课题基金 / 基金详情

Predictive Modelling for Nuclear Engineering

Predictive Modelling for Nuclear Engineering
核工程预测模型
批准号:
EP/M022684/1
负责人:
Andrew Buchan
金额:
$84.37万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

项目摘要

项目成果

Andrew Buchan的其他基金

相似基金

相关文献

中文摘要
翻译
几十年来,计算机模型在评估核电设施的行为方面发挥了核心作用,它们确保了核操作对公众和环境都是安全的。该项目的目的是开发一种新的、高度先进的、准确、稳健和经过验证的建模能力。将形成一个新的多物理预测模型框架,用于模拟中子输运、流体流动和结构相互作用问题。它的目标是结合数值方法和高性能计算方面的新的和世界领先的技术,形成一个用于几何复杂的核工程问题的模拟工具。这将超过目前的计算能力,通过使用有效的自适应分辨率来提供建模精度,并将解决诸如全堆芯反应堆建模等重大挑战问题。该模型将在一个预测性框架内开发,该框架将建模与不确定性和实验数据相结合。这是一个至关重要的组成部分,因为数据、几何、参数和测量中的固有不确定性将在建模预测中带来不确定性。通过将这些不确定性整合到计算中,我们可以量化它们对最终结果的不确定性。所有这些技术的结合将产生第一个此类建模框架,通过结合不确定性量化和数据同化的优化分辨率提供前所未有的细节。它将大大改进对核设施的分析,提高运作效率,并最终帮助确保其安全。该项目将与英国国内外的世界领先的学术界和产业界密切合作。这种合作将导致这些技术被用于分析未来的反应堆设计,包括那些将于未来几年在英国建造的反应堆。
英文摘要
Computer models have played a central role in assessing the behaviour of nuclear power facilities for decades, they have ensured nuclear operations remain safe to both the public and the environment. The aim of the project is to develop a new and highly advanced modelling capability that is accurate, robust and validated. A new multi-physics, predictive modelling framework will be formed for simulating neutron transport, fluid flows and structural interaction problems. It aims to combine novel and world leading technologies in numerical methods and high performance computing to form a simulation tool for geometrically complex, nuclear engineering problems. This will surpass current computational capabilities, by providing modelling accuracy through the use of efficient adaptive resolution, and will tackle grand challenge problems such as full core reactor modelling. This model will be developed within a predictive framework that combines modelling with uncertainty and experimental data. This is a vital component as inherent uncertainties in data, geometry, parameterisations and measurement will place uncertainties in the modelled predictions. By integrating these uncertainties within the calculations we can quantify the uncertainty they place on the final result. The combination of all these technologies will result in the first modelling framework of its kind, offering unprecedented detail through optimised resolution with combined uncertainty quantification and data assimilation. It will provide substantially improved analysis of nuclear facilities, improve operational efficiency and, ultimately, help ensure its safety. The project will work closely with world leading academics and industry, both within the UK and overseas. This collaboration will result in the technologies being used to analyse future reactor designs, including those reactors due to be built in the UK over the coming years.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.jcp.2019.109124
发表时间: 2019-01
期刊: J. Comput. Phys.
影响因子: --
作者: [S. Dargaville;A. Buchan;R. Smedley-Stevenson;Paul N. Smith;C. Pain]
通讯作者: S. Dargaville;A. Buchan;R. Smedley-Stevenson;Paul N. Smith;C. Pain
DOI: 10.1038/s41598-021-99204-0
发表时间: 2021-10-07
期刊: Scientific reports
影响因子: 4.6
作者: [Buchan AG, Yang L, Welch D, Brenner DJ, Atkinson KD]
通讯作者: Atkinson KD
DOI: 10.1038/s41598-020-76597-y
发表时间: 2020-11-12
期刊: Scientific reports
影响因子: 4.6
作者: [Buchan AG, Yang L, Atkinson KD]
通讯作者: Atkinson KD
A comparison of element agglomeration algorithms for unstructured geometric multigrid
非结构化几何多重网格的元素聚集算法比较
DOI: 10.1016/j.cam.2020.113379
发表时间: 2021
期刊: Journal of Computational and Applied Mathematics
影响因子: 2.4
作者: [Dargaville S]
通讯作者: Dargaville S
10
    Predictive Modelling for Nuclear Engineering
    • 批准号:
      EP/M022684/2
    • 项目类别:
      Fellowship
    • 资助金额:
      $59.14万
    • 财政年份:
      2017
    • 负责人:
      Andrew Buchan
    • 依托单位:
    国内基金
    海外基金
    Improving modelling of compact binary evolution.
    • 批准号:
      10903001
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      20.0万元
    • 批准年份:
      2009
    • 负责人:
      史蒂芬
    • 依托单位: