Risk assessment for dynamic systems: An overview

Siu, Nathan

doi:10.1016/0951-8320(94)90095-7

Cited by 226 publications

(64 citation statements)

References 36 publications

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“…Dynamic reliability [2][3][4][5] originated from the observation that classical PSA techniques could hardly deal with accidental sequences presenting strongly dynamic aspects. This advanced approach to reliability problems was thereby developed to model the interaction between the dynamic evolution of a system in the course of a transient and the transitions between system states that define an accident sequence.…”

Section: Dynamic Reliability and Monte Carlo Simulationmentioning

confidence: 99%

“…actual inlet temperature of HNO 3 . The evolution of x 1 is a given increasing function of time, between two values T 0 and T 1 , and it represents the initiating event.…”

Section: Appendix B Physical Modelmentioning

confidence: 99%

“…In such situations, where the dynamic aspects of the transient come into play, the safety analysis should be conducted using a dynamic reliability approach [2][3][4][5]. Therefore, the corresponding optimization algorithm consists in the combination of the following three computational stages:…”

Section: Introductionmentioning

confidence: 99%

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Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

Bourgeois

Labeau

2001

Reliability Engineering & System Safety

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On one hand, PSA results are increasingly used in decision making, system management and optimization of system design. On the other hand, when severe accidental transients are considered, dynamic reliability appears appropriate to account for the complex interaction between the transitions between hardware configurations, the operator behavior and the dynamic evolution of the system. This paper presents an exploratory work in which the estimation of the system unreliability in a dynamic context is coupled with an optimization algorithm to determine the "best" safety policy. Because some reliability parameters are likely to be distributed, the cost function to be minimized turns out to be a random variable. Stochastic programming techniques are therefore envisioned to determine an optimal strategy. Monte Carlo simulation is used at all stages of the computations, from the estimation of the system unreliability to that of the stochastic quasi-gradient. The optimization algorithm is illustrated on a HNO 3 supply system. ᭧

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Section: Dynamic Reliability and Monte Carlo Simulationmentioning

confidence: 99%

“…actual inlet temperature of HNO 3 . The evolution of x 1 is a given increasing function of time, between two values T 0 and T 1 , and it represents the initiating event.…”

Section: Appendix B Physical Modelmentioning

confidence: 99%

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Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

Bourgeois

Labeau

2001

Reliability Engineering & System Safety

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“…For example, Cai et al (2013) demonstrated the application of a DBN in BOP reliability analysis by converting one of Holand's FTA models. Another interesting class of dynamic reliability analysis is referred to as 'multiphase' or 'phase mission system' (PMS) analysis (Siu (1994). This is analysis where the system model consists of a set of sub-models that are consecutively linked together over the (mission) timeline.…”

Section: Ntnu Department Of Production and Quality Engineering Tronmentioning

confidence: 99%

Risk control in the well drilling phase: BOP system reliability assessment

Strand¹,

Lundteigen²

2015

Safety and Reliability of Complex Engineered Systems

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“…In many complex systems, however, the timing of the events and the dynamics of the system are key to understanding the effects of failures. As a result, there has been much work on dynamic reliability techniques using a combination of continuous, discrete and stochastic models (including hybrid automata models [35]) in conjunction with techniques such as Monte-Carlo simulation for predicting failure probabilities [42]. Formal Dependability Analysis There has been much recent progress in the use of formal verification techniques such as model checking for automating dynamic dependability analyses [7,8].…”

Section: Dependability Analysismentioning

confidence: 99%

Model-Based Dependability Analysis of Programmable Drug Infusion Pumps

Sankaranarayanan

Homaei

Lewis

2011

Lecture Notes in Computer Science

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Abstract. Infusion pumps are commonly used in home/hospital care to inject drugs into a patient at programmable rates over time. However, in practice, a combination of faults including software errors, mechanical failures and human error can lead to catastrophic situations, causing death or serious harm to the patient. Dependability analysis techniques such as failure mode effect analysis (FMEA) can be used to predict the worst case outcomes of such faults and facilitate the development of remedies against them. In this paper, we present the use of model-checking to automate the dependability analysis of programmable, real-time medical devices. Our approach uses timed and hybrid automata to model the real-time operation of the medical device and its interactions with the care giver and the patient. Common failure modes arising from device failures and human error are modeled in our framework. Specifically, we use "mistake models" derived from human factor studies to model the effects of mistakes committed by the operator. We present a case-study involving an infusion pump used to manage pain through the infusion of analgesic drugs. The dynamics of analgesic drugs are modeled by empirically validated pharmacokinetic models. Using model checking, our technique can systematically explore numerous combinations of failures and characterize the worse case effects of these failures.

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Risk assessment for dynamic systems: An overview

Cited by 226 publications

References 36 publications

Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

Risk control in the well drilling phase: BOP system reliability assessment

Model-Based Dependability Analysis of Programmable Drug Infusion Pumps

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