Collaborative Research: Efficient algorithms for free boundary flows of complex fluids

合作研究：复杂流体自由边界流的高效算法

• 批准号: 0811138
• 负责人: Giovanna Guidoboni
• 金额: $ 12.21万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0811138&HistoricalAwards=false
• 关键词: Collaborative; Research; Efficient; algorithms; free

In engineered and biological systems, flows often involve complexity because of the shape of the flow domain which can be unknown, and because the fluid can consist of or contain macromolecules and nanoparticles which impart unusual behavior. This research aims at developing novel numerical algorithms for computing flows with such complexity. Because of their robustness and reliability, fully-coupled (monolithic/implicit) schemes are commonly used to simulate flows with free boundaries; however, these schemes may become impractical, especially in three-dimensional geometries and when the fluid has complex behavior, e.g., viscoelasticity. On the other hand, partitioned schemes have simpler implementation and potential lower computational cost, yet have shown severe stability issues when applied to highly nonlinear free boundary flows. This research will develop novel partitioned algorithms for free boundary flows of complex fluids which will combine good stability properties with low computational costs and ease of implementation.The novel algorithms developed in the project will be used to study and understand complex flows arising in biology, medicine, and engineering. Major applications include blood flow in human arteries, the optimization of coating processes, and the flow of emulsions which naturally occur in oil extraction. Multidisciplinary training will be incorporated in the research by joint advising of two PhD students in Applied Mathematics and Chemical Engineering. The outcomes of the proposed research will impact cyberinfrastructures through scientific computing, as well as other areas of complex fluid mechanics where computing plays a central and essential role.

在工程和生物系统中，由于流动结构域的形状可能是未知的，并且由于流体可以包含或包含带有异常行为的大分子和纳米颗粒，因此流量通常涉及复杂性。 这项研究旨在开发新颖的数值算法来计算这种复杂性。由于它们的稳健性和可靠性，完全耦合（单片/隐式）方案通常用于模拟自由边界的流。但是，这些方案可能变得不切实际，尤其是在三维几何形状中，当流体具有复杂的行为时，例如粘弹性。另一方面，分区方案具有更简单的实现和潜在的计算成本，但是当应用于高度非线性的自由边界流时，显示出严重的稳定性问题。 这项研究将开发出复杂流体的自由边界流的新型分区算法，这些算法将结合良好的稳定性和低计算成本和易于实施。该项目中开发的新算法将用于研究和理解生物学，医学和工程中产生的复杂流。主要应用包括在人动脉中的血流，涂料过程的优化以及自然出现在油提取中的乳液流动。多学科培训将通过与两名应用数学和化学工程学的博士学位学生联合建议在研究中纳入研究。 拟议的研究的结果将通过科学计算以及计算具有核心和重要作用的复杂流体力学领域来影响网络基础设施。