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DOE OSTI2018

RELAP-7 User's Guide

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s capability and extends the analysis capability for all reactor system simulation scenarios.This document is a user's guide on how to use the RELAP-7 code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

RELAP-7 User's Guide

The document contains a user's guide on how to run the RELAP-7 code. The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory. RELAP-7 will become the main reactor systems simulation toolkit for the LWRS (Light Water Reactor Sustainability) program’s RISMC (Risk Informed Safety Margin Characterization) effort and the next generation tool in the RELAP reactor safety/systems analysis application series. RELAP-7 is written with object oriented programming language C++. A number of example problems and their associated input files are presented in this document to guide users to run the RELAP-7 code starting with simple pipe problems to problems with increasing complexity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

An Update on Improvements to NiCE Support for RELAP-7

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is a framework that facilitates the development of applications that rely on finite-element analysis to solve a coupled, nonlinear system of partial differential equations. RELAP-7 represents an update to the venerable RELAP-5 simulator that is built upon this framework and attempts to model the balance-of-plant concerns in a full nuclear plant. This report details the continued support and integration of RELAP-7 and the NEAMS Integrated Computational Environment (NiCE). RELAP-7 is fully supported by the NiCE due to on-going work to tightly integrate NiCE with the MOOSE framework, and subsequently the applications built upon it. NiCE development throughout the first quarter of FY15 has focused on improvements, bug fixes, and feature additions to existing MOOSE-based application support. Specifically, this report will focus on improvements to the NiCE MOOSE Model Builder, the MOOSE application job launcher, and the 3D Nuclear Plant Viewer. This report also includes a comprehensive tutorial that guides RELAP-7 users through the basic NiCE workflow: from input generation and 3D Plant modeling, to massively parallel job launch and post-simulation data visualization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Analysis of the Space Propulsion System Problem Using RAVEN

This paper presents the solution of the space propulsion problem using a PRA code currently under development at Idaho National Laboratory (INL). RAVEN (Reactor Analysis and Virtual control ENviroment) is a multi-purpose Probabilistic Risk Assessment (PRA) software framework 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 perform both Monte- Carlo sampling of random distributed events and Event Tree based analysis. In order to facilitate the input/output handling, a Graphical User Interface (GUI) and a post-processing data-mining module are available. RAVEN allows also to interface with several numerical codes such as RELAP5 and RELAP-7 and ad-hoc system simulators. For the space propulsion system problem, an ad-hoc simulator has been developed and written in python language and then interfaced to RAVEN. Such simulator fully models both deterministic (e.g., system dynamics and interactions between system components) and stochastic behaviors (i.e., failures of components/systems such as distribution lines and thrusters). Stochastic analysis is performed using random sampling based methodologies (i.e., Monte-Carlo). Such analysis is accomplished to determine both the reliability of the space propulsion system and to propagate the uncertainties associated to a specific set of parameters. As also indicated in the scope of the benchmark problem, the results generated by the stochastic analysis are used to generate risk-informed insights such as conditions under witch different strategy can be followed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Performing Probabilistic Risk Assessment Through RAVEN

The Reactor Analysis and Virtual control ENviroment (RAVEN) code is a software tool that acts as the control logic driver and post-processing engine for the newly developed Thermal-Hydraulic code RELAP-7. RAVEN is now a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities: Derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures), allowing on-line monitoring/controlling in the Phase Space Perform both Monte-Carlo sampling of random distributed events and Dynamic Event Tree based analysis Facilitate the input/output handling through a Graphical User Interface (GUI) and a post-processing data mining module

99 GENERAL AND MISCELLANEOUS↗