69 research outputs found
Mathematical Framework for the Analysis of Dynamic Stochastic Systems with the RAVEN code
No full textRAVEN (Reactor Analysis and Virtual control Environment) is a software code under
development at Idaho National Laboratory aimed at performing probabilistic risk assessment and uncertainty quantification using RELAP-7, for which it acts also as a simulation controller. In this paper we will present the equations characterizing a dynamic stochastic system and we will then discuss the behavior of each stochastic term and how it is accounted for in the RAVEN software design. Moreover we will present preliminary results of the implementatio
Simulation of AER-DYN-002 and AER-DYN-003 Control Rod Ejection Benchmarks by RELAP5-3D/PHISICS Coupled Codes
No full textENEA “Casaccia” Research Center is collaborating with Idaho National Laboratory performing activities devoted to the validation of the Parallel and Highly Innovative Simulation for INL Code System (PHISICS) neutron simulation code. In such framework, the AER-DYN-002 and AER-DYN-003 control rod (CR) ejection benchmarks were used to validate the coupled codes RELAP5-3D/PHISICS. The AER-DYN-002 benchmark provides a test case of a CR ejection accident in a VVER-440 at hot-zero-power and end-of-cycle conditions assuming an adiabatic fuel and taking into account only the fuel temperature feedback. The AER-DYN-003 benchmark is based on the same problem; however, the moderator density feedback and the coolant heat removal are also considered. A RELAP5-3D core channel-bychannel, thermal-hydraulic nodalization was developed and coupled, first with the RELAP5-3D internal neutronic routine NESTLE and then with the PHISICS code. Analysis of the AER-DYN-002 results shows that the steady-state solutions are in good agreement with the other participants’ average solution, while some differences are shown in the transient simulations. In the AER-DYN-003 benchmark, however, both steady-state and transient results are in good agreement with the average solution
Performing Probabilist Risk Assessment Through RAVEN
No full textRAVEN (Reactor Analysis and Virtual control
ENviroment) [1, 2] is a software framework that acts
as the control logic driver for the Thermo-Hydraylic code
RELAP-7, a newly developed software at Idaho National
Laboratory. The aim of this paper is to provide an overview
of the software structure and its utilization in conjunction
with RELAP-7/MOOSE [3, 4]. RAVEN is a multi-purpose
Probabilistic Risk Assement (PRA) code that allows
dispatching different functionalities. It is designed to derive
and actuate the control logic required to simulate the plant
control system and operator actions (guided procedures) and
to performboth Monte-Carlo sampling ofrandom distributed
events and dynamic event tree based analysis [5]. In order to
assist the user in the input/output handling, a Graphical User
Interface (GUI) and a post-processing data mining module,
based on dimensionality and cardinality reduction [6], are
available. This paper wants to point up the link between the
software layout and the mathematical framework from which
its structure is derived. In order to show some capabilities, a
demo of a Station Black Out (SBO) analysis of a simplified
Pressurized Water Reactor (PWR) model is reported.RAVEN (Reactor Analysis and Virtual control
ENviroment) [1, 2] is a software framework that acts
as the control logic driver for the Thermo-Hydraylic code
RELAP-7, a newly developed software at Idaho National
Laboratory. The aim of this paper is to provide an overview
of the software structure and its utilization in conjunction
with RELAP-7/MOOSE [3, 4]. RAVEN is a multi-purpose
Probabilistic Risk Assement (PRA) code that allows
dispatching different functionalities. It is designed to derive
and actuate the control logic required to simulate the plant
control system and operator actions (guided procedures) and
to performboth Monte-Carlo sampling ofrandom distributed
events and dynamic event tree based analysis [5]. In order to
assist the user in the input/output handling, a Graphical User
Interface (GUI) and a post-processing data mining module,
based on dimensionality and cardinality reduction [6], are
available. This paper wants to point up the link between the
software layout and th
Simulation tools and approaches for the compliance with performance-based ECCS cladding acceptance criteria (10 CFR50.46c)
No full textThe Nuclear Regulatory Commission (NRC) is currently considering a revision of the requirements in 10 CFR 50.46C, rules, focused on the ECCS rule in LOCA scenarios. The new approach modifies the analysis strategy in order to take into account also the effects of the burn-up rate. The maximum temperature and the oxidation of the cladding must be casted as function of the fuel exposure in order to find the limiting conditions in the history of the reactor, with its different design and different reloading patterns. This new analysis requires new tools and capabilities in order to have reasonable computational times and good accuracy, taking in account the dynamic phenomena of multi-physics systems. In order to perform such analysis, a rigorous Probabilistic Risk Assessment (PRA) strategy needs to be employed. This work is a proof of concept for illustrating a new proposed approach that will be required in the next years, in order to face the challenges posed by the new rule
RAVEN: a GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework
No full textIncreases in computational power and pressure for
more accurate simulations and estimations of accident scenario consequences are driving the need for Dynamic
Probabilistic Risk Assessment (PRA) [1] of very complex models. While more sophisticated algorithms and
computational power address the back end of this challenge, the front end is still handled by engineers that
need to extract meaningful information from the large amount of data and build these complex models.
