Reconstructed Discontinuous Galerkin System Requirements Specification

This template follows INL template TEM-135, "IT System Requirements Specification".

note

This document serves as an addendum to Framework System Requirements Specification and captures information for Software Requirement Specification (SRS) specific to the Reconstructed Discontinuous Galerkin module.

Framework System Requirements Specification

Introduction

System Purpose

The MOOSE rDG module is a library for the implementation of simulation tools that solve convection-dominated problems using the class of so-called reconstructed discontinuous Galerkin (rDG) methods. The specific rDG method implemented in this module is rDG(P0P1), which is equivalent to the second-order cell-centered finite volume method (FVM). Cell-centered FVMs are regarded as a subset of rDG methods in the case when the baseline polynomial solution in each element is a constant monomial. The FVMs are the most widely used numerical methods in areas such as computational fluid dynamics (CFD) and heat transfer, computational acoustics, and magnetohydrodynamics (MHD).

System Scope

The purpose of this software is to provide capability to MOOSE-based applications to use a second-order, cell-centered finite volume method (FVM). This module provides a systematic solution for implementing all required components in a second-order FVM such as slope reconstruction, slope limiting, numerical flux, and proper boundary conditions. Additionally, this module provides an implementation of these components for the scalar advection equation.

System Overview

System Context

The Reconstructed Discontinuous Galerkin module is command-line driven. Like MOOSE, this is typical for a high-performance software that is designed to run across several nodes of a cluster system. As such, all usage of the software is through any standard terminal program generally available on all supported operating systems. Similarly, for the purpose of interacting through the software, there is only a single user, "the user", which interacts with the software through the command-line. The Reconstructed Discontinuous Galerkin module does not maintain any back-end database or interact with any system daemons. It is an executable, which may be launched from the command line and writes out various result files as it runs.

Figure 1: Usage of the Reconstructed Discontinuous Galerkin module and other MOOSE-based applications.

System Functions

Since the Reconstructed Discontinuous Galerkin module is a command-line driven application, all functionality provided in the software is operated through the use of standard UNIX command line flags and the extendable MOOSE input file. The Reconstructed Discontinuous Galerkin module is completely extendable so individual design pages should be consulted for specific behaviors of each user-defined object.

User Characteristics

Like MOOSE, there are three kinds of users working on the Reconstructed Discontinuous Galerkin module:

Reconstructed Discontinuous Galerkin module Developers: These are the core developers of the Reconstructed Discontinuous Galerkin module. They are responsible for following and enforcing the software development standards of the module, as well as designing, implementing, and maintaining the software.
Developers: A scientist or engineer that uses the Reconstructed Discontinuous Galerkin module alongside MOOSE to build their own application. This user will typically have a background in modeling or simulation techniques (and perhaps numerical analysis) but may only have a limited skillset when it comes to code development using the C++ language. This is the primary focus group of the module. In many cases, these developers will be encouraged to contribute module-appropriate code back to the Reconstructed Discontinuous Galerkin module, or to MOOSE itself.
Analysts: These are users that will run the code and perform analysis on the simulations they perform. These users may interact with developers of the system requesting new features and reporting bugs found and will typically make heavy use of the input file format.

Assumptions and Dependencies

The Reconstructed Discontinuous Galerkin module is developed using MOOSE and can itself be based on various MOOSE modules, as such the SRS for the Reconstructed Discontinuous Galerkin module is dependent upon the files listed at the beginning of this document. Any further assumptions or dependencies are outlined in the remainder of this section.

The Reconstructed Discontinuous Galerkin module is designed with the fewest possible constraints on hardware and software. For more context on this point, the Reconstructed Discontinuous Galerkin module SRS defers to the framework Assumptions and Dependencies. Any physics-based or mathematics-based assumptions in code simulations and code objects are highlighted in their respective documentation pages.

References

ISO/IEC/IEEE 24765:2010(E). Systems and software engineering—Vocabulary. first edition, December 15 2010.

@manual{ISO-systems-software,
    author = "24765:2010(E), ISO/IEC/IEEE",
    title = "Systems and software engineering---Vocabulary",
    edition = "First",
    year = "2010",
    month = "December 15"
}

ASME NQA-1. ASME NQA-1-2008 with the NQA-1a-2009 addenda: Quality Assurance Requirements for Nuclear Facility Applications. first edition, August 31 2009.

