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Tatsuya Sakurahara - One of the best experts on this subject based on the ideXlab platform.
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global importance measure methodology for integrated Probabilistic Risk Assessment
Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk and Reliability, 2020Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra MohagheghAbstract:An integrated Probabilistic Risk Assessment framework combines spatio-temporal Probabilistic simulations of underlying failure mechanisms with classical Probabilistic Risk Assessment logic consisti...
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an algorithm for enhancing spatiotemporal resolution of Probabilistic Risk Assessment to address emergent safety concerns in nuclear power plants
Reliability Engineering & System Safety, 2019Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Justin Pence, Zahra MohagheghAbstract:Abstract Emergent safety concerns often involve complex spatiotemporal phenomena. In addressing these concerns, the classical Probabilistic Risk Assessment (PRA) of Nuclear Power Plants (NPPs) has limitations in generating the required resolution for Risk estimations. The existing dynamic PRAs have yet to demonstrate their feasibility for implementation in a plant. In addition, due to the widespread use of classical PRA in the nuclear industry and by the regulatory agency, a transition to a fully dynamic PRA would require a significant investment of resources. As a more feasible alternative, the authors have developed the Integrated PRA (I-PRA) methodology to add realism to Risk estimations by explicitly incorporating time and space into underlying models of the events in the plant PRA while avoiding significant changes to its structure. In I-PRA, the failure mechanisms associated with the areas of concern (e.g., fire, Generic Safety Issue 191) were modeled in separate simulation modules, which were then integrated with the plant PRA through a Probabilistic interface. This paper (i) provides theoretical foundations for the incorporation of time and space into PRA and (ii) introduces an algorithm that helps execute I-PRA in a way to gradually enhance spatiotemporal resolution of plant PRAs to efficiently address emergent safety concerns.
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methodological and practical comparison of integrated Probabilistic Risk Assessment i pra with the existing fire pra of nuclear power plants
Nuclear Technology, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Zahra Mohaghegh, Ernie KeeAbstract:AbstractNearly half of the U.S. nuclear power plants (NPPs) are in the process of transitioning, or have already transitioned, to a Risk-informed, performance-based fire protection program. For this transition, Fire Probabilistic Risk Assessment (Fire PRA) is used as a foundation for fire Risk evaluation. To increase realism in Fire PRA by reducing conservative bias, the authors have developed an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework that does not require major changes to the existing plant Probabilistic Risk Assessments (PRAs). The underlying failure mechanism models associated with fire events are developed in a separate module, which can be interfaced and connected to the existing plant PRA. This paper explains the areas of methodological advancements in I-PRA, comparing them with the existing Fire PRA of NPPs. This comparison is further demonstrated in a realistic case study that applies the I-PRA framework to a critical fire-induced scenario at an NPP. The core dam...
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an integrated methodology for spatio temporal incorporation of underlying failure mechanisms into fire Probabilistic Risk Assessment of nuclear power plants
Reliability Engineering & System Safety, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, Shawn RodgersAbstract:Abstract In this research, an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework for Fire PRA is developed to provide a unified multi-level Probabilistic integration, beginning with spatio-temporal simulation-based models of underlying failure mechanisms (i.e., physical phenomena and human actions), connecting to component-level failures, and then linking to system-level Risk scenarios in classical PRA. The simulation-based module, called the fire simulation module (FSM), includes state-of-the-art models of fire initiation, fire progression, post-fire failure damage propagation, fire brigade response, and scenario-based damage. Fire progression is simulated using a CFD code, fire dynamics simulator (FDS), which solves Navier–Stokes equations governing the turbulent flow field. Uncertainty quantification is conducted to address parameter uncertainties. The I-PRA paves the way for reducing excessive conservatisms derived from the modeling of (i) fire progression and damage and (ii) the interactions between fire progression and manual suppression. Global importance measure analysis is used to rank the Risk-contributing factors. A case study demonstrates the implementation of I-PRA for a regulatory-documented fire scenario.
