MCSIMus: Monte Carlo Simulation with Inline Multiphysics
MCSIMus: Monte Carlo Simulation with Inline Multiphysics
批准号:
EP/W037165/1
负责人:
Paul Cosgrove
金额:
$44.47万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE
随机射线方法与多组蒙特卡罗:OpenMC 和 SCONE 中的特征方法
DOI:
10.1080/00295639.2023.2270618
发表时间:
2023
期刊:
Nuclear Science and Engineering
影响因子:
1.2
作者:
[Cosgrove P]
通讯作者:
Cosgrove P
A memory-efficient neutron noise algorithm for reactor physics
用于反应堆物理的内存高效中子噪声算法
DOI:
10.1016/j.anucene.2024.110450
发表时间:
2024
期刊:
Annals of Nuclear Energy
影响因子:
1.9
作者:
[Cosgrove P]
通讯作者:
Cosgrove P
国内基金
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