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Title: RAVEN. Dynamic Event Tree Approach Level III Milestone

Abstract

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. Inmore » the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.« less

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Idaho National Lab. (INL), Idaho Falls, ID (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1182224
Report Number(s):
INL/EXT-13-30332
DOE Contract Number:  
AC07-05ID14517
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; 97 MATHEMATICS AND COMPUTING; 42 ENGINEERING; Dynamic Event Tree; PRA; RAVEN; UNCERTAINTY

Citation Formats

Alfonsi, Andrea, Rabiti, Cristian, Mandelli, Diego, Cogliati, Joshua, and Kinoshita, Robert. RAVEN. Dynamic Event Tree Approach Level III Milestone. United States: N. p., 2014. Web. doi:10.2172/1182224.
Alfonsi, Andrea, Rabiti, Cristian, Mandelli, Diego, Cogliati, Joshua, & Kinoshita, Robert. RAVEN. Dynamic Event Tree Approach Level III Milestone. United States. https://doi.org/10.2172/1182224
Alfonsi, Andrea, Rabiti, Cristian, Mandelli, Diego, Cogliati, Joshua, and Kinoshita, Robert. 2014. "RAVEN. Dynamic Event Tree Approach Level III Milestone". United States. https://doi.org/10.2172/1182224. https://www.osti.gov/servlets/purl/1182224.
@article{osti_1182224,
title = {RAVEN. Dynamic Event Tree Approach Level III Milestone},
author = {Alfonsi, Andrea and Rabiti, Cristian and Mandelli, Diego and Cogliati, Joshua and Kinoshita, Robert},
abstractNote = {Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.},
doi = {10.2172/1182224},
url = {https://www.osti.gov/biblio/1182224}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jul 01 00:00:00 EDT 2014},
month = {Tue Jul 01 00:00:00 EDT 2014}
}