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developing a new fire pra framework by integrating Probabilistic Risk Assessment with a fire simulation module
12th International Probabilistic Safety Assessment and Management Conference PSAM 2014, 2014Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, David W Johnson, Shawn Rodgers, Mary Anne BillingsAbstract:Recently, the fire protection programs at nuclear power plants have been transitioned to a Risk-informed approach utilizing Fire Probabilistic Risk Assessment (Fire PRA). One of the main limitations of the current methodology is that it is not capable of adequately accounting for the dynamic behavior and effects of fire due to its reliance on the classical PRA methodology (i.e., Event Trees and Fault Trees). As a solution for this limitation, in this paper we propose an integrated framework for Fire PRA. This method falls midway between a classical and a fully dynamic PRA with respect to the utilization of simulation techniques. In the integrated framework, some of the fire-related Fault Trees are replaced with a Fire Simulation Module (FSM) , which is linked to a plant-specific PRA model. The FSM is composed of simulation-based physical models for fire initiation, progression, and post-fire failure. Moreover, FSM includes the uncertainty propagation in the physical models and input parameters. These features will reduce the unnecessary conservativeness in the current Fire PRA methodology by modeling the underlying physical phenomena and by considering the dynamic interactions among them.
Zahra Mohaghegh - One of the best experts on this subject based on the ideXlab platform.
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global importance measure methodology for integrated Probabilistic Risk Assessment
Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk and Reliability, 2020Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra MohagheghAbstract:An integrated Probabilistic Risk Assessment framework combines spatio-temporal Probabilistic simulations of underlying failure mechanisms with classical Probabilistic Risk Assessment logic consisti...
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an algorithm for enhancing spatiotemporal resolution of Probabilistic Risk Assessment to address emergent safety concerns in nuclear power plants
Reliability Engineering & System Safety, 2019Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Justin Pence, Zahra MohagheghAbstract:Abstract Emergent safety concerns often involve complex spatiotemporal phenomena. In addressing these concerns, the classical Probabilistic Risk Assessment (PRA) of Nuclear Power Plants (NPPs) has limitations in generating the required resolution for Risk estimations. The existing dynamic PRAs have yet to demonstrate their feasibility for implementation in a plant. In addition, due to the widespread use of classical PRA in the nuclear industry and by the regulatory agency, a transition to a fully dynamic PRA would require a significant investment of resources. As a more feasible alternative, the authors have developed the Integrated PRA (I-PRA) methodology to add realism to Risk estimations by explicitly incorporating time and space into underlying models of the events in the plant PRA while avoiding significant changes to its structure. In I-PRA, the failure mechanisms associated with the areas of concern (e.g., fire, Generic Safety Issue 191) were modeled in separate simulation modules, which were then integrated with the plant PRA through a Probabilistic interface. This paper (i) provides theoretical foundations for the incorporation of time and space into PRA and (ii) introduces an algorithm that helps execute I-PRA in a way to gradually enhance spatiotemporal resolution of plant PRAs to efficiently address emergent safety concerns.
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methodological and practical comparison of integrated Probabilistic Risk Assessment i pra with the existing fire pra of nuclear power plants
Nuclear Technology, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Zahra Mohaghegh, Ernie KeeAbstract:AbstractNearly half of the U.S. nuclear power plants (NPPs) are in the process of transitioning, or have already transitioned, to a Risk-informed, performance-based fire protection program. For this transition, Fire Probabilistic Risk Assessment (Fire PRA) is used as a foundation for fire Risk evaluation. To increase realism in Fire PRA by reducing conservative bias, the authors have developed an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework that does not require major changes to the existing plant Probabilistic Risk Assessments (PRAs). The underlying failure mechanism models associated with fire events are developed in a separate module, which can be interfaced and connected to the existing plant PRA. This paper explains the areas of methodological advancements in I-PRA, comparing them with the existing Fire PRA of NPPs. This comparison is further demonstrated in a realistic case study that applies the I-PRA framework to a critical fire-induced scenario at an NPP. The core dam...
