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RAVEN as Control Logic and Probabilistic Risk Assessment Driver for RELAP-7

Description: The Next Generation of System Analysis Code (NGSAC) [1] aims to model and simulate the Nuclear Power Plant (NPP) thermo-hydraulic behavior with high level of accuracy. In this respect, Idaho National Laboratory (INL) is developing a NGSAC (known as RELAP-7) which will allow to model NPP responses for a set of accident scenarios (e.g., loss of off-site power).
Date: November 1, 2012
Creator: Rabiti, C.; Alfonsi, A.; Mandelli, D.; Cogliati, J. & Martineau, R.
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Partner: UNT Libraries Government Documents Department
open access

RAVEN AS A TOOL FOR DYNAMIC PROBABILISTIC RISK ASSESSMENT: SOFTWARE OVERVIEW

Description: RAVEN is a software tool under development at the Idaho National Laboratory (INL) that acts as the control logic driver and post-processing tool for the newly developed Thermo-Hydraylic code RELAP- 7. The scope of this paper is to show the software structure of RAVEN and its utilization in connection with RELAP-7. A short overview of the mathematical framework behind the code is presented along with its main capabilities such as on-line controlling/monitoring and Monte-Carlo sampling. A demo of… more
Date: May 1, 2013
Creator: Andrea, Alfonsi; Diego, Mandelli; Cristian, Rabiti; Cogliati, Joshua & Kinoshita, Robert
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Partner: UNT Libraries Government Documents Department
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Adaptive Sampling using Support Vector Machines

Description: Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the devel… more
Date: November 1, 2012
Creator: Mandelli, D. & Smith, C.
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Partner: UNT Libraries Government Documents Department
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MINING NUCLEAR TRANSIENT DATA THROUGH SYMBOLIC CONVERSION

Description: Dynamic Probabilistic Risk Assessment (DPRA) methodologies generate enormous amounts of data for a very large number of simulations. The data contain temporal information of both the state variables of the simulator and the temporal status of specific systems/components. In order to measure system performances, limitations and resilience, such data need to be carefully analyzed with the objective of discovering the correlations between sequence/timing of events and system dynamics. A first appr… more
Date: September 1, 2013
Creator: MAndelli, Diego; Aldemir, Tunc; Yilmaz, Alper & Smith, Curtis
Item Type: Refine your search to only Article
Partner: UNT Libraries Government Documents Department
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New Methods and Tools to Perform Safety Analysis within RISMC

Description: The Risk Informed Safety Margins Characterization (RISMC) Pathway uses a systematic approach developed to characterize and quantify safety margins of nuclear power plant structures, systems and components. What differentiates the RISMC approach from traditional probabilistic risk assessment (PRA) is the concept of safety margin. In PRA, a safety metric such as core damage frequency (CDF) is generally estimated using static fault-tree and event-tree models. However, it is not possible to estimat… more
Date: November 1, 2013
Creator: Mandelli, Diego; Smith, Curtis; Rabiti, Cristian; Alfonsi, Andrea; Kinoshita, Robert & Cogliati, Joshua
Item Type: Refine your search to only Article
Partner: UNT Libraries Government Documents Department
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