@manual{ASME-NQA-1-2008,
    author = "NQA-1, ASME",
    title = "ASME NQA-1-2008 with the NQA-1a-2009 addenda: Quality Assurance Requirements for Nuclear Facility Applications",
    orginization = "American Socieity of Mechanical Engineers",
    year = "2009",
    month = "August 31",
    edition = "First"
}

Definitions and Acronyms

This section defines, or provides the definition of, all terms and acronyms required to properly understand this specification.

Definitions

Verification: (1) The process of: evaluating a system or component to determine whether the products of a given development phase satisfy the conditions imposed at the start of that phase. (2) Formal proof of program correctness (e.g., requirements, design, implementation reviews, system tests) (24765:2010(E), 2010).

Acronyms

Acronym	Description
INL	Idaho National Laboratory
LGPL	GNU Lesser General Public License
MOOSE	Multiphysics Object Oriented Simulation Environment
NQA-1	Nuclear Quality Assurance Level 1
POSIX	Portable Operating System Interface
SRS	Software Requirement Specification

System Requirements

In general, the following is required for MOOSE-based development:

A POSIX compliant Unix-like operating system. This includes any modern Linux-based operating system (e.g., Ubuntu, Fedora, Rocky, etc.), or a Macintosh machine running either of the last two MacOS releases.

Hardware	Information
CPU Architecture	x86_64, ARM (Apple Silicon)
Memory	8 GB (16 GBs for debug compilation)
Disk Space	30GB

Libraries	Version / Information
GCC	9.0.0 - 12.2.1
LLVM/Clang	10.0.1 - 19
Intel (ICC/ICX)	Not supported at this time
Python	3.10 - 3.13
Python Packages	packaging pyaml jinja2

Functional Requirements

rdg: Bcs
8.1.1The system shall compute the equilibrium flux condition between an enclosure and a structure when a field variable is used for the enclosure variable.

rdg: Divertor Monoblock
8.2.1The system shall maintain a working input file to model heat and tritium transport in a divertor monoblock during pulsed operation.
8.2.2The system shall model heat and tritium transport in a divertor monoblock during pulsed operation.

rdg: Fuel Cycle Abdou
8.3.1The system shall reproduce a consistent solution to an ODE system of equations modeling the tritium fuel cycle.
8.3.2The system shall be able to generate comparison plots between the simulated solution from TMAP8 and Abdou et al. (2020), modeling tritium fuel cycle.
8.3.3The system shall be able to open a graphical interface for the tritium fuel cycle example for user training.

rdg: Fuel Cycle Meschini
8.4.1The system shall be able to model the tritium fuel cycle from Meschini et al. (2023).
8.4.2The system shall be able to the model tritium fuel cycle from Meschini et al. (2023) with fine time step.
8.4.3The system shall be able to generate comparison plots between the simulated solution from TMAP8 and Meschini et al. (2023), modeling tritium fuel cycle.

rdg: Interfacekernels
8.5.1The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions.
8.5.2The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using a penalty-enforced flux balance.
8.5.3The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using automatic differentiation.
8.5.4The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using automatic differentiation and a penalty-enforced flux balance.
8.5.5The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions.
8.5.6The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using a penalty-enforced flux balance.
8.5.7The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using automatic differentiation.
8.5.8The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using automatic differentiation and a penalty-enforced flux balance.
8.5.9The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions during transient simulations.
8.5.10The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using automatic differentiation during transient simulations.
8.5.11The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions during transient simulations with unit scaling on both variables.
8.5.12The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using automatic differentiation during transient simulations with unit scaling on both variables.
8.5.13The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using a penalty-enforced flux balance during transient simulations with unit scaling on both variables.
8.5.14The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using a penalty-enforced flux balance during transient simulations with unit scaling on both variables and provide similar results to the approach without the penalty-enforced flux balance.
8.5.15The system shall have the capability to enforce interfacial conditions based on the Sievert law in isothermal conditions using automatic differentiation and a penalty-enforced flux balance during transient simulations with unit scaling on both variables.
8.5.16The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions during transient simulations.
8.5.17The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using automatic differentiation during transient simulations.
8.5.18The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions during transient simulations with unit scaling on both variables.
8.5.19The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using automatic differentiation during transient simulation with unit scaling on both variables.
8.5.20The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using a penalty-enforced flux balance during transient simulations with unit scaling on both variables.
8.5.21The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using a penalty-enforced flux balance during transient simulations with unit scaling on both variables and provide similar results to the approach without the penalty-enforced flux balance.
8.5.22The system shall have the capability to enforce interfacial conditions based on the Henry law in isothermal conditions using automatic differentiation and a penalty-enforced flux balance during transient simulations with unit scaling on both variables.