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an integrated methodology for spatio temporal incorporation of underlying failure mechanisms into fire Probabilistic Risk Assessment of nuclear power plants
Reliability Engineering & System Safety, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, Shawn RodgersAbstract:Abstract In this research, an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework for Fire PRA is developed to provide a unified multi-level Probabilistic integration, beginning with spatio-temporal simulation-based models of underlying failure mechanisms (i.e., physical phenomena and human actions), connecting to component-level failures, and then linking to system-level Risk scenarios in classical PRA. The simulation-based module, called the fire simulation module (FSM), includes state-of-the-art models of fire initiation, fire progression, post-fire failure damage propagation, fire brigade response, and scenario-based damage. Fire progression is simulated using a CFD code, fire dynamics simulator (FDS), which solves Navier–Stokes equations governing the turbulent flow field. Uncertainty quantification is conducted to address parameter uncertainties. The I-PRA paves the way for reducing excessive conservatisms derived from the modeling of (i) fire progression and damage and (ii) the interactions between fire progression and manual suppression. Global importance measure analysis is used to rank the Risk-contributing factors. A case study demonstrates the implementation of I-PRA for a regulatory-documented fire scenario.
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developing a new fire pra framework by integrating Probabilistic Risk Assessment with a fire simulation module
12th International Probabilistic Safety Assessment and Management Conference PSAM 2014, 2014Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, David W Johnson, Shawn Rodgers, Mary Anne BillingsAbstract:Recently, the fire protection programs at nuclear power plants have been transitioned to a Risk-informed approach utilizing Fire Probabilistic Risk Assessment (Fire PRA). One of the main limitations of the current methodology is that it is not capable of adequately accounting for the dynamic behavior and effects of fire due to its reliance on the classical PRA methodology (i.e., Event Trees and Fault Trees). As a solution for this limitation, in this paper we propose an integrated framework for Fire PRA. This method falls midway between a classical and a fully dynamic PRA with respect to the utilization of simulation techniques. In the integrated framework, some of the fire-related Fault Trees are replaced with a Fire Simulation Module (FSM) , which is linked to a plant-specific PRA model. The FSM is composed of simulation-based physical models for fire initiation, progression, and post-fire failure. Moreover, FSM includes the uncertainty propagation in the physical models and input parameters. These features will reduce the unnecessary conservativeness in the current Fire PRA methodology by modeling the underlying physical phenomena and by considering the dynamic interactions among them.
Seyed Reihani - One of the best experts on this subject based on the ideXlab platform.
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global importance measure methodology for integrated Probabilistic Risk Assessment
Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk and Reliability, 2020Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra MohagheghAbstract:An integrated Probabilistic Risk Assessment framework combines spatio-temporal Probabilistic simulations of underlying failure mechanisms with classical Probabilistic Risk Assessment logic consisti...
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an algorithm for enhancing spatiotemporal resolution of Probabilistic Risk Assessment to address emergent safety concerns in nuclear power plants
Reliability Engineering & System Safety, 2019Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Justin Pence, Zahra MohagheghAbstract:Abstract Emergent safety concerns often involve complex spatiotemporal phenomena. In addressing these concerns, the classical Probabilistic Risk Assessment (PRA) of Nuclear Power Plants (NPPs) has limitations in generating the required resolution for Risk estimations. The existing dynamic PRAs have yet to demonstrate their feasibility for implementation in a plant. In addition, due to the widespread use of classical PRA in the nuclear industry and by the regulatory agency, a transition to a fully dynamic PRA would require a significant investment of resources. As a more feasible alternative, the authors have developed the Integrated PRA (I-PRA) methodology to add realism to Risk estimations by explicitly incorporating time and space into underlying models of the events in the plant PRA while avoiding significant changes to its structure. In I-PRA, the failure mechanisms associated with the areas of concern (e.g., fire, Generic Safety Issue 191) were modeled in separate simulation modules, which were then integrated with the plant PRA through a Probabilistic interface. This paper (i) provides theoretical foundations for the incorporation of time and space into PRA and (ii) introduces an algorithm that helps execute I-PRA in a way to gradually enhance spatiotemporal resolution of plant PRAs to efficiently address emergent safety concerns.
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methodological and practical comparison of integrated Probabilistic Risk Assessment i pra with the existing fire pra of nuclear power plants
Nuclear Technology, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Zahra Mohaghegh, Ernie KeeAbstract:AbstractNearly half of the U.S. nuclear power plants (NPPs) are in the process of transitioning, or have already transitioned, to a Risk-informed, performance-based fire protection program. For this transition, Fire Probabilistic Risk Assessment (Fire PRA) is used as a foundation for fire Risk evaluation. To increase realism in Fire PRA by reducing conservative bias, the authors have developed an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework that does not require major changes to the existing plant Probabilistic Risk Assessments (PRAs). The underlying failure mechanism models associated with fire events are developed in a separate module, which can be interfaced and connected to the existing plant PRA. This paper explains the areas of methodological advancements in I-PRA, comparing them with the existing Fire PRA of NPPs. This comparison is further demonstrated in a realistic case study that applies the I-PRA framework to a critical fire-induced scenario at an NPP. The core dam...
