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Reducing risk through uncertainty quantification for past, present and future generations of nuclear power plants

通过过去、现在和未来各代核电站的不确定性量化来降低风险

基本信息

批准号：
EP/R012423/1
负责人：
Neil Bourne
金额：
$ 46.03万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FR012423%2F1
关键词：
Reducing risk through uncertainty quantification

项目摘要

To ensure national resilience and productivity in an uncertain world, the UK needs a safe, reliable energy supply. Electricity generated by domestic nuclear fission plant creates an important contribution to this, currently generating around one sixth of the UK's requirements. Future fusion-powered plant provide a vision of lower waste, higher safety energy generation from essentially limitless fuel.However, poor public perception of nuclear safety is limiting uptake, whilst poor understanding of the behaviour of critical nuclear materials exposed to thermal, mechanical and radiation loading increases engineering uncertainty, hence escalating design risk and operational cost.This programme of research uses a multi-scale, multi-technique approach, combining high performance computer models with imaging analysis, to build a deeper understanding of the mechanical behaviour of several vital engineering materials subject to such stresses: * silicon ceramics used for the containment of historic nuclear waste, * graphite used for moderating reactions in the current generation of nuclear plant, * beryllium and tungsten used to line containment vessels for future fusion generation.Developing better, experimentally-validated models of the structural integrity of such vital components will enable increased accuracy in design, hence reducing the cost of build and operation of power generation and waste storage facilities and giving greater public confidence in the industry. The research combines the strengths of two computational approaches:* Fully physically-based materials models, which are well-developed, but are not yet applicable to large and complex engineering systems;* Empirical engineering models, which are useful in the domain for which they have been calibrated, but currently have limited transferability; along with rigorous error analysis, to create an approach that is transferable across length scales, enabling the tracking of fundamental physical mechanisms through to engineering application.The experimental elements of the programme, using X-ray tomography to create 3D images of strain and damage inside samples and Digital Image Correlation to track real-time crack propagation, will provide new insight into the behaviour of these critical materials under stress and observational parameters to inform the modelling.The project will draw from the strengths of the interdisciplinary team to develop experts of the future. It will involve and inform industrial partners and other key stakeholders, from regulators to plant workers, to ensure results are relevant to and taken up by UK energy generation and other strategically important industries.

为了在一个不确定的世界中确保国家的弹性和生产力，英国需要一个安全、可靠的能源供应。国内核裂变工厂产生的电力对此做出了重要贡献，目前产生的电力约占英国需求的六分之一。未来的核聚变发电厂提供了一个愿景，即从本质上无限的燃料中产生更低的废物，更高的安全性。然而，公众对核安全的不良认识限制了对核安全的吸收，而对暴露于热、机械和辐射负荷下的关键核材料的行为的不了解增加了工程的不确定性，从而增加了设计风险和运行成本。本研究项目采用多尺度、多技术的方法，将高性能计算机模型与成像分析相结合，以更深入地了解几种重要工程材料在这种应力下的机械行为：*硅陶瓷用于遏制历史核废料，*石墨用于缓和当前核电站的反应，*铍和钨用于未来核聚变发电的安全壳。开发更好的、经过实验验证的这些重要部件的结构完整性模型，将提高设计的准确性，从而降低发电和废物储存设施的建造和运营成本，并增强公众对该行业的信心。该研究结合了两种计算方法的优势：*完全基于物理的材料模型，这是发达的，但还不适用于大型和复杂的工程系统；*经验工程模型，在它们被校准的领域是有用的，但目前具有有限的可转移性；通过严格的误差分析，创建了一种可跨长度尺度转移的方法，从而可以通过工程应用跟踪基本物理机制。该项目的实验元素，使用x射线断层扫描技术创建样品内部应变和损伤的3D图像，并使用数字图像相关技术跟踪实时裂纹扩展，将为这些关键材料在应力和观测参数下的行为提供新的见解，从而为建模提供信息。该项目将借鉴跨学科团队的优势，培养未来的专家。它将涉及并告知工业合作伙伴和其他主要利益相关者，从监管机构到工厂工人，以确保结果与英国能源发电和其他具有重要战略意义的行业相关并被采用。