Phenomena Identification and Ranking Table (PIRT) study for metallic structural materials for advanced High-Temperature reactor

Singh, Preet M.; Chan, Kevin J.; Deo, Chaitanya; Deodeshmukh, Vinay; Keiser, James R.; Ren, Weiju; Sham, T.-L.; Wilson, Daniel A.; Yoder, G.L.; Zhang, Jinsuo

doi:10.1016/j.anucene.2018.08.036

Cited by 15 publications

(3 citation statements)

References 18 publications

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“…A series of four white papers were released in 2013, providing a comprehensive review of the technology developed thus far for the FHR concept [71][72][73][74]. Additionally, considerable work has recently been completed in identifying important phenomena and knowledge gaps for neutronics, thermal hydraulics, and materials design for the modeling and simulation of a FHR [75][76][77][78][79], although the development of a mechanistic source term assessment has yet to be published. A summary diagram for radionuclide release paths in a generic saltcooled molten salt reactor is provided in Figure 3-2 [7].…”

Section: Salt-cooled Molten Salt Reactorsmentioning

confidence: 99%

Functional Requirements for the Modeling and Simulation of Advanced (Non-LWR) Reactor Mechanistic Source Term

Shahbazi

Grabaskas

2020

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Section: Salt-cooled Molten Salt Reactorsmentioning

confidence: 99%

Functional Requirements for the Modeling and Simulation of Advanced (Non-LWR) Reactor Mechanistic Source Term

Shahbazi

Grabaskas

2020

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“…b) Label Ranks: If limited resources hinder the labeling process, a ranking of labels based on some structured method e.g. Phenomena Identification and Ranking Table (PIRT) [16] can be used.…”

Section: Availability Of the Labeled Datamentioning

confidence: 99%

Discovery of Perception Performance Limiting Triggering Conditions in Automated Driving

Adee

Gansch

Liggesmeyer

et al. 2021

2021 5th International Conference on System Reliability and Safety (ICSRS)

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Highly automated driving (HAD) vehicles are complex systems operating in an open context. Performance limitations originating from sensing and understanding the open context under triggering conditions may result in unsafe behavior, thus, need to be identified and modeled. This aspect of safety is also discussed in standardization activities such as ISO 21448, safety of the intended functionality (SOTIF). Although SOTIF provides a non-exhaustive list of scenario factors to identify and analyze performance limitations under triggering conditions, no concrete methodology is yet provided to identify novel triggering conditions.We propose a methodology to identify and model novel triggering conditions in a scene in order to assess SOTIF using Bayesian network (BN) and p-value hypothesis testing. The experts provide the initial BN structure while the conditional belief tables (CBTs) are learned using dataset. P-value hypothesis testing is used to identify the relevant subset of scenes. These scenes are then analyzed by experts who provide potential triggering conditions present in the scenes. The novel triggering conditions are modeled in the BN and retested. As a case study, we provide p-value hypothesis testing of BN of LIDAR using real world data.

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“…Rahnema et al have published considerable literature on the phenomenology of FHRs, including the challenges in modeling and simulation of FHRs [174], the required level of multiphysics coupling corresponding to various phenomena [175], and important phenomena and gaps for neutronics modeling [176]. Similarly, Lin et al published a phenomena identification and ranking table (PIRT) for thermal hydraulics modeling [177], and Singh et al published a PIRT for metallic structural materials [178].…”

Section: Fluoride Salt-cooled High Temperature Reactorsmentioning

confidence: 99%

Survey and Assessment of Computational Capabilities for Advanced (Non-LWR) Reactor Mechanistic Source Term Analysis.

Clark¹,

Luxat²,

Higgins³

et al. 2020

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Phenomena Identification and Ranking Table (PIRT) study for metallic structural materials for advanced High-Temperature reactor

Cited by 15 publications

References 18 publications

Functional Requirements for the Modeling and Simulation of Advanced (Non-LWR) Reactor Mechanistic Source Term

Functional Requirements for the Modeling and Simulation of Advanced (Non-LWR) Reactor Mechanistic Source Term

Discovery of Perception Performance Limiting Triggering Conditions in Automated Driving

Survey and Assessment of Computational Capabilities for Advanced (Non-LWR) Reactor Mechanistic Source Term Analysis.

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