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an integrated methodology for spatio temporal incorporation of underlying failure mechanisms into fire Probabilistic Risk Assessment of nuclear power plants
Reliability Engineering & System Safety, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, Shawn RodgersAbstract:Abstract In this research, an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework for Fire PRA is developed to provide a unified multi-level Probabilistic integration, beginning with spatio-temporal simulation-based models of underlying failure mechanisms (i.e., physical phenomena and human actions), connecting to component-level failures, and then linking to system-level Risk scenarios in classical PRA. The simulation-based module, called the fire simulation module (FSM), includes state-of-the-art models of fire initiation, fire progression, post-fire failure damage propagation, fire brigade response, and scenario-based damage. Fire progression is simulated using a CFD code, fire dynamics simulator (FDS), which solves Navier–Stokes equations governing the turbulent flow field. Uncertainty quantification is conducted to address parameter uncertainties. The I-PRA paves the way for reducing excessive conservatisms derived from the modeling of (i) fire progression and damage and (ii) the interactions between fire progression and manual suppression. Global importance measure analysis is used to rank the Risk-contributing factors. A case study demonstrates the implementation of I-PRA for a regulatory-documented fire scenario.
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developing a new fire pra framework by integrating Probabilistic Risk Assessment with a fire simulation module
12th International Probabilistic Safety Assessment and Management Conference PSAM 2014, 2014Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, David W Johnson, Shawn Rodgers, Mary Anne BillingsAbstract:Recently, the fire protection programs at nuclear power plants have been transitioned to a Risk-informed approach utilizing Fire Probabilistic Risk Assessment (Fire PRA). One of the main limitations of the current methodology is that it is not capable of adequately accounting for the dynamic behavior and effects of fire due to its reliance on the classical PRA methodology (i.e., Event Trees and Fault Trees). As a solution for this limitation, in this paper we propose an integrated framework for Fire PRA. This method falls midway between a classical and a fully dynamic PRA with respect to the utilization of simulation techniques. In the integrated framework, some of the fire-related Fault Trees are replaced with a Fire Simulation Module (FSM) , which is linked to a plant-specific PRA model. The FSM is composed of simulation-based physical models for fire initiation, progression, and post-fire failure. Moreover, FSM includes the uncertainty propagation in the physical models and input parameters. These features will reduce the unnecessary conservativeness in the current Fire PRA methodology by modeling the underlying physical phenomena and by considering the dynamic interactions among them.
Ali Mosleh - One of the best experts on this subject based on the ideXlab platform.
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dynamic Probabilistic Risk Assessment of decision making in emergencies for complex systems case study dynamic positioning drilling unit
Ocean Engineering, 2021Co-Authors: Ingrid Bouwer Utne, Tarannom Parhizkar, Jan Erik Vinnem, Ali MoslehAbstract:Abstract Decision-making in emergency situations is a Risky and uncertain process due to the limited information and lack of time. Some key problem parameters, such as the time required to complete important response tasks, must be estimated and are therefore prone to errors. Other parameters, such as the probability of occurrence of a consequential event, will typically change as the response operation progresses. As a result, there should be a dynamic Probabilistic Risk Assessment framework to assess the Risk level of decision scenarios and facilitate the decision-making process. In this paper, a methodology for dynamic Probabilistic Risk Assessment of decision making in emergencies for complex marine systems is proposed. In this method, a dynamic event sequence diagram is introduced that helps to quantify events probabilities as a function of time, as well as environmental and operational variables, considering events interdependencies and uncertainties. In addition, the effects of time required 1 and time available 2 for performing a decision in emergency are considered in the Risk model. In this methodology, Probabilistic models including Bayesian network and Monte Carlo simulation are utilized to quantify the uncertain behavior of the decision-making process in complex marine systems. A computational study is also conducted to evaluate the methodology performance, in terms of effectiveness and efficiency. Computational results show that the proposed approach can obtain optimal solutions for large and practical problem sizes.