Compounding this problem is the difficulty in knowledge transfer and retention, and the increasing speed of
software development. The above-described issues would have negatively
impacted deployment of the new high fidelity plant simulator RELAP-7 (Reactor Excursion and Leak
Analysis Program) at Idaho National Laboratory. Therefore, RAVEN that was initially focused to be the
plant controller for RELAP-7 will help mitigate future
RELAP-7 software engineering risks. In order to accomplish such a task Reactor Analysis
and V
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RAVEN As a tool for Dynamic Probabilistic Risk Assessment: Software Overview
No full textRAVEN 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 RELAP7.
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 maincapabilities such as on-line controlling/monitoringand Monte-Carlo sampling. A demo of
a Station Black Out PRA analysis of a simplified Pressurized Water Reactor (PWR) model is shown in
order to demonstrate the Monte-Carlo and clustering capabilities
PolyPole-1: An accurate numerical algorithm for intra-granular fission gas release
No full textThe transport of fission gas from within the fuel grains to the grain boundaries (intra-granular fission gas release) is a fundamental controlling mechanism of fission gas release and gaseous swelling in nuclear fuel. Hence, accurate numerical solution of the corresponding mathematical problem needs to be included in fission gas behaviour models used in fuel performance codes. Under the assumption of equilibrium between trapping and resolution, the process can be described mathematically by a single diffusion equation for the gas atom concentration in a grain. In this paper, we propose a new numerical algorithm (PolyPole-1) to efficiently solve the fission gas diffusion equation in time-varying conditions. The PolyPole-1 algorithm is based on the analytic modal solution of the diffusion equation for constant conditions, combined with polynomial corrective terms that embody the information on the deviation from constant conditions. The new algorithm is verified by comparing the results to a finite difference solution over a large number of randomly generated operation histories. Furthermore, comparison to state-of-the-art algorithms used in fuel performance codes demonstrates that the accuracy of PolyPole-1 is superior to other algorithms, with similar computational effort. Finally, the concept of PolyPole-1 may be extended to the solution of the general problem of intra-granular fission gas diffusion during non-equilibrium trapping and resolution, which will be the subject of future work
In vitro oral processing of raw tomato: Novel insights into the role of endogenous fruit enzymes
No full textDuring consumption of fruits, the breakdown of the fruit tissue due to oral processing (chewing, mixing with saliva) may activate or increase the rate of endogenous enzyme activities via the disruption of the cell wall, cellular de‐compartmentalization and particle size reduction allowing the enzymes to reach their substrates. The aim of this study was to investigate the activity of one such endogenous fruit enzyme (pectin methylesterase (E.C. 3.1.1.11) during in vitro oral processing of raw tomatoes and associated changes in viscosity and microstructure. Oral processing of tomatoes purees was examined in the presence of artificial saliva at 37 ○C. In vitro oral processing was followed using immunofluorescence microscopy, apparent viscosity measurements, spectrophotometric and titrimetric techniques. Results demonstrated that pectin methylesterase had slight but significant activity in the tomato fruit during in vitro oral processing generating methanol as a function of oral processing time, which was further evidenced using immunolabelling techniques to detect methylated pectin epitopes. A significant shear‐thinning behaviour of the tomato puree was observed due to dilution and/or endogenous fruit enzyme activity. These results suggest that activity of other fruit enzymes, such as polygalacturonase, which catalysed the depolymerisation of unmethylated pectin chains might have resulted in a decrease in viscosity, which compensated for the increased potential for gel formation (if any) caused by PME. These interesting insights on role of endogenous fruit enzymes might pave the way to the understanding of fruit viscosity modification occurring in the mouth and help in rational design of new fruit based products
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Dynamic Event Tree Analysis Through RAVEN
No full textConventional 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 is 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 in a high modular and pluggable way in order to enable easy integration of different
programminglanguages(i.e.,C++,Python)andcouplingwithotherapplicationincludingtheonesbased
on the MOOSE framew
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