rdg: Kernels
8.6.1The system shall compute the annihilation of a concentration variable towards its equilibrium in the material.
8.6.2The system shall compute the reaction contribution in the material.

rdg: Pore Scale Transport
8.7.1The system shall be able to read a microstructure image and import it to perform a simulation to smoothen the interfaces.
8.7.2The system shall be able to import an existing microstructure and perform a simulation of tritium transport during absorption at the pore scale.

rdg: Val-2A
8.8.1The system shall be able to model deuterium ion implantation in a steel alloy for comparison with experimental results, particularly focusing on the permeation flux.
8.8.2The system shall be able to model deuterium ion implantation in a steel alloy for comparison with experimental results, focused on the full set of simulation output including deuterium concentration, recombination coefficient, and dissociation coefficient.
8.8.3The system shall be able to generate comparison plots between the analytical solution and simulated solution of validation case 2a, modeling deuterium ion implantation in a steel alloy.

rdg: Val-2B
8.9.1The system shall be able to model diffusion of deuterium in a beryllium sample and generate CSV data output for comparison to experimental results.
8.9.2The system shall be able to model diffusion of deuterium in a beryllium sample and generate field and material property data output in the Exodus format for comparison to experimental results.
8.9.3The system shall be able to model diffusion of deuterium in beryllium sample with a short runtime suitable for regular regression testing.
8.9.4The system shall be able to generate comparison plots between simulated solutions and experimental data of validation case val-2b, modeling diffusion and release of deuterium in a beryllium sample.

rdg: Val-2C
8.10.1The system shall be able to model the Test Cell Release Experiment (val-2c) with immediate T2 injection.
8.10.2The system shall be able to model the Test Cell Release Experiment (val-2c) with immediate T2 injection and properly compute the exodus file.
8.10.3The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection.
8.10.4The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection and properly compute the exodus file.
8.10.5The system shall be able to generate comparison plots between simulated solutions and experimental data of validation cases val-2c, modeling a Test Cell Release Experiment.

rdg: Val-2D
8.11.1The system shall be able to model thermal desorption spectroscopy on Tungsten.
8.11.2The system shall be able to model thermal desorption spectroscopy on Tungsten to include full set of simulation outputs, including tritium concentration, diffusion flux, and trapping properties.
8.11.3The system shall be able to model thermal desorption spectroscopy on Tungsten with fine mesh and time step to compare with the desorption flux from experiment results.
8.11.4The system shall be able to model thermal desorption spectroscopy on Tungsten with fine mesh and time step to include full set of simulation outputs, including tritium concentration, diffusion flux, and trapping properties.
8.11.5The system shall be able to generate comparison plots between the analytical solution and simulated solution of validation case 2d, modeling thermal desorption spectroscopy on Tungsten.

