RUI: Algorithms and Modeling for Chemotactic Deformable Particles in Non-Newtonian, Multiphase, Non-Isothermal, Turbulent Flows

该项目涉及流体-结构相互作用领域的计算流体动力学。该研究的目标是开发一种新的多尺度计算效率和鲁棒性的数值模型，以模拟粒子在其环境中响应化学刺激而移动。这项工作的目的是创造新的理解，这种颗粒与散装流体的流体动力学相互作用，这不同于非趋化性颗粒的颗粒-流体流体动力学，其运动性仅由散装流体流动驱动。该项目将招募一批有才华的本科生，并鼓励他们攻读研究生课程，重点是在一个完善的跨学科环境中挑战性的研究问题。该项目将向学生介绍流体动力学计算和数学研究的智力兴奋，从而鼓励他们创造性地和独立地思考潜在的应用，并提高他们对研究生院的途径和工业就业中的研究和开发机会的认识。本项目探索了一种新的多尺度计算效率和鲁棒性数值模型，以模拟两个和三个-复杂流体中可变形趋化颗粒的空间运动性。这解决了在流体中的颗粒运动的数学和计算处理中出现的两个基本问题：（i）响应于空间和时间变化的化学引诱物梯度的可变形趋化颗粒的自自主运动，以及（ii）非牛顿流体和层流到湍流流态中的多相流中的颗粒流体动力学。多尺度模型使用RapidCell模型、正则化Stokeslet方法和浸没边界方法将细胞内信号传导途径与颗粒-流体相互作用耦合。这非常适合复杂的应用，包括例如促进生物膜形成的细菌趋化性和群机器人气味定位。该项目包括开发一种新颖的多尺度计算流体动力学软件包，适用于理论分析和各种多学科应用。它将作为一个高度翔实的教学工具，研究生和本科水平的类。

This project concerns computational fluid dynamics in the field of fluid-structure interactions. The goal of the research is to develop a new multi-scale computationally-efficient and robust numerical model to simulate particles that move in response to chemical stimuli in their environment. The work aims to create new understanding of the hydrodynamic interactions of such particles with the bulk fluid, which differs from particle-fluid hydrodynamics for non-chemotactic particles, whose motility is driven solely by the bulk fluid flow. The project will recruit a diverse group of talented undergraduate students and encourage them to pursue graduate studies, focusing on challenging research problems in a well-established interdisciplinary environment. The project will introduce students to the intellectual excitement of computational and mathematical research in fluid dynamics, thereby encouraging them to think creatively and independently about potential applications and increasing their awareness of pathways to graduate schools and opportunities in research and development in industry employment.This project explores a new multi-scale computationally-efficient and robust numerical model to simulate two- and three-dimensional motility of deformable chemotactic particles in complex fluids. This addresses two fundamental issues that arise in the mathematical and computational treatment of particle motility in fluids: (i) self-autonomous motion of deformable chemotactic particles in response to spatially- and temporally-varying chemoattractant gradients, and (ii) particle-fluid hydrodynamics in non-Newtonian fluids and multiphase flows in laminar to turbulent flow regimes. The multi-scale model couples intracellular signaling pathways with particle-fluid interactions using the RapidCell model, the method of Regularized Stokeslets, and the Immersed Boundary method. This is well-suited for sophisticated applications, including, for example, bacterial chemotaxis promoting biofilm formation and swarm robotic odor localization. The project includes development of a novel, multi-scale computational fluid dynamics package suitable for theoretical analyses and diverse multi-disciplinary applications. It will serve as a highly informative teaching tool for graduate and undergraduate level classes.