Collaborative Research: Optimal-Complexity Spectral Methods for Complex Fluids

合作研究：复杂流体的最优复杂谱方法

基本信息

批准号：
1952757
负责人：
Alex Townsend
金额：
$ 12万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2023-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952757&HistoricalAwards=false
关键词：
Collaborative Research Optimal Complexity Spectral

项目摘要

Complex fluids, such as microbial suspensions in biology or quantum fluids in physics, exhibit a wealth of intriguing phenomena, ranging from spontaneous transport and non-equilibrium pattern formation to the emergence of superfluid and superconductive currents. Computational techniques for simulating and predicting the dynamics of these fluids in realistic 3D configurations found in laboratories are not keeping pace with the recent breakthroughs in experimental design and mathematical modeling. The Principal Investigators (PIs) will develop a collection of computational advancements that are urgently needed to validate current mathematical models and explore relevant parameter regimes to guide current and next-generation experiments. These efforts will pave the way for a better understanding of biological and physical transport phenomena, promising improved designs of micro-fluidic and quantum-fluidic devices. The project also provides research training opportunities for graduate students. The PIs will be developing highly efficient numerical methods based on a hybrid of Fourier/ultraspherical spectral methods that are ideally suited for accurately and robustly treating the high-order derivatives that appear in the complex fluid models. This computational framework will enable the fast simulation of non-equilibrium fluid flows through scientifically relevant geometries composed of cylinders, spheres, and ellipsoids. The algorithms will be parallelizable for efficient simulation on next-generation hardware accelerators. Working with two experimental collaborators, the PIs will investigate chaotic mixing, transport properties, and topological nature of geometrically confined non-Newtonian fluids.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

复杂的液体，例如生物学中的微生物悬浮液或物理学中的量子流体，表现出丰富的有趣现象，从自发运输和非平衡模式形成到超氟和超导电流的出现。在实验室中发现的现实3D配置中这些流体的动力学的计算技术并没有与实验设计和数学建模的最新突破保持同步。主要研究人员（PIS）将开发一系列计算进步的集合，这些进步迫切需要验证当前数学模型并探索相关参数制度以指导当前和下一代实验。这些努力将为更好地理解生物和物理运输现象铺平道路，并有望改进微富集和量子富丽体设备的设计。该项目还为研究生提供了研究培训机会。 PI将基于傅立叶/超球光谱方法的混合体开发高效的数值方法，这些方法非常适合准确，可靠地处理复杂流体模型中出现的高阶衍生物。该计算框架将使非平衡流体通过由圆柱，球体和椭圆形组成的科学相关几何形状进行快速模拟。该算法将是可行的，以便在下一代硬件加速器上有效仿真。 PIS与两个实验合作者合作，将研究几何限制的非牛顿流体的混乱混合，运输特性以及拓扑性质。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得支持的。