Rattlesnake is built on the MOOSE framework. Rattlesnake manages meshes with libMesh [25] and solves the system equation with PETSc [26] through MOOSE. Support of unstructured meshes, parallelization with domain decomposition, various time integration schemes, most of nonlinear solvers features, multiphysics coupling are all inherited from the framework. Rattlesnake is responsible for setting up the discretization of RTE with interfaces provided by MOOSE. Because Rattlesnake is built on a general framework, it can perform calculations in 1D, 2D and 3D unstructured meshes via MPI (message passing interface) [27] and multi-threading. The weak forms can be directly translated into code under the MOOSE framework, which results in codes easy to maintain and extend. Multiple developers can co-work seamlessly on Rattlesnake. This development pattern allows splitting the work into the physics-related items residing in Rattlesnake, and physics-irrelevant items residing in the framework. The benefit is twofold: Rattlesnake can push the development on the framework side, which can benefit all the other MOOSE-based applications and any improvements in MOOSE can improve Rattlesnake. For example, the common software development procedure is managed by MOOSE, e.g. the version control, regression tests, on-line documentation. In addition, coupling Rattlesnake with other MOOSE-based applications dealing with other physics is straightforward because these applications are based on the same framework. As an example, the reactor physics application MAMMOTH [2, 28] leverages components spread over Rattlesnake, MOOSE and its modules, Bison [29, 30, 31], and Relap-7 [32]. In summary, being built on MOOSE makes Rattlesnake powerful and unique. There indeed are constraints imposed by the framework, but this is not insurmountable and outweighted by all the advantages provided by this development pattern. In Section 2, we first state the RTE for various particles. Currently, we only consider two particles: neutron and thermal radiation but Rattlesnake can be extended easily to other types. Particles mostly share the same time derivative,

In this work, we provide a fully-implicit implementation of the time-dependent, filtered spherical harmonics (FP N ) equations for non-linear, thermal radiative transfer. We investigate local filtering strategies and analyze the effect of the filter on the conditioning of the system, showing in particular that the filter improves the convergence properties of the iterative solver. We also investigate numerically the rigorous error estimates derived in the linear setting, to determine whether they hold also for the non-linear case. Finally, we simulate a standard test problem on an unstructured mesh and make comparisons with implicit Monte-Carlo (IMC) calculations.

Advanced reactor concepts span the spectrum from heat pipe-cooled microreactors, through thermal and fast molten-salt reactors, to gas-and salt-cooled pebble bed reactors. The modeling and simulation of each of these reactor types comes with their own geometrical complexities and multiphysics challenges. However, the common theme for all nuclear reactors is the necessity to be able to accurately predict neutron distribution in the presence of multiphysics feedback. We argue that the current standards of modeling and simulation, which couple single-physics, single-reactor-focused codes via ad hoc methods, are not sufficiently flexible to address the challenges of modeling and simulation for advanced reactors. In this work, we present the Multiphysics Object Oriented Simulation Environment (MOOSE)-based radiation transport application Rattlesnake. The use of Rattlesnake for the modeling and simulation of nuclear reactors represents a paradigm shift away from makeshift data exchange methods, as it is developed based on the MOOSE platform with its very natural form of shared data distribution. Rattlesnake is well equipped for addressing the geometric and multiphysics challenges of advanced reactor concepts because it is a flexible finite element tool that leverages the multiphysics capabilities inherent in MOOSE. This paper focuses on the concept and design of Rattlesnake. We also demonstrate the capabilities and performance of Rattlesnake with a set of problems including a microreactor, a molten-salt reactor, a pebble bed reactor, the Advanced Test Reactor at the Idaho National Laboratory, and two benchmarks: a multiphysics version of the C5G7 benchmark and the LRA benchmark.

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program, the DireWolf software application's objective is to provide the nuclear community with a design and safety analysis simulation capability. Based upon the NEAMS program Multiphysics Object-Oriented Simulation Environment (MOOSE) computational framework, DireWolf tightly couples nuclear microreactor physics, reactor physics, radiation transport, nuclear fuel performance, heat pipe thermal hydraulics, power generation, and structural mechanics to resolve the interdependent nonlinearities. DireWolf is capable of simulating both steady and transient normal reactor operation and several postulated failure scenarios. We will present the fundamental physics of heat pipe-cooled nuclear microreactors and the MOOSE-based software employed in DireWolf. Both steady and transient results for coupled reactor physics, radiation transport, and nuclear fuel performance are demonstrated.