rdg: Val-2E
8.12.1The system shall be able to model permeation of Deuterium from a 0.05 mm thick membrane at 825 K to generate CSV data for use in comparisons with the experimental data.
8.12.2The system shall be able to model permeation of Deuterium from a 0.05 mm thick membrane at 825 K.
8.12.3The system shall be able to model permeation of Deuterium from a 0.025 mm thin membrane at 825 K to generate CSV data for use in comparisons with the experimental data.
8.12.4The system shall be able to model permeation of Deuterium from a 0.025 mm thin membrane at 825 K.
8.12.5The system shall be able to model permeation of Deuterium from a 0.025 mm thin membrane at 865 K to generate CSV data for use in comparisons with the experimental data.
8.12.6The system shall be able to model permeation of Deuterium from a 0.025 mm thin membrane at 865 K and generate an exodus file.
8.12.7The system shall be able to model permeation of mixture gas from a 0.025 mm thin membrane at 870 K using lawdep boundary conditions to generate CSV data for use in comparisons with the experimental data.
8.12.8The system shall be able to model permeation of mixture gas with chemical reaction from a 0.025 mm thin membrane at 870 K using lawdep boundary conditions and generate an exodus file.
8.12.9The system shall be able to model permeation of mixture gas from a 0.025 mm thin membrane at 870 K using ratedep boundary conditions to generate CSV data for use in comparisons with the experimental data.
8.12.10The system shall be able to model permeation of mixture gas with chemical reaction from a 0.025 mm thin membrane at 870 K using ratedep boundary conditions and generate an exodus file.
8.12.11The system shall be able to generate comparison plots between the analytical solution and experimental data of validation case 2e, modeling the permeation of Deuterium from a membrane.

rdg: Val-2F
8.13.1The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output with a short runtime and coarse mesh testing.
8.13.2The system shall be able to model self-damaged tungsten effects on deuterium transport with a short runtime and coarse mesh testing.
8.13.3The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output.
8.13.4The system shall be able to model self-damaged tungsten effects on deuterium transport.
8.13.5The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output, for the infinite recombination case.
8.13.6The system shall be able to generate comparison plots between simulated solutions and experimental data of validation case val-2f, modeling self-damaged tungsten effects on deuterium transport.

rdg: Ver-1A
8.14.1The system shall be able to model species diffusion through a structure, originating from a depleting source enclosure.
8.14.2The system shall be able to model species diffusion through a structure, originating from a depleting source enclosure, with the fine mesh and timestep required to match the analytical solution.
8.14.3The system shall be able to model species diffusion through a structure, originating from a depleting source enclosure, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution.
8.14.4The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1a, modeling species diffusion through a structure, originating from a depleting source enclosure.

rdg: Ver-1B
8.15.1The system shall be able to model transient diffusion through a slab with a constant concentration boundary condition as the species source.
8.15.2The system shall be able to model transient diffusion through a slab with a constant concentration boundary condition as the species source with the fine mesh and time step required to match the analytical solution.
8.15.3The system shall be able to model transient diffusion through a slab with a constant concentration boundary condition as the species source, with the fine mesh and time step required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution over time.
8.15.4The system shall be able to model transient diffusion through a slab with a constant concentration boundary condition as the species source, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution for the profile concentration.
8.15.5The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1b, modeling transient diffusion through a slab with a constant concentration boundary condition as the species source.

rdg: Ver-1C
8.16.1The system shall be able to model species permeation into an unloaded portion of a slab from a pre-loaded portion with boundary conditions consistent with TMAP4.
8.16.2The system shall be able to model species permeation into an unloaded portion of a slab from a pre-loaded portion with boundary conditions consistent with TMAP7
8.16.3The system shall be able to model species permeation into an unloaded portion of a slab from a pre-loaded portion to generate CSV data for use in comparisons with the analytic solution over time for the TMAP4 verification case.
8.16.4The system shall be able to model species permeation into an unloaded portion of a slab from a pre-loaded portion to generate CSV data for use in comparisons with the analytic solution over time for the TMAP7 verification case.
8.16.5The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1c, modeling species permeation into an unloaded portion of a slab from a pre-loaded portion for both the TMAP4 and TMAP7 verification cases.

rdg: Ver-1D
8.17.1The system shall be able to model a breakthrough problem where diffusion is the rate limiting process.
8.17.2The system shall be able to model a breakthrough problem where diffusion is the rate limiting process, with the fine mesh and time step required to match the analytical solution for the verification case.
8.17.3The system shall be able to model a breakthrough problem where diffusion is the rate limiting process, with the fine mesh and time step required to match the analytical solution for the verification case and generate CSV data for use in comparisons with the analytic solution.
8.17.4The system shall be able to model a breakthrough problem where trapping is the rate limiting process.
8.17.5The system shall be able to model a breakthrough problem where trapping is the rate limiting process with the fine mesh and time step required to match the analytical solution for the verification case.
8.17.6The system shall be able to model a breakthrough problem where trapping is the rate limiting process with the fine mesh and time step required to match the analytical solution for the verification case and generate CSV data for use in comparisons with the analytic solution.
8.17.7The system shall be able to generate comparison plots between the analytical solution and simulated solutions of verification cases 1d, modeling a breakthrough problem where diffusion and trapping are the rate limiting processes.

