PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE)

多相系统不确定性量化的预测建模 (PREMIERE)

• 批准号: EP/T000414/1
• 负责人: Omar Matar
• 金额: $ 835.94万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT000414%2F1
• 关键词: PREdictive; Modelling; QuantIfication; UncERtainty; MultiphasE

PREMIERE will integrate challenges identified by the EPSRC Prosperity Outcomes and the Industrial Strategy Challenge Fund (ISCF) in healthcare (Healthy Nation), energy (Resilient Nation), manufacturing and digital technologies (Resilient Nation, Productive Nation) as areas to drive economic growth. The programme will bring together a multi-disciplinary team of researchers to create unprecedented impact in these sectors through the creation of a next-generation predictive framework for complex multiphase systems. Importantly, the framework methodology will span purely physics-driven, CFD-mediated solutions at one extreme, and data-centric solutions at the other where the complexity of the phenomena masks the underlying physics. The framework will advance the current state-of-the-art in uncertainty quantification, adjoint sensitivity, data-assimilation, ensemble methods, CFD, and design of experiments to 'blend' the two extremes in order to create ultra-fast multi-fidelity, predictive models, supported by cutting-edge experimental investigations. This transformative technology will be sufficiently generic so as to address a wide spectrum of challenges across the ISCF areas, and will empower the user with optimal compromises between off-line (modelling) and on-line (simulation) efforts so as to meet an a priori 'error bar' on the model outputs. The investigators' synergy, and their long-standing industrial collaborations, will ensure that PREMIERE will result in a paradigm-shift in multiphase flow research worldwide. We will demonstrate our capabilities using exemplar challenges, of central importance to their respective sectors in close collaboration with our industrial and healthcare partners. Our PREMIERE framework will provide novel and more efficient manufacturing processes, reliable design tools for the oil-and-gas industry, which remove conservatism in design, improve safety management, and reduce emissions and carbon footprint. This framework will also provide enabling technology for the design, operation, and optimisation of the next-generation nuclear reactors, and associated reprocessing, as well as patient-specific therapies for diseases such as acute compartment syndrome.

PREMIERE将整合EPSRC繁荣成果和工业战略挑战基金（ISCF）在医疗保健（健康国家），能源（弹性国家），制造业和数字技术（弹性国家，生产力国家）方面确定的挑战，作为推动经济增长的领域。该计划将汇集一个多学科的研究人员团队，通过为复杂的多相系统创建下一代预测框架，在这些领域产生前所未有的影响。重要的是，框架方法将在一个极端跨越纯粹物理驱动的CFD介导的解决方案，在另一个极端以数据为中心的解决方案，其中现象的复杂性掩盖了底层物理。该框架将推进当前不确定性量化、伴随灵敏度、数据同化、集合方法、CFD和实验设计方面的最新技术，以“混合”两个极端，以创建超快的多保真度预测模型，并得到前沿实验研究的支持。这一变革性技术将具有足够的通用性，以应对ISCF各领域的广泛挑战，并将使用户能够在离线（建模）和在线（模拟）工作之间实现最佳折衷，以满足模型输出的先验“误差线”。研究人员的协同作用和他们长期的工业合作将确保PREMIERE将导致全球多相流研究的范式转变。我们将与工业和医疗保健合作伙伴密切合作，利用对各自行业至关重要的典型挑战来展示我们的能力。我们的PREMIERE框架将为石油和天然气行业提供新颖、更高效的制造工艺和可靠的设计工具，消除设计中的保守性，改善安全管理，减少排放和碳足迹。这一框架还将为下一代核反应堆的设计、运行和优化提供技术支持，以及相关的后处理，以及针对急性筋膜室综合征等疾病的患者特异性治疗。

项目成果

Interaction of two non-coalescing bubbles rising in a non-isothermal self-rewetting fluid

• DOI: 10.1016/j.euromechflu.2021.01.009
• 发表时间: 2021-05
• 期刊: European Journal of Mechanics - B/Fluids
• 作者: Mounika Balla;M. Tripathi;O. Matar;K. Sahu

Linear stability analysis of Taylor bubble motion in downward flowing liquids in vertical tubes

垂直管内向下流动液体泰勒气泡运动的线性稳定性分析

• DOI: 10.1017/jfm.2022.261
• 发表时间: 2022
• 期刊: Journal of Fluid Mechanics
• 影响因子: 3.7
• 作者: Abubakar H

Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian optimisation-CFD approach

• DOI: 10.1016/j.cej.2023.145217
• 发表时间: 2023-08-16
• 期刊: CHEMICAL ENGINEERING JOURNAL
• 影响因子: 15.1
• 作者: Basha，Nausheen;Savage，Thomas;Matar，Omar K.
• 通讯作者: Matar，Omar K.

Effect of surfactant on elongated bubbles in capillary tubes at high Reynolds number

表面活性剂对高雷诺数毛细管内拉长气泡的影响

• DOI: 10.1103/physrevfluids.5.093605
• 发表时间: 2020
• 期刊: Physical Review Fluids
• 影响因子: 2.7
• 作者: Batchvarov A

Three-dimensional dynamics of falling films in the presence of insoluble surfactants

• DOI: 10.1017/jfm.2020.796
• 发表时间: 2020-05
• 期刊: Journal of Fluid Mechanics
• 影响因子: 3.7
• 作者: A. Batchvarov;L. Kahouadji;C. Constante-Amores;Gabriel Farah Norões Gonçalves;Seungwon Shin;J. Chergui;D. Juric;R. Craster;O. Matar