MCSIMus: Monte Carlo Simulation with Inline Multiphysics
Lead Research Organisation:
University of Cambridge
Department Name: Engineering
Abstract
Nuclear reactors in various forms are increasingly prominent in the context of net zero. However, stringent safety standards and advanced reactor designs necessitate ever-greater certainty and understanding in reactor physics and operation. As physical experimentation becomes more expensive, nuclear engineering relies increasingly on high-fidelity simulation of reactors.
Traditionally, resolving different physical phenomena in a reactor (such as neutron transport or thermal-hydraulics) proceeded by assuming only a weak dependence upon other phenomena due to limits on computational power. Such approximations were allowable when additional conservatisms were included in reactor designs. However, more economical or sophisticated reactor designs render such approximations invalid, and reactor designers must be able to resolve the interplay between each physical phenomenon. This poses a challenge to reactor physicists due to vastly increased computational costs of multi-physics calculations, as well as the risks of numerical instabilities - these are essentially non-physical behaviours which are purely an artefact of simulation.
This proposal aims to provide the basis of new computational approaches in nuclear engineering which are both substantially cheaper and more stable than present multi-physics approaches. Traditional methods tend to have one tool fully resolve one phenomenon, pass the information to another tool which resolves a second phenomenon, and then pass this updated information back to the first tool and repeat until (hopefully) the results converge. This proposal hopes to explore a slightly simpler approach, where information is exchanged between different solvers before each has fully resolved its own physics, extending this to many of the phenomena of interest to a reactor designer. Preliminary analysis suggests that this approach should be vastly more stable and computationally efficient than previous methods. The investigations will be carried out using home-grown numerical tools developed at the University of Cambridge which are designed for rapid prototyping of new ideas and algorithms. The final result is anticipated to transform the nuclear industry's approach to multi-physics calculations and greatly accelerate our ability to explore and design more advanced nuclear reactors.
Traditionally, resolving different physical phenomena in a reactor (such as neutron transport or thermal-hydraulics) proceeded by assuming only a weak dependence upon other phenomena due to limits on computational power. Such approximations were allowable when additional conservatisms were included in reactor designs. However, more economical or sophisticated reactor designs render such approximations invalid, and reactor designers must be able to resolve the interplay between each physical phenomenon. This poses a challenge to reactor physicists due to vastly increased computational costs of multi-physics calculations, as well as the risks of numerical instabilities - these are essentially non-physical behaviours which are purely an artefact of simulation.
This proposal aims to provide the basis of new computational approaches in nuclear engineering which are both substantially cheaper and more stable than present multi-physics approaches. Traditional methods tend to have one tool fully resolve one phenomenon, pass the information to another tool which resolves a second phenomenon, and then pass this updated information back to the first tool and repeat until (hopefully) the results converge. This proposal hopes to explore a slightly simpler approach, where information is exchanged between different solvers before each has fully resolved its own physics, extending this to many of the phenomena of interest to a reactor designer. Preliminary analysis suggests that this approach should be vastly more stable and computationally efficient than previous methods. The investigations will be carried out using home-grown numerical tools developed at the University of Cambridge which are designed for rapid prototyping of new ideas and algorithms. The final result is anticipated to transform the nuclear industry's approach to multi-physics calculations and greatly accelerate our ability to explore and design more advanced nuclear reactors.
People |
ORCID iD |
Paul Cosgrove (Principal Investigator / Fellow) |
Publications
Cosgrove P
(2023)
The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE
in Nuclear Science and Engineering
Cosgrove P
(2024)
A memory-efficient neutron noise algorithm for reactor physics
in Annals of Nuclear Energy
P. Cosgrove
(2024)
The random ray method applied to fixed source transport problems
R. Neame
(2024)
Linear Source Approximation in The Random Ray Method
Description | Random ray work with Argonne |
Organisation | Argonne National Laboratory |
Country | United States |
Sector | Public |
PI Contribution | We worked together on several papers with ANL members |
Collaborator Contribution | Intellectual contributions and discussions to creating papers. |
Impact | Several of the papers published so far are directly attributable to this collaboration. |
Start Year | 2023 |