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Probabilistic Risk Assessment procedures guide for nasa managers and practitioners second edition
2011Co-Authors: Michael Stamatelatos, Ali Mosleh, Homayoon Dezfuli, George Apostolakis, Chester J Everline, Sergio B Guarro, Donovan Mathias, Todd Paulos, David Riha, Curtis SmithAbstract:Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing Risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA's objective is to better understand and effectively manage Risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. NASA intends to use Risk Assessment in its programs and projects to support optimal management decision making for the improvement of safety and program performance. In addition to using quantitative/Probabilistic Risk Assessment to improve safety and enhance the safety decision process, NASA has incorporated quantitative Risk Assessment into its system safety Assessment process, which until now has relied primarily on a qualitative representation of Risk. Also, NASA has recently adopted the Risk-Informed Decision Making (RIDM) process [1-1] as a valuable addition to supplement existing deterministic and experience-based engineering methods and tools. Over the years, NASA has been a leader in most of the technologies it has employed in its programs. One would think that PRA should be no exception. In fact, it would be natural for NASA to be a leader in PRA because, as a technology pioneer, NASA uses Risk Assessment and management implicitly or explicitly on a daily basis. NASA has Probabilistic safety requirements (thresholds and goals) for crew transportation system missions to the International Space Station (ISS) [1-2]. NASA intends to have Probabilistic requirements for any new human spaceflight transportation system acquisition. Methods to perform Risk and reliability Assessment in the early 1960s originated in U.S. aerospace and missile programs. Fault tree analysis (FTA) is an example. It would have been a reasonable extrapolation to expect that NASA would also become the world leader in the application of PRA. That was, however, not to happen. Early in the Apollo program, estimates of the probability for a successful roundtrip human mission to the moon yielded disappointingly low (and suspect) values and NASA became discouraged from further performing quantitative Risk analyses until some two decades later when the methods were more refined, rigorous, and repeatable. Instead, NASA decided to rely primarily on the Hazard Analysis (HA) and Failure Modes and Effects Analysis (FMEA) methods for system safety Assessment.
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hybrid causal methodology and software platform for Probabilistic Risk Assessment and safety monitoring of socio technical systems
Reliability Engineering & System Safety, 2010Co-Authors: Katrina M Groth, Chengdong Wang, Ali MoslehAbstract:Abstract This paper introduces an integrated framework and software platform for Probabilistic Risk Assessment (PRA) and safety monitoring of complex socio-technical systems. An overview of the three-layer hybrid causal logic (HCL) modeling approach and corresponding algorithms, implemented in the Trilith software platform, are provided. The HCL approach enhances typical PRA methods by quantitatively including the influence of soft causal factors introduced by human and organizational aspects of a system. The framework allows different modeling techniques to be used for different aspects of the socio-technical system. The HCL approach combines the power of traditional event sequence diagram (ESD)event tree (ET) and fault tree (FT) techniques for modeling deterministic causal paths, with the flexibility of Bayesian belief networks for modeling non-deterministic cause–effect relationships among system elements (suitable for modeling human and organizational influences). Trilith enables analysts to construct HCL models and perform quantitative Risk Assessment and management of complex systems. The Risk management capabilities included are HCL-based Risk importance measures, hazard identification and ranking, precursor analysis, safety indicator monitoring, and root cause analysis. This paper describes the capabilities of the Trilith platform and power of the HCL algorithm by use of example Risk models for a type of aviation accident (aircraft taking off from the wrong runway).
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incorporating organizational factors into Probabilistic Risk Assessment pra of complex socio technical systems a hybrid technique formalization
Reliability Engineering & System Safety, 2009Co-Authors: Zahra Mohaghegh, Reza Kazemi, Ali MoslehAbstract:This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and Risk Assessment, but the progress on techniques most suitable for organizational safety Risk frameworks has been limited. The focus of this paper is on the choice of “representational schemes†and “techniques.†A methodology for selecting appropriate candidate techniques and their integration in the form of a “hybrid†approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid techniques. The proposed hybrid approach integrates deterministic and Probabilistic modeling perspectives, and provides a flexible Risk management tool for complex socio-technical systems. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems. The example demonstrates how the hybrid method can be used to analyze the dynamic effects of organizational factors on system Risk.