rdg: Ver-1Dc
8.18.1The system shall be able to model a breakthrough problem of multiple traps.
8.18.2The system shall be able to model a breakthrough problem of multiple traps, with the fine mesh and time step required to match the analytical solution for the verification case.
8.18.3The system shall be able to model a breakthrough problem of multiple traps, with the fine mesh and time step required to match the analytical solution for the verification case and generate CSV data for use in comparisons with the analytic solution.
8.18.4The system shall be able to generate comparison plots between the analytical solution and simulated solutions of verification cases 1dc, modeling a breakthrough problem of multiple traps.
8.18.5The system shall show second order spatial convergence for a diffusion-trapping-release test case.

rdg: Ver-1Dd
8.19.1The system shall be able to model a breakthrough problem without traps.
8.19.2The system shall be able to model a breakthrough problem without traps, and generate CSV data for use in comparisons with the analytic solution.
8.19.3The system shall be able to generate comparison plots between the analytical solution and simulated solutions of verification cases 1dd, modeling a breakthrough problem without traps.

rdg: Ver-1E
8.20.1The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source.
8.20.2The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and time step required to match the analytical solution for the TMAP4 verification case.
8.20.3The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and time step required to match the analytical solution for the TMAP7 verification case.
8.20.4The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and time step required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution over time for the TMAP4 verification case.
8.20.5The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and time step required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution over time for the TMAP7 verification case.
8.20.6The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution for the profile concentration for the TMAP4 verification case.
8.20.7The system shall be able to model transient diffusion through a composite slab with a constant concentration boundary condition as the species source, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution for the profile concentration for the TMAP7 verification case.
8.20.8The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1e, modeling transient diffusion through a composite slab with a constant concentration boundary condition as the species source for both the TMAP4 and TMAP7 verification cases.

rdg: Ver-1Fa
8.21.1The system shall be able to model heat conduction in a slab that has heat generation
8.21.2The system shall be able to model heat conduction in a slab that has heat generation to generate CSV data for use in comparisons with the analytic solution for the profile concentration.
8.21.3The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1fa, to model heat conduction in a slab that has heat generation.

rdg: Ver-1Fb
8.22.1The system shall be able to model thermal transient in a slab that has temperatures fixed at both the ends
8.22.2The system shall be able to model thermal transient in a slab that has temperatures fixed at both the ends to generate CSV data at time of 0.1 s for use in comparison with analytical solution.
8.22.3The system shall be able to model thermal transient in a slab that has temperatures fixed at both the ends to generate CSV data at time of 0.5 s for use in comparison with analytical solution.
8.22.4The system shall be able to model thermal transient in a slab that has temperatures fixed at both the ends to generate CSV data at time of 1.0 s for use in comparison with analytical solution.
8.22.5The system shall be able to model thermal transient in a slab that has temperatures fixed at both the ends to generate CSV data at time of 5.0 s for use in comparison with analytical solution.
8.22.6The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1fb, modeling thermal transient in a slab with fixed temperatures at both the ends.

rdg: Ver-1Fc
8.23.1The system shall be able to model conduction in a composite structure with constant surface temperatures.
8.23.2The system shall be able to model conduction in a composite structure with constant surface temperatures to generate CSV data for use in comparisons with ABAQUS during transient at x=0.09 m.
8.23.3The system shall be able to model conduction in a composite structure with constant surface temperatures to generate CSV data for use in comparisons with ABAQUS during transient at t=150 s.
8.23.4The system shall be able to model conduction in a composite structure with constant surface temperatures to generate CSV data for use in comparisons with ABAQUS and an analytical solution at steady state (t=10000 s).
8.23.5The system shall be able to generate comparison plots between the analytical solution, ABAQUS data, and simulated solution of verification case 1fc, modeling conduction in a composite structure with constant surface temperatures.

rdg: Ver-1Fd
8.24.1The system shall be able to model convective heating.
8.24.2The system shall be able to model convective heating to generate CSV data for use in comparisons with the analytic solution.
8.24.3The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1fd, modeling convective heating.

rdg: Ver-1G
8.25.1The system shall be able to model a chemical reaction between two species with the same concentrations and calculate the concentrations of reactants and product as a function of time
8.25.2The system shall be able to model a chemical reaction between two species with different concentrations and calculate the concentrations of reactants and product as a function of time using the initial conditions from the TMAP4 case
8.25.3The system shall be able to model a chemical reaction between two species with different concentrations and calculate the concentrations of reactants and product as a function of time using the initial conditions from the TMAP7 case
8.25.4The system shall be able to model a chemical reaction between two species with the same concentrations and calculate the concentrations of reactants and product as a function of time, to match the analytical solution to generate CSV data for use in comparisons with the analytic solution over time.
8.25.5The system shall be able to model a chemical reaction between two species with different concentrations using the initial conditions from the TMAP4 case and calculate the concentrations of reactants and product as a function of time to generate CSV data for use in comparisons with the analytic solution over time.
8.25.6The system shall be able to model a chemical reaction between two species with different concentrations using the initial conditions from the TMAP7 case and calculate the concentrations of reactants and product as a function of time to generate CSV data for use in comparisons with the analytic solution over time.
8.25.7The system shall be able to generate comparison plots between the analytical solution and simulated solution of a chemical reaction between two species with same or different concentrations, using the initial conditions from both TMAP4 and TMAP7 cases.

rdg: Ver-1Gc
8.26.1The system shall be able to model a series of chemical reactions involving three species and calculate the concentrations of each species as a function of time.
8.26.2The system shall be able to model a series of chemical reactions involving three species and calculate the concentrations of each species as a function of time and to generate CSV data for use in comparisons with the analytic solution over time.
8.26.3The system shall be able to generate comparison plots between the analytical solution and simulated solution of a series of chemical reactions involving three species and calculate the concentrations of each species as a function of time and to generate CSV data for use in comparisons with the analytic solution over time.

rdg: Ver-1Ha
8.27.1The system shall be able to model a convective outflow problem and calculate the pressure and concentration of the gas in the second and third enclosure and to generate CSV data for use in comparisons with the analytic solution over time.
8.27.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a convective outflow problem involving three enclosures and calculate the pressure and concentration of the gas in the second and third enclosure.

rdg: Ver-1Hb
8.28.1The system shall be able to model a convective outflow problem and calculate the pressure and concentration of tritium and deuterium gas in the first and second enclosure and to generate CSV data for use in comparisons with the analytic solution over time.
8.28.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a convective outflow problem involving two enclosures and two different gases and calculate the pressure and concentration of the gases in the enclosures.

rdg: Ver-1Ia
8.29.1The system shall be able to model a equilibration problem on a reactive surface with equal starting pressures in ratedep condition and to generate CSV data for use in comparisons with the analytic solution over time.
8.29.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface with equal starting pressures in ratedep condition

rdg: Ver-1Ib
8.30.1The system shall be able to model a equilibration problem on a reactive surface with unequal starting pressures in ratedep condition and to generate CSV data for use in comparisons with the analytic solution over time.
8.30.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface in ratedep condition with unequal starting pressures.

rdg: Ver-1Ic
8.31.1The system shall be able to model a equilibration problem on a reactive surface in surfdep conditions with low barrier energy and to generate CSV data for use in comparisons with the analytic solution over time.
8.31.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface in surfdep condition with low barrier energy.

rdg: Ver-1Id
8.32.1The system shall be able to model a equilibration problem on a reactive surface in surfdep conditions with high barrier energy and to generate CSV data for use in comparisons with the analytic solution over time.
8.32.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface in surfdep condition with high barrier energy.

rdg: Ver-1Ie
8.33.1The system shall be able to model a equilibration problem on a reactive surface in lawdep condition with equal starting pressures and to generate CSV data for use in comparisons with the analytic solution over time.
8.33.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface in lawdep condition with equal starting pressures.

