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Reactor Requirements Traceability Matrix

This template follows INL template TEM-214, "IT System Requirements Traceability Matrix."

commentnote

This document serves as an addendum to Framework Requirements Traceability Matrix and captures information for RTM specific to the Reactor application.

Introduction

Minimum System Requirements

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

  • GCC/Clang C++17 compliant compiler (GCC @ 7.5.0, Clang @ 5.0.2 or greater)

    • Note: Intel compilers are not supported.

  • Memory: 16 GBs (debug builds)

  • Processor: 64-bit x86

  • Disk: 30GB

System Purpose

The MOOSE is a tool for solving complex coupled Multiphysics equations using the finite element method. MOOSE uses an object-oriented design to abstract data structure management, parallelism, threading and compiling while providing an easy to use interface targeted at engineers that may not have a lot of software development experience. MOOSE will require extreme scalability and flexibility when compared to other FEM frameworks. For instance, MOOSE needs the ability to run extremely complex material models, or even third-party applications within a parallel simulation without sacrificing parallelism. This capability is in contrast to what is often seen in commercial packages, where custom material models can limit the parallel scalability, forcing serial runs in the most severe cases. When comparing high-end capabilities, many MOOSE competitors target modest-sized clusters with just a few thousand processing cores. MOOSE, however, will be required to routinely executed on much larger clusters with scalability to clusters available in the top 500 systems (top500.org). MOOSE will also be targeted at smaller systems such as high-end laptop computers.

The design goal of MOOSE is to give developers ultimate control over their physical models and applications. Designing new models or solving completely new classes of problems will be accomplished by writing standard C++ source code within the framework's class hierarchy. Scientists and engineers will be free to implement completely new algorithms using pieces of the framework where possible, and extending the framework's capabilities where it makes sense to do so. Commercial applications do not have this capability, and instead opt for either a more rigid parameter system or a limited application-specific metalanguage.

System Scope

MOOSE's scope is to provide a set of interfaces for building FEM simulations. Abstractions to all underlying libraries are provided.

Solving coupled problems where competing physical phenomena impact one and other in a significant nonlinear fashion represents a serious challenge to several solution strategies. Small perturbations in strongly-coupled parameters often have very large adverse effects on convergence behavior. These adverse effects are compounded as additional physics are added to a model. To overcome these challenges, MOOSE employs three distinct yet compatible systems for solving these types of problems.

First, an advanced numerical technique called the JFNK method is employed to solve the most fully-coupled physics in an accurate, consistent way. An example of this would be the effect of temperature on the expansion or contraction of a material. While the JFNK numerical method is very effective at solving fully-coupled equations, it can also be computationally expensive. Plus, not all physical phenomena in a given model are truly coupled to one another. For instance, in a reactor, the speed of the coolant flow may not have any direct effect on the complex chemical reactions taking place inside the fuel rods. We call such models "loosely-coupled". A robust, scalable system must strike the proper balance between the various modeling strategies to avoid performing unnecessary computations or incorrectly predicting behavior in situations such as these.

MOOSE's Multiapp system will allow modelers to group physics into logical categories where MOOSE can solve some groups fully-coupled and others loosely-coupled. The Multiapp system goes even further by also supporting a "tightly-coupled" strategy, which falls somewhere between the "fully-coupled" and "loosely-coupled" approaches. Several sets of physics can then be linked together into logical hierarchies using any one of these coupling strategies, allowing for several potential solution strategies. For instance, a complex nuclear reactor model might consist of several tightly-coupled systems of fully-coupled equations.

Finally, MOOSE's Transfers system ties all of the physics groups contained within the Multiapp system together and allows for full control over the flow of information among the various groups. This capability bridges physical phenomena from several different complementary scales simultaneously. When these three MOOSE systems are combined, myriad coupling combinations are possible. In all cases, the MOOSE framework handles the parallel communication, input, output and execution of the underlying simulation. By handling these computer science tasks, the MOOSE framework keeps modelers focused on doing research.

MOOSE innovates by building advanced simulation capabilities on top of the very best available software technologies in a way that makes them widely accessible for innovative research. MOOSE is equally capable of solving small models on common laptops and the very biggest FEM models ever attempted—all without any major changes to configuration or source code. Since its inception, the MOOSE project has focused on both developer and computational efficiency. Improved developer efficiency is achieved by leveraging existing algorithms and technologies from several leading open-source packages. Additionally, MOOSE uses several complementary parallel technologies (both the distributed-memory message passing paradigm and shared-memory thread-based approaches are used) to lay an efficient computational foundation for development. Using existing open technologies in this manner helps the developers reduce the scope of the project and keeps the size of the MOOSE code base maintainable. This approach provides users with state-of-the-art finite element and solver technology as a basis for the advanced coupling and solution strategies mentioned previously.

MOOSE's developers work openly with other package developers to make sure that cutting-edge technologies are available through MOOSE, providing researchers with competitive research opportunities. MOOSE maintains a set of objects that hide parallel interfaces while exposing advanced spatial and temporal coupling algorithms in the framework. This accessible approach places developmental technology into the hands of scientists and engineers, which can speed the pace of scientific discovery.

Assumptions and Dependencies

The Reactor application is developed using MOOSE and is based on various modules, as such the RTM for Reactor is dependent upon the files listed at the beginning of this document.

Pre-test Instructions/Environment/Setup

Ideally all testing should be performed on a clean test machine following one of the supported configurations setup by the test system engineer. Testing may be performed on local workstations and cluster systems containing supported operating systems.

The repository should be clean prior to building and testing. When using "git" this can be done by doing a force clean in the main repository and each one of the submodules:


git clean -xfd
git submodule foreach 'git clean -xfd'

All tests must pass in accordance with the type of test being performed. This list can be found in the Software Test Plan.

System Requirements Traceability

Functional Requirements

Usability Requirements

Performance Requirements

System Interface Requirements

References

No citations exist within this document.