A predictive multiscale numerical framework for emulsion flow

乳液流动的预测多尺度数值框架

• 批准号: RGPIN-2016-04098
• 负责人: Komrakova, Alexandra
• 金额: $ 3.5万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760209
• 关键词: predictive; multiscale; numerical; framework; emulsion

The pharmaceutical, cosmetics, and food industries have undertaken substantial efforts to create stable liquid-liquid emulsions that satisfy customers with the unique properties of their products (e.g., bioavailability, texture, and taste). At the same time, the oil sands industry has worked to develop efficient methods to separate leftover bitumen and water as a way of reducing the accumulation of tailings ponds, which have a negative impact on everyone in the Athabasca River watershed. The common challenge for each industry is insufficient understanding of the complex nature of the interaction of two immiscible liquids, which leads to the formation and annihilation of drops. The distribution of drop sizes, as a function of liquid properties and flow conditions, defines the emulsion characteristics, including its stability, viscosity, and rheology. To control the properties of the emulsion product, a reliable prediction of the drop size distribution is essential.In this program, the aim is to develop a multiscale numerical framework for in-depth study of the liquid-liquid systems on a fundamental level. This will foster the resolution of practical problems. Direct numerical simulations will be performed to elucidate the liquid-liquid interactions on a micro scale, thereby accounting for the formation of submicron drops. Generation of these drops is necessary to achieve stable emulsions, and it is highly undesirable if the two liquids are eventually separated (e.g., bitumen and water). The gained data will be used to establish new, well-grounded sub-models that describe breakup and coalescence events. The new sub-models will overcome the limitations of the existing ones by accounting for more physical phenomena that affect liquid-liquid interactions. The improved sub-models will be embedded as the source terms of the population balance equation (PBE). The latter will be coupled with a computational fluid dynamics (CFD) solver. With the improved kernels, the created numerical instrument can be considered an original and innovative virtual laboratory to study dispersed systems. The interaction between micro events occurring on a drop scale will be correlated with the macroscale evolution of the entire system.The intended level of resolution of emulsion flows will result in state-of-the-art numerical simulations that will be performed using advanced computing facilities deployed by Compute Canada. The proposed program is motivated by the frontier industrial challenges that require deep understanding of the problems on a fundamental level. Integration of world class computing platforms and an academic program that involves exploration of complex physical phenomena will result in cutting-edge discoveries and innovations that will attract excellent researchers and promote training of highly qualified personnel.

制药、化妆品和食品工业已经进行了大量的努力来产生稳定的液-液乳液，其使客户满意其产品的独特性质（例如，生物利用度、质地和味道）。与此同时，油砂行业一直在努力开发有效的方法来分离剩余的沥青和水，以减少尾矿池的积累，这对阿萨巴斯卡河流域的每个人都有负面影响。每个行业面临的共同挑战是对两种不混溶液体相互作用的复杂性质的理解不足，这导致了液滴的形成和湮灭。液滴尺寸的分布，作为液体性质和流动条件的函数，定义了乳液特性，包括其稳定性、粘度和流变性。为了控制乳液产品的性质，液滴尺寸分布的可靠预测是必不可少的。在这个程序中，目的是开发一个多尺度的数值框架，深入研究的液-液系统的基本水平。这将有助于解决实际问题。将进行直接数值模拟，以阐明在微观尺度上的液-液相互作用，从而占亚微米液滴的形成。这些液滴的产生对于获得稳定的乳液是必要的，并且如果两种液体最终分离（例如，沥青和水）。所获得的数据将用于建立新的、有充分依据的子模型，描述分裂和合并事件。新的子模型将克服现有模型的局限性，考虑更多的物理现象，影响液-液相互作用。改进后的子模型将被嵌入作为人口平衡方程（PBE）的源项。后者将与计算流体动力学（CFD）求解器相结合。有了改进的内核，创建的数字仪器可以被认为是一个原始的和创新的虚拟实验室，研究分散系统。在液滴尺度上发生的微观事件之间的相互作用将与整个系统的宏观尺度演变相关联。乳液流的预期分辨率水平将导致最先进的数值模拟，该模拟将使用加拿大计算公司部署的先进计算设施进行。该计划的动机是前沿的工业挑战，需要在基础层面上深入了解问题。世界一流的计算平台和涉及复杂物理现象探索的学术计划的整合将导致尖端的发现和创新，这将吸引优秀的研究人员并促进高素质人才的培养。