rdg: Ver-1If
8.34.1The system shall be able to model a equilibration problem on a reactive surface in lawdep condition with unequal starting pressures and to generate CSV data for use in comparisons with the analytic solution over time.
8.34.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of a equilibration on a reactive surface in lawdep condition with unequal starting pressures.

rdg: Ver-1Ja
8.35.1The system shall be able to model decay of tritium and associated growth of helium in a diffusion segment and generate CSV data for use in comparisons with the analytic solution.
8.35.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1ja, which models decay of tritium and associated growth of helium in a diffusion segment.

rdg: Ver-1Jb
8.36.1The system shall be able to model decay of tritium and associated growth of He in a diffusion segment with distributed traps, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution.
8.36.2The system shall be able to model decay of tritium and associated growth of He in a diffusion segment with distributed traps and output the profiles of concentrations.
8.36.3The system shall be able to model decay of tritium and associated growth of He in a diffusion segment with distributed traps with equivalent initial mobile and trapped tritium concentration, with the fine mesh and timestep required to match the analytical solution to generate CSV data for use in comparisons with the analytic solution.
8.36.4The system shall be able to model decay of tritium and associated growth of He in a diffusion segment with distributed traps with equivalent initial mobile and trapped tritium concentration and output the profiles of concentrations.
8.36.5The system shall be able to generate comparison plots between the analytical solution and simulated solution when modeling decay of tritium and associated growth of He in a diffusion segment with distributed traps.

rdg: Ver-1Ka
8.37.1The system shall be able to model a tritium volumetric source in one enclosure
8.37.2The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1ka, modeling a tritium volumetric source in one enclosure.

rdg: Ver-1Kb
8.38.1The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Henry’s law without any concentration jump at the interface.
8.38.2The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Henry’s law with a concentration jump at the interface.
8.38.3The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Henry’s law with a concentration jump at the interface
8.38.4The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1kb, modeling a diffusion across a membrane separating two enclosures in accordance with Henry’s law.

rdg: Ver-1Kc-1
8.39.1The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface.
8.39.2The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface with a fine mesh and tight tolerances for higher accuracy.
8.39.3The system shall be able to model the diffusion of T2 across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface with a fine mesh and tight tolerances for higher accuracy and generate an exodus file.
8.39.4The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1kc-1, modeling a diffusion across a membrane separating two enclosures in accordance with Sieverts’ law.

rdg: Ver-1Kc-2
8.40.1The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface.
8.40.2The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface with tight tolerances for higher accuracy.
8.40.3The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface and generate an exodus file with tight tolerances for higher accuracy.
8.40.4The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1kc-2, modeling a diffusion across a membrane separating two enclosures in accordance with Sieverts’ law.

rdg: Ver-1Kd
8.41.1The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface and a T2 volumetric source term.
8.41.2The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface and a T2 volumetric source term with tight tolerances for higher accuracy.
8.41.3The system shall be able to model the diffusion of T2, H2 and HT across a membrane separating two enclosures in accordance with Sieverts’ law with a concentration jump at the interface and a T2 volumetric source term and generate an exodus file with tight tolerances for higher accuracy.
8.41.4The system shall be able to generate comparison plots between the analytical solution and simulated solution of verification case 1kd, modeling a diffusion across a membrane separating two enclosures in accordance with Sieverts’ law and a T2 volumetric source term.

rdg: Yttrium Hydrogen System
8.42.1The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature.
8.42.2The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature and generate an exodus file.
8.42.3The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=1e3 Pa and T=1173.15 K.
8.42.4The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=1e4 Pa and T=1173.15 K.
8.42.5The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=5e4 Pa and T=1173.15 K.
8.42.6The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=3e3 Pa and T=1273.15 K.
8.42.7The system shall be able to generate comparison plots between experimental PCT curves, the model used in TMAP8, and TMAP8 predictions.
8.42.8The system shall be able to return a warning when the pressure and temperature are outside the range of validity of the YHxPCT model (pressure too low).
8.42.9The system shall be able to return a warning when the pressure and temperature are outside the range of validity of the YHxPCT model (pressure too high).

Usability Requirements

No requirements of this type exist for this application, beyond those of its dependencies.

