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.
Organisations
- UNIVERSITY OF CAMBRIDGE (Lead Research Organisation)
- Argonne National Laboratory (Collaboration)
- University of Michigan (Collaboration)
- Amentum (Collaboration)
- Georgia Institute of Technology (Project Partner)
- Jacobs UK Limited (Project Partner)
- AWE PLC (Project Partner)
- IMPERIAL COLLEGE LONDON (Project Partner)
- University of Liverpool (Project Partner)
- EDF ENERGY R&D UK CENTRE LIMITED (Project Partner)
- UNITED KINGDOM ATOMIC ENERGY AUTHORITY (Project Partner)
People |
ORCID iD |
| Paul Cosgrove (Principal Investigator / Fellow) |
Publications
Cosgrove P
(2025)
On the practicalities of producing a nuclear weapon using high-assay low-enriched uranium
in Annals of Nuclear Energy
Cosgrove P
(2026)
Negative fluxes and cell-miss errors in the random ray method
in Progress in Nuclear Energy
Cosgrove P
(2024)
A memory-efficient neutron noise algorithm for reactor physics
in Annals of Nuclear Energy
Cosgrove P
(2023)
The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE
in Nuclear Science and Engineering
D'Auria F
(2024)
What is the future for nuclear fission technology? A technical opinion from the Guest Editors of VSI NFT series and the Editor of the Journal Nuclear Engineering and Design
in Nuclear Engineering and Design
Kraus M
(2025)
Time-Dependent Variants of The Random Ray Method for Transient Simulations
in Nuclear Science and Engineering
Neame R
(2024)
Linear Sources and Anisotropic Scattering in the Random Ray Method
in Nuclear Science and Engineering
| Description | There have been several significant developments to the 'random ray' method, an approach to radiation transport simulation. This project has significantly advanced its application to shielding problems and improved its readiness for industrial usage. The project demonstrated that the method is very well-suited to radiation shielding problems due to producing low errors in remote regions of radiation transport problems through deeply shielded material. We have demonstrated approaches to accelerating the method significantly, using 'linear sources' to coarsen the simulation mesh while maintaining accuracy and showing its particular applicability to GPUs. We have also demonstrated its use in accelerating the workhorse shielding method (Monte Carlo particle transport) by serving as a variance reduction tool. We also identified and corrected a deficiency of the method in fusion-like problems. These techniques are now implemented in OpenMC and used by the fusion industry. We have also advanced neutron noise techniques which are used for reactor monitoring. Simulating neutron noise has been made significantly less memory-intensive by a new algorithmic development proposed during the project. This should make this approach to reactor monitoring more readily accessible in the future. We have also developed several approaches to reducing variance in Monte Carlo particle transport, especially in time-dependent simulations which are used for characterising nuclear reactor behaviour during transients. We also improved on a previous mathematical proof of the error bounds for a Monte Carlo tallying technique; this provides greater assurance of robustness and performance when applying this technique in industrial settings. We also developed a new technique for analysing the convergence of stochastic algorithms in neutron transport. Previous approaches neglected stochasticity entirely, despite its known importance to convergence behaviour. This is a significant step forward for numerical analysis in nuclear engineering, as stochastic neutron transport methods are widely used. This technique was applied to the random ray method, providing further assurance of its robustness in industrial applications. |
| Exploitation Route | Many of the techniques developed have been implemented in industrial code, namely OpenMC. This is currently being used for large-scale radiation shielding calculations. The ANSWERS software suite, owned by Amentum, also plan on implementing several of the techniques developed. |
| Sectors | Aerospace Defence and Marine Energy |
| Description | Several of the findings have been implemented in industrial radiation transport tools such as OpenMC. These findings are directly used in large-scale radiation shielding problems for fusion applications by several companies. The techniques are also being implemented by Amentum into their code suite. |
| First Year Of Impact | 2025 |
| Sector | Aerospace, Defence and Marine,Energy |
| Impact Types | Economic |
| Title | Linear sources in the random ray method |
| Description | This algorithm allows meshes used in neutron transport to be significantly coarsened, reducing memory and runtime. The innovation is taking a previous model and extending it to the random ray method. This algorithm holds significant promise in radiation shielding applications. It is described in detail in https://www.tandfonline.com/doi/full/10.1080/00295639.2024.2394729 |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | This algorithm has been implemented in the widely used Monte Carlo code OpenMC. This will be applied to radiation shielding challenges in fusion simulations. |
| URL | https://www.tandfonline.com/doi/full/10.1080/00295639.2025.2458958?src=exp-la |
| Title | Memory efficient deterministic neutron noise algorithm |
| Description | A new algorithm was proposed to reduce the memory burden of deterministic neutron noise calculations. This can make these calculations more tractable, allowing their use as diagnostic tools in nuclear reactors. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | No impacts yet, but it is anticipated that this becomes a common algorithm in neutron noise applications. |
| URL | https://www.sciencedirect.com/science/article/pii/S0306454924001130 |
| Description | Multiphysics simulation with Amentum |
| Organisation | Amentum |
| Department | Amentum UK |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Amentum provided a prototype of a new multiphysics coupling script which one of my students adapted to work with SCONE and the random ray method. |
| Collaborator Contribution | They provided the coupling script and thermal-hydraulics solver. |
| Impact | The work will be presented at the ANSWERS Seminar 2026 and will also be the subject of future papers. Code modifications on the SCONE side will be uploaded to github. |
| Start Year | 2026 |
| 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 |
| Description | Random ray work with Michigan |
| Organisation | University of Michigan |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | One of my PhD students worked with University of Michigan to investigate the random ray method applied to multiphysics reactor problems. |
| Collaborator Contribution | The partner provided supervision and desk space to the student, as well as intellectual contributions. |
| Impact | We collaboratively devised a way of understanding the stability of the random ray method. This is the first time the convergence properties of a stochastic neutron transport algorithm has been handled without neglecting stochastic behaviour. It also accounts for peculiarities of the method which were not previously well understood. This allows the method to be used with more confidence and robustness in industrial settings. It also provides a route to analyse other stochastic neutronics algorithms, which are a mainstay in nuclear engineering analysis. This work has been accepted for publication at the PHYSOR 2026 conference and will be further expanded for a journal paper. |
| Start Year | 2025 |
| Title | SCONE |
| Description | Open-source modifiable neutron transport code. |
| Type Of Technology | Software |
| Year Produced | 2026 |
| Open Source License? | Yes |
| Impact | Research progress for methods in particle transport. Most researchers in the group now use SCONE in some capacity. Many of our masters students use it for projects. This has been the testing ground for several new developments in the random ray method which are now used for large-scale fusion shielding calculations. |
| URL | https://github.com/CambridgeNuclear/SCONE |