An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants

Bui, Ha; Sakurahara, Tatsuya; Pence, Justin; Reihani, Seyed; Kee, Ernie; Mohaghegh, Zahra

doi:10.1016/j.ress.2019.01.004

Cited by 18 publications

(11 citation statements)

References 46 publications

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“…Meanwhile, the Interface Module ('e' in Figure 11) in the I-PRA offers the possibility of reliably using dynamic simulation approaches linked with the existing PRA of aging plants. The I-PRA risk importance ranking offered in this report can provide valuable information for efficiently (i) enhancing the realism of Fire PRA for existing plants [77] and (ii) supporting the development of Fire DPRA for advanced reactors and new plants.…”

Section: Time Dependent Scenario Modelingmentioning

confidence: 99%

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Biersdorf

Bui

Sakurahara

et al. 2020

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Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools, and data for modeling this risk are highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data's high rate of uncertainty. This report outlines work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant PRA models. This research used the Integrated Probabilistic Risk Assessment (I-PRA) method and paves the way to correctly assess and reduce data uncertainty in fire modeling.

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Section: Time Dependent Scenario Modelingmentioning

confidence: 99%

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Biersdorf

Bui

Sakurahara

et al. 2020

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“…is applied to the reduced-order I-PRA developed for GSI-191. 12,23 This case study aims to demonstrate the applicability of S (CDF) i for a realistic I-PRA framework. GSI-191 is a safety issue for pressurized water reactors (PWRs), associated with accident scenarios following a loss-of-coolant accident (LOCA), where debris (e.g.…”

Section: Non-linear Fault Tree Modelmentioning

confidence: 99%

“…The tornado diagram for the non-linear fault tree model (equation (15)) with the input parameter distributions in Table 4, showing a different input parameter ranking by global IM and one-way SA. details on this I-PRA framework developed for GSI-191 were presented in Mohaghegh et al 12 and Bui et al 23 To demonstrate the applicability of the selected global IM method for I-PRA, this article develops a reduced-order I-PRA for GSI-191 ( Figure 7). This I-PRA is a ''reduced-order'' model, in that (a) the plantspecific PRA module utilizes a hypothetical and simplified PRA and (b) the scope of the simulation module (''reduced-order CASA'' in Figure 7) is limited, compared to the scope of the original CASA Grande.…”

Section: Non-linear Fault Tree Modelmentioning

confidence: 99%

“…11 Therefore, as a more feasible short-term alternative for practical risk-informed applications, the integrated probabilistic risk assessment (I-PRA) framework ( Figure 1) has been developed. [12][13][14][15][16][17][18][19][20][21][22][23] The I-PRA framework (Figure 1) incorporates the underlying science of accident causation (i.e. physical and social failure mechanisms) into classical PRA (plant-specific PRA module in Figure 1) associated with certain areas of safety concern, for example, internal fire 14,15,17,20,22 and Generic Safety Issue 191 (GSI-191), i.e., a sump blockage issue following a loss-of-coolant accident at an NPP.…”

Section: Introductionmentioning

confidence: 99%

“…physical and social failure mechanisms) into classical PRA (plant-specific PRA module in Figure 1) associated with certain areas of safety concern, for example, internal fire 14,15,17,20,22 and Generic Safety Issue 191 (GSI-191), i.e., a sump blockage issue following a loss-of-coolant accident at an NPP. 12,21,23 I-PRA is a multi-level risk assessment framework that begins with the simulation of dominant failure mechanisms (e.g. stress corrosion cracking, cavitation, and mechanical wear) associated with the primary physical failure modes (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Global importance measure methodology for integrated probabilistic risk assessment

Sakurahara

Reihani

Kee

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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An integrated probabilistic risk assessment framework combines spatio-temporal probabilistic simulations of underlying failure mechanisms with classical probabilistic risk assessment logic consisting of event trees and fault trees. The importance measure methods commonly used in classical probabilistic risk assessment, for example, Fussell–Vesely importance measure and Risk Achievement Worth, generate the ranking of components at the basic event level utilizing the one-at-a-time and local methods. These classical importance measure methods, however, are not sufficient for integrated probabilistic risk assessment where, in addition to the component-level risk importance ranking, the ranking of risk-contributing factors (e.g. physical design parameters) associated with the underlying failure mechanisms is desired. In this research, the global importance measure method is suggested and implemented for the integrated probabilistic risk assessment framework. The global importance measure can account for four key aspects of integrated probabilistic risk assessment, including (a) ranking of input parameters at the failure mechanism level based on the contribution to the system risk metrics, (b) uncertainty of input parameters, (c) non-linearity and interactions among input parameters inside the model, and (d) uncertainty associated with the system risk estimates; therefore, it enhances the accuracy of risk importance ranking when the risk model has a high level of non-linearity, interactions, and uncertainties. This article shows (a) qualitative justifications for the selection of the global importance measure method for the integrated probabilistic risk assessment framework and (b) quantitative proof of concept using three case studies, including two illustrative fault tree examples and one practical application of the integrated probabilistic risk assessment framework for Generic Safety Issue 191 at nuclear power plants (a sump blockage issue following a loss-of-coolant accident).

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Fire dynamics simulation in a cable spreading room of a nuclear power plant using fire test results of heat release and toxic gas emission

Lee,

Kim,

Jeong

et al. 2024

J Mech Sci Technol

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An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants

Cited by 18 publications

References 46 publications

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Global importance measure methodology for integrated probabilistic risk assessment

Fire dynamics simulation in a cable spreading room of a nuclear power plant using fire test results of heat release and toxic gas emission

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