper. For other related research on integrating software into dynamic PRA, see [35]. A methodology to consider software risk assessment at the system level is thus needed, especially regarding how the software fails, how the software allows failures to propagate at the system level, and how the software should be modelled and quantified in accident sequences.…”

Section: Related Workmentioning

confidence: 99%

Probabilistic risk assessment framework for software propagation analysis of failures

Wei

Rodrı́guez

Smidts

2010

Proceedings of the Institution of Mechanical Engineers, Part O:

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Probabilistic risk assessment (PRA) is a methodology consisting of techniques to assess the probability of failure or success of a system. It has been proven to be a systematic, logical, and comprehensive methodology for risk assessment. However, the contribution of software to risk has not been well studied. To address this shortcoming, recent research has focused on the development of an approach to systematically integrate software risk contributions into the PRA framework. The latter research has identified as key the need to quantify various major software-failure-related contributions to risk. Of these contributions, the quantification of input failures is the topic of this paper. An input failure consists of a failure of a system component directly or indirectly connected to a software component, which reaches the software input and propagates through the software component. The paper studies and quantifies the impact of input failures on the software component and then further on in the system, and outlines a framework to systematically conduct such an analysis. An application to a safety-critical system is also provided that illustrates the application of the concepts introduced in the paper.

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Section: Related Workmentioning

confidence: 99%

Probabilistic risk assessment framework for software propagation analysis of failures

Wei

Rodrı́guez

Smidts

2010

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…High demand or continuous mode of operation (Probability of a dangerous failure per hour) 9 In signal control system, the key protection subsystems, such as automatic train protection (ATP) and the computer interlocking system should meet the safety requirements of SIL4. And the automatic train operation (ATO) and automatic train monitoring subsystem (ATS) should meet the requirements of SIL2 or higher.…”

Section: Safety Integrity Levelmentioning

confidence: 99%

The FTA based safety analysis method for urban transit signal system

Pan

Zhang

et al. 2011

The Proceedings of 2011 9th International Conference on Reliability, Maintainability and Safety

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As an effective means of solution to traffic congestion, the modern urban transit has attracted worldwide attention. The signal control system, the core parts of the urban transit, is a typical safety critical system which ensures the safe operation and improves the transport efficiency. Therefore, the safety of the system must be analyzed during the development, production, and evaluation processes. Due to the system itself, operating environment, staff operation and other factors, the different failure modes which impact the system reliability and safety will occur during operating of the signal system. According to the system functionalities and system structures, the failure reasons can be analyzed layer by layer to improve the system design and performance. This paper suggests a safety analyze method for the signal system on the basis of the technical features using fault tree methods, and gives the proposals to improve system design.

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“…However, to make a simple model that only simulates the reliability behavior of the software, hardware and human elements of simulation without presenting other unnecessary aspects of these elements, several modeling techniques are developed and suggested for the SimPRA environment. Please refer to Mosleh et al, 2004;Zhu et al, 2006) for more details.…”

Section: Simulatormentioning

confidence: 99%

“…SimPRA, a simulation-based Dynamic Probabilistic Risk Assessment method is a framework accompanied by a prototype software tool developed at the University of Maryland to take on this challenge Mosleh et al, 2004;Nejad and Mosleh, 2005;Zhu et al, 2006). A hierarchical planning engine generates high level risk scenarios automatically.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical planning and multi-level scheduling for simulation-based probabilistic risk assessment

Nejad¹,

Zhu²,

Mosleh³

2007

2007 Winter Simulation Conference

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Simulation of dynamic complex systems-specifically, those comprised of large numbers of components with stochastic behaviors-for the purpose of probabilistic risk assessment faces challenges in every aspect of the problem. Scenario generation confronts many impediments, one being the problem of handling the large number of scenarios without compromising completeness. Probability estimation and consequence determination processes must also be performed under real world constraints on time and resources. In the approach outlined in this paper, hierarchical planning is utilized to generate a relatively small but complete group of risk scenarios to represent the unsafe behaviors of the system. Multi-level scheduling makes the probability estimation and consequence determination processes more efficient and affordable. The scenario generation and scheduling processes both benefit from an updating process that takes place after a number of simulation runs by fine-tuning the scheduler's level adjustment parameters and refining the planner's high level system model.

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A framework to integrate software behavior into dynamic probabilistic risk assessment

Cited by 22 publications

References 24 publications

Probabilistic risk assessment framework for software propagation analysis of failures

Probabilistic risk assessment framework for software propagation analysis of failures

The FTA based safety analysis method for urban transit signal system

Hierarchical planning and multi-level scheduling for simulation-based probabilistic risk assessment

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