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学科之间。多年来，我们已经很好地理解了材料在受到机械载荷（固体力学）时的行为。我们还了解了当材料暴露于给定环境（电化学）时发生的化学反应的性质。然而，由于机械载荷和降解环境的联合暴露，预测材料的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，因此无法理解和预测电化学力学现象的代价很大。在本奖学金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)腐蚀损伤，(2)锂离子电池。它们的重要性怎么强调都不为过。仅在英国，由于腐蚀导致的结构和工业部件失效每年就需要花费惊人的460亿英镑。锂离子电池是实现普遍获得可靠、清洁、可持续能源的关键推动者。现在，有机会开发出能够防止腐蚀失效的模型，并显著提高电池技术的进步。更大的计算机资源和新的算法能够模拟并发（耦合）物理过程，如化学反应，物质扩散和机械变形；所谓的多物理场建模。然而，建立在多物理场模拟的成功基础上预测材料降解的机会受到阻碍，因为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。例如，腐蚀通常是不均匀的，导致小缺陷（凹坑）的生长，并作为裂纹的起始点。防止相关的灾难性故障，如莫兰迪桥坍塌，需要捕获这些缺陷如何在电解质-材料界面成核并生长。但是在一个不断进化的界面中，形态变化的建模一直被认为是一个数学和计算上的挑战。我将通过使用一个辅助的“相场”变量在一个小的漫射区域上涂抹“尖锐”界面来克服这个长期存在的障碍——这是一个范式的改变，将使跟踪不断发展的界面适合于数值计算。新一代的模型将开发和验证强大的3D技术，如x射线计算机断层扫描，及时经历了空间分辨率和图像重建时间的显着改进。通过明确捕获损伤过程，该研究不仅将为理解多物理场材料降解现象开辟新的视野，而且还将为在工程实践中引入基于模拟的评估奠定基础；模型预测可以与检测数据进行比较，将“数字双胞胎”和“虚拟测试”范例引入到涉及苛刻环境的工程应用中。近期的社会影响将通过解决近海能源、电池、供水网络和核裂变方面的突出技术问题来证明。奖学金顾问委员会将指导工作，该委员会包括这些领域的领先公司：EDF能源、劳斯莱斯、苏伊士、PA咨询、Vattenfall和Subsea7。例如，开发的新一代模型将用于协助世界上最古老的大型风力发电场霍恩斯Rev 1的寿命延长决策。在这个世界上第一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。成功的奖学金将为新的工程解决方案奠定科学基础，从而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.