New Phase Field Models for Unravelling Multi-Physics Material Degradation Challenges (NEWPHASE)

最大的科学和工程挑战往往存在于不同学科之间。多年来，我们对材料在机械载荷(固体力学)作用下的行为有了很好的了解。我们还了解当材料暴露在特定环境(电化学)中时发生的化学反应的性质。然而，预测由于机械载荷和退化环境的共同暴露而导致的材料行为仍然是一个难以实现的目标。由于材料在许多应用中对环境和机械降解非常敏感，因此不能理解和预测电化学-力学现象是要付出巨大代价的。在这项研究中进行的基础科学的价值将在以下两个应用中得到证明：(1)腐蚀损害，(2)锂离子电池。它们的重要性怎么强调都不为过。仅在英国，由于腐蚀而导致的结构和工业部件的失效每年就会造成惊人的460亿GB的损失。锂离子电池是实现普遍获得可靠、清洁、可持续能源的关键因素。现在，有机会开发能够防止腐蚀故障的模型，并显著促进电池技术的进步。更大的计算机资源和新的算法能够模拟并行(耦合)的物理过程，如化学反应、物种扩散和机械变形；所谓的多物理建模。然而，由于我们无法模拟两个不同阶段之间的边界如何随着时间的推移而发展，因此在多物理模拟的成功基础上预测材料退化的机会受到了阻碍。例如，腐蚀通常是不均匀的，导致小缺陷(凹坑)生长并充当裂纹启动者。防止相关的灾难性故障，如莫兰迪大桥坍塌，需要捕获这些缺陷将如何在电解液-材料界面形核和生长。但长期以来，对不断演变的界面中的形态变化进行建模一直被认为是一个数学和计算方面的挑战。我将克服这个长期存在的障碍，使用一个辅助的“相位场”变量，在一个小的漫射区域上涂抹“尖锐”的界面--这是一种范式的改变，它将使对不断演变的界面的跟踪变得易于数值计算。新一代模型将利用X射线计算机层析成像等强大的3D技术进行开发和验证，这些技术在空间分辨率和图像重建时间方面都有了显著的改善。通过明确捕捉破坏过程，该研究金不仅将在理解多物理材料降解现象方面开辟新的视野，还将为在工程实践中引入基于模拟的评估奠定基础；模型预测可以与检查数据进行比较，将“数字孪生”和“虚拟测试”范例引入涉及苛刻环境的工程应用。近期的社会影响将通过解决海上能源、电池、供水网络和核裂变方面的突出技术问题来展示。这些努力将由奖学金顾问委员会指导，该委员会包括以下每个行业的领先公司：法国电力能源公司、劳斯莱斯公司、苏伊士集团、PA咨询公司、Vtenfall和海底7。例如，开发的新一代模型将用于帮助世界上最古老的大型风力发电场Horns Rev 1的寿命延长决策。从这项世界首个工程评估中吸取的经验教训将为整个行业树立榜样，并展示计算机模拟在提高领先可再生能源的经济可行性方面的潜力。这项成功的奖学金将为新的工程解决方案奠定科学基础，这些解决方案将提高英国的竞争力和我们的生活质量。

The biggest scientific and engineering challenges often lie in between disciplines. Through the years, we have gained a good understanding of how materials behave when subjected to mechanical loads (solid mechanics). We also understand the nature of the chemical reactions occurring when materials are exposed to a given environment (electrochemistry). However, predicting material behaviour due to combined exposure to mechanical loads and a degrading environment continues to be an elusive goal. Not being able to understand and predict electro-chemo-mechanics phenomena comes at a great cost since materials are very sensitive to environmental and mechanical degradation in many applications. The value of the fundamental science conducted in this fellowship will be demonstrated on two of these applications: (1) corrosion damage, and (2) Li-Ion batteries. Their importance cannot be emphasised enough. Solely in the UK, failure of structures and industrial components due to corrosion entails a staggering cost of £46 billion per annum. Li-Ion batteries are key enablers in achieving universal access to reliable, clean, sustainable energy.Now, there is an opportunity to develop models that can prevent corrosion failures and significantly enhance progress in battery technology. Larger computer resources and new algorithms enable simulating concurrent (coupled) physical processes such as chemical reactions, diffusion of species and mechanical deformation; so-called multi-physics modelling. However, the opportunity of building upon the success of multi-physics simulations to predict material degradation is held back due to our inability to model how the boundary between two different phases develops over time. For example, corrosion is often non-uniform, leading to small defects (pits) that grow and act as crack initiators. Preventing the associated catastrophic failures, such as the Morandi Bridge collapse, requires capturing how these defects will nucleate at the electrolyte-material interface and grow. But the modelling of morphological changes in an evolving interface has been long considered a mathematical and computational challenge. I will overcome this longstanding obstacle by smearing the "sharp" interface over a small diffuse region using an auxiliary "phase field" variable - a paradigm change that will make tracking of evolving interfaces amenable to numerical computations. A new generation of models will be developed and validated with powerful 3D techniques such as X-ray Computed Tomography, which have timely experienced notable improvements in spatial resolution and image reconstruction times. By explicitly capturing the damage process, this fellowship will not only open new horizons in the understanding of multi-physics material degradation phenomena but also set the basis for the introduction of simulation-based assessment in engineering practice; model predictions can be compared with inspection data, introducing the "Digital Twins" and "Virtual Testing" paradigms into engineering applications involving demanding environments.The near-term societal impact will be demonstrated by addressing salient technological problems in offshore energy, batteries, water supply networks and nuclear fission. Efforts will be guided by the fellowship advisory board, which includes leading firms in each of these sectors: EDF Energy, Rolls-Royce, SUEZ, PA Consulting, Vattenfall and Subsea7. For example, the new generation of models developed will be used to assist in the life extension decision of the oldest large-scale wind farm in the world, Horns Rev 1. The lessons learned in this world-first engineering assessment will set an example for the entire sector and demonstrate the potential of computer simulations in enhancing the economic viability of the leading renewable energy source. The successful fellowship will lay scientific foundations for new engineering solutions that will improve UK's competitiveness and our quality of life.