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Predictive Modelling for Nuclear Engineering

Predictive Modelling for Nuclear Engineering
核工程预测模型
批准号:
EP/M022684/2
负责人:
Andrew Buchan
金额:
$59.14万
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

Andrew Buchan的其他基金

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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,它们确保了核运行对公众和环境都是安全的。该项目的目标是开发一种新的、高度先进的建模能力,这种能力是准确的、健壮的和经过验证的。为模拟中子输运、流体流动和结构相互作用问题,将形成一个新的多物理场预测建模框架。它旨在结合数值方法和高性能计算方面的新颖和世界领先技术,形成几何复杂核工程问题的模拟工具。这将超越目前的计算能力,通过使用有效的自适应分辨率提供建模精度,并将解决诸如全堆芯建模等重大挑战问题。该模型将在一个预测框架内开发,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、参数化和测量中的固有不确定性会给建模预测带来不确定性。通过在计算中整合这些不确定性,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同类中的第一个建模框架,通过优化的分辨率,结合不确定性量化和数据同化,提供前所未有的细节。它将大大改进对核设施的分析,提高运行效率,并最终帮助确保核设施的安全。该项目将与英国和海外的世界领先学者和行业密切合作。这一合作将导致技术被用于分析未来的反应堆设计,包括那些将在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)
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科研奖励(0)
会议论文
DOI: 10.1016/j.jcp.2020.109759
发表时间: 2019-11
期刊: ArXiv
影响因子: --
作者: [Steven Dargaville-;R. Smedley-Stevenson;Paul N. Smith;C. Pain]
通讯作者: Steven Dargaville-;R. Smedley-Stevenson;Paul N. Smith;C. Pain
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
9
    Predictive Modelling for Nuclear Engineering
    • 批准号:
      EP/M022684/1
    • 项目类别:
      Fellowship
    • 资助金额:
      $84.37万
    • 财政年份:
      2016
    • 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: