Development of a quantitative resilience model for nuclear power plants

Kim, Ji Tae; Park, Jooyoung; Kim, Jong-Hyun; Seong, Poong Hyun

doi:10.1016/j.anucene.2018.08.042

Cited by 19 publications

(5 citation statements)

References 11 publications

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“…Resilience Engineering is still in its early stages of development and its application in the nuclear industry is limited and not fully explored [2,3]. Differently from conventional risk assessment methods, resilience approaches aim to bypass the resilience on historical information making space for proactive solutions aiming at anticipating and planning for the unexpected.…”

Section: Resilience Engineeringmentioning

confidence: 99%

Resilience in the Context of Nuclear Safety Engineering

Yan

Tolo

Dunnett

et al. 2020

2020 Annual Reliability and Maintainability Symposium (RAMS)

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The safety and reliability of critical infrastructures is a key challenge in modern societies. This is all the more true when referring to the nuclear power industry, due to the rigid safety requirements on the one hand and the growing complexity of new systems on the other. The current study investigates the potential of a resilience engineering approach in dealing with current and future challenges in the context of nuclear reactor safety. The efficiency of several resilience metrics for capturing systems' performance in the case of accidents are discussed, and a novel framework for resilience analysis of nuclear reactor is proposed. The overall aim of this work is to provide computational and theoretical tools for resilience evaluation, paving the way for its application in the nuclear industry.

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Section: Resilience Engineeringmentioning

confidence: 99%

Resilience in the Context of Nuclear Safety Engineering

Yan

Tolo

Dunnett

et al. 2020

2020 Annual Reliability and Maintainability Symposium (RAMS)

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“…In this work we thus introduce the concept of quantitative resilience for control systems in order to measure the delays caused by the loss of control authority over actuators. While concepts of quantitative resilience have been previously developed for water infrastructure systems [17] or for nuclear power plants [11], such concepts only work for their specific application.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Resilience of Linear Driftless Systems

Bouvier

Ornik

2021

2021 Proceedings of the Conference on Control and Its Applications

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This paper introduces the notion of quantitative resilience of a control system. Following prior work, we study linear driftless systems enduring a loss of control authority over some of their actuators. Such a malfunction results in actuators producing possibly undesirable inputs over which the controller has real-time readings but no control. By definition, a system is resilient if it can still reach a target after a partial loss of control authority. However, after such a malfunction, a resilient system might be significantly slower to reach a target compared to its initial capabilities. We quantify this loss of performance through the new concept of quantitative resilience. We define such a metric as the maximal ratio of the minimal times required to reach any target for the initial and malfunctioning systems. Naïve computation of quantitative resilience directly from the definition is a complex task as it requires solving four nested, possibly nonlinear, optimization problems. The main technical contribution of this work is to provide an efficient method to compute quantitative resilience. Relying on control theory and on two novel geometric results we reduce the computation of quantitative resilience to a single linear optimization problem. We demonstrate our method on an opinion dynamics scenario.

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“…Previous work [1] introduced the concept of quantitative resilience for control systems in order to measure the delays caused by the loss of control authority over actuators. While concepts of quantitative resilience have been previously developed for water infrastructure systems [12] or for nuclear power plants [13], such concepts only work for their specific application.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Resilience of Generalized Integrators

Bouvier¹,

Xu²,

Ornik³

2021

Preprint

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To design critical systems engineers must be able to prove that their system can continue with its mission even after losing control authority over some of its actuators. Such a malfunction results in actuators producing possibly undesirable inputs over which the controller has real-time readings but no control. By definition, a system is resilient if it can still reach a target after a partial loss of control authority. However, after such a malfunction, a resilient system might be significantly slower to reach a target compared to its initial capabilities. To quantify this loss of performance we introduce the notion of quantitative resilience as the maximal ratio of the minimal times required to reach any target for the initial and malfunctioning systems. Naive computation of quantitative resilience directly from the definition is a complex task as it requires solving four nested, possibly nonlinear, optimization problems. The main technical contribution of this work is to provide an efficient method to compute quantitative resilience of control systems with multiple integrators and nonsymmetric input sets. Relying on control theory and on two novel geometric results we reduce the computation of quantitative resilience to a linear optimization problem. We illustrate our method on two numerical examples: a trajectory controller for low-thrust spacecrafts and a UAV with eight propellers.Index termsreachability, quantitative resilience, linear systems, optimization Notice of previous publication: This manuscript is a substantially extended version of [1] where we remove the assumption of symmetry on the input sets, leading to more general and more complex results, e.g., Theorems 1 and 2. This paper also provides several proofs omitted from [1] and tackle systems with multiple integrators. Entirely novel material includes Sections VII, VIII, Appendices A, B and parts of all other sections.

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Development of a quantitative resilience model for nuclear power plants

Cited by 19 publications

References 11 publications

Resilience in the Context of Nuclear Safety Engineering

Resilience in the Context of Nuclear Safety Engineering

Quantitative Resilience of Linear Driftless Systems

Quantitative Resilience of Generalized Integrators

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