Performance Requirements

No requirements of this type exist for this application, beyond those of its dependencies.

System Interfaces

No requirements of this type exist for this application, beyond those of its dependencies.

System Operations

Human System Integration Requirements

The Reconstructed Discontinuous Galerkin module is command line driven and conforms to all standard terminal behaviors. Specific human system interaction accommodations shall be a function of the end-user's terminal. MOOSE (and therefore the Reconstructed Discontinuous Galerkin module) does support optional coloring within the terminal's ability to display color, which may be disabled.

Maintainability

The latest working version (defined as the version that passes all tests in the current regression test suite) shall be publicly available at all times through the repository host provider.
Flaws identified in the system shall be reported and tracked in a ticket or issue based system. The technical lead will determine the severity and priority of all reported issues and assign resources at their discretion to resolve identified issues.
The software maintainers will entertain all proposed changes to the system in a timely manner (within two business days).
The core software in its entirety will be made available under the terms of a designated software license. These license terms are outlined in the LICENSE file alongside the Reconstructed Discontinuous Galerkin module source code. As a MOOSE physics module, the license for the Reconstructed Discontinuous Galerkin module is identical to that of the framework - that is, the LGPL version 2.1 license.

Reliability

The regression test suite will cover at least 65% of all lines of code within the Reconstructed Discontinuous Galerkin module at all times. Known regressions will be recorded and tracked (see Maintainability) to an independent and satisfactory resolution.

System Modes and States

MOOSE applications normally run in normal execution mode when an input file is supplied. However, there are a few other modes that can be triggered with various command line flags as indicated here:

Command Line Flag	Description of mode
`-i <input_file>`	Normal execution mode
`--split-mesh <splits>`	Read the mesh block splitting the mesh into two or more pieces for use in a subsequent run
`--use-split`	(implies -i flag) Execute the simulation but use pre-split mesh files instead of the mesh from the input file
`--yaml`	Output all object descriptions and available parameters in YAML format
`--json`	Output all object descriptions and available parameters in JSON format
`--syntax`	Output all registered syntax
`--registry`	Output all known objects and actions
`--registry-hit`	Output all known objects and actions in HIT format
`--mesh-only` (implies -i flag)	Run only the mesh related tasks and output the final mesh that would be used for the simulation
`--start-in-debugger <debugger>`	Start the simulation attached to the supplied debugger

note

The list of system-modes may not be extensive as the system is designed to be extendable to end-user applications. The complete list of command line options for applications can be obtained by running the executable with zero arguments. See the command line usage.

Physical Characteristics

The Reconstructed Discontinuous Galerkin module is software only with no associated physical media. See System Requirements for a description of the minimum required hardware necessary for running the Reconstructed Discontinuous Galerkin module.

Environmental Conditions

Not Applicable

System Security

MOOSE-based applications such as the Reconstructed Discontinuous Galerkin module have no requirements or special needs related to system security. The software is designed to run completely in user-space with no elevated privileges required nor recommended.

Information Management

The core framework and all modules in their entirety will be made publicly available on an appropriate repository hosting site. Day-to-day backups and security services will be provided by the hosting service. More information about MOOSE backups of the public repository on INL-hosted services can be found on the following page: GitHub Backups

Polices and Regulations

MOOSE-based applications must comply with all export control restrictions.

System Life Cycle Sustainment

MOOSE-based development follows various agile methods. The system is continuously built and deployed in a piecemeal fashion since objects within the system are more or less independent. Every new object requires a test, which in turn requires an associated requirement and design description. The Reconstructed Discontinuous Galerkin module development team follows the NQA-1 standards.

Packaging, Handling, Shipping and Transportation

No special requirements are needed for packaging or shipping any media containing MOOSE and Reconstructed Discontinuous Galerkin module source code. However, some MOOSE-based applications that use the Reconstructed Discontinuous Galerkin module may be export-controlled, in which case all export control restrictions must be adhered to when packaging and shipping media.

Verification

The regression test suite will employ several verification tests using comparison against known analytical solutions, the method of manufactured solutions, and convergence rate analysis.

Introduction
System Overview
References
Definitions and Acronyms
System Requirements
Verification