Ernie Kee - One of the best experts on this subject based on the ideXlab platform.
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global importance measure methodology for integrated Probabilistic Risk Assessment
Proceedings of the Institution of Mechanical Engineers Part O: Journal of Risk and Reliability, 2020Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra MohagheghAbstract:An integrated Probabilistic Risk Assessment framework combines spatio-temporal Probabilistic simulations of underlying failure mechanisms with classical Probabilistic Risk Assessment logic consisti...
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methodological and practical comparison of integrated Probabilistic Risk Assessment i pra with the existing fire pra of nuclear power plants
Nuclear Technology, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Zahra Mohaghegh, Ernie KeeAbstract:AbstractNearly half of the U.S. nuclear power plants (NPPs) are in the process of transitioning, or have already transitioned, to a Risk-informed, performance-based fire protection program. For this transition, Fire Probabilistic Risk Assessment (Fire PRA) is used as a foundation for fire Risk evaluation. To increase realism in Fire PRA by reducing conservative bias, the authors have developed an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework that does not require major changes to the existing plant Probabilistic Risk Assessments (PRAs). The underlying failure mechanism models associated with fire events are developed in a separate module, which can be interfaced and connected to the existing plant PRA. This paper explains the areas of methodological advancements in I-PRA, comparing them with the existing Fire PRA of NPPs. This comparison is further demonstrated in a realistic case study that applies the I-PRA framework to a critical fire-induced scenario at an NPP. The core dam...
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an integrated methodology for spatio temporal incorporation of underlying failure mechanisms into fire Probabilistic Risk Assessment of nuclear power plants
Reliability Engineering & System Safety, 2018Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, Shawn RodgersAbstract:Abstract In this research, an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework for Fire PRA is developed to provide a unified multi-level Probabilistic integration, beginning with spatio-temporal simulation-based models of underlying failure mechanisms (i.e., physical phenomena and human actions), connecting to component-level failures, and then linking to system-level Risk scenarios in classical PRA. The simulation-based module, called the fire simulation module (FSM), includes state-of-the-art models of fire initiation, fire progression, post-fire failure damage propagation, fire brigade response, and scenario-based damage. Fire progression is simulated using a CFD code, fire dynamics simulator (FDS), which solves Navier–Stokes equations governing the turbulent flow field. Uncertainty quantification is conducted to address parameter uncertainties. The I-PRA paves the way for reducing excessive conservatisms derived from the modeling of (i) fire progression and damage and (ii) the interactions between fire progression and manual suppression. Global importance measure analysis is used to rank the Risk-contributing factors. A case study demonstrates the implementation of I-PRA for a regulatory-documented fire scenario.
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developing a new fire pra framework by integrating Probabilistic Risk Assessment with a fire simulation module
12th International Probabilistic Safety Assessment and Management Conference PSAM 2014, 2014Co-Authors: Tatsuya Sakurahara, Seyed Reihani, Ernie Kee, Zahra Mohaghegh, Mark D Brandyberry, David W Johnson, Shawn Rodgers, Mary Anne BillingsAbstract:Recently, the fire protection programs at nuclear power plants have been transitioned to a Risk-informed approach utilizing Fire Probabilistic Risk Assessment (Fire PRA). One of the main limitations of the current methodology is that it is not capable of adequately accounting for the dynamic behavior and effects of fire due to its reliance on the classical PRA methodology (i.e., Event Trees and Fault Trees). As a solution for this limitation, in this paper we propose an integrated framework for Fire PRA. This method falls midway between a classical and a fully dynamic PRA with respect to the utilization of simulation techniques. In the integrated framework, some of the fire-related Fault Trees are replaced with a Fire Simulation Module (FSM) , which is linked to a plant-specific PRA model. The FSM is composed of simulation-based physical models for fire initiation, progression, and post-fire failure. Moreover, FSM includes the uncertainty propagation in the physical models and input parameters. These features will reduce the unnecessary conservativeness in the current Fire PRA methodology by modeling the underlying physical phenomena and by considering the dynamic interactions among them.