CAREER: Towards Harnessing the Motility of Microorganisms: Fast Algorithms, Data-Driven Models, and 3D Interactive Visual Computing

职业：利用微生物的运动性：快速算法、数据驱动模型和 3D 交互式视觉计算

• 批准号: 2408964
• 负责人: Minghao Rostami
• 金额: $ 50万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-15 至 2027-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2408964&HistoricalAwards=false
• 关键词: CAREER; Towards; Harnessing; Motility; Microorganisms

Due to their small size, microorganisms perceive a fluid as much “stickier” than do fish or humans. Such small creatures must adopt a different strategy for efficient swimming. Many of them propel themselves in the fluid by wiggling micro-structures such as cilia and flagella. The remarkable efficiency of microorganisms at moving and navigating through a surrounding fluid has inspired recent construction of microfluidic devices for mixing and transport, and micro-machines for drug delivery and manipulation of cells. Since theoretical analyses and experimentation are challenging in this setting, mathematical modeling and numerical simulation have become indispensable in these developments. This project aims to create improved computational and visualization tools for advancing understanding of the motility of microorganisms and our capability to harness this process. The project will develop an interactive three-dimensional visual computing system to serve as (1) a research tool for studying the hydrodynamics of swimming microorganisms, (2) an engineering tool for testing and improving the design of artificial, bio-inspired micro-swimmers, and (3) an educational tool for introducing students of all levels to this field. The project will also provide direct training and research opportunities for undergraduate and graduate students, postdoctoral researchers, and high school teachers. The project includes plans to develop virtual reality games based on microswimmers to be exhibited at the Museum of Science & Technology as well as public libraries. Research objectives in this project include the development of an efficient, multigrid-like method for manipulating the large, dense matrices arising from the simulation of interacting micro-swimmers, a data-driven, reduced order model for tracking fluid particles, an efficient numerical method for optimizing the design of bio-inspired swimmers given a task, and a three-dimensional interactive visual computing system for real-time fluid visualization and manipulation. Multigrid methods exploit the geometry of the swimmers and are therefore expected to be more efficient than current numerical approaches. An artificial neural network will be leveraged as a data-driven, reduced order model for the change in a fluid particle’s position. This approach is intended to simulate a fluid particle's trajectory very efficiently, since it does not require calculating fluid-structure interactions, an important aspect in real-time and/or multi-query scenarios. The planned numerical optimization method takes advantage of both the reliability of a genetic algorithm at finding global optima and the efficiency of a gradient-based method when a good initial guess is given. The interactive visual computing system is intended to serve as a virtual laboratory for analysis of the effects of parameter changes. This project is jointly funded by the Computational Mathematics and the Mathematical Biology Programs of the Division of Mathematical Science.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.

由于它们的体积小，微生物比鱼或人类更“粘性”地感知流体。这些小生物必须采取不同的策略来进行有效的游泳。它们中的许多通过摆动纤毛和鞭毛等微结构在流体中推进自己。微生物在周围流体中移动和导航的显著效率激发了最近用于混合和运输的微流体装置以及用于药物递送和细胞操纵的微机器的构造。由于理论分析和实验是具有挑战性的，在这种情况下，数学建模和数值模拟已成为不可或缺的这些发展。该项目旨在创建改进的计算和可视化工具，以促进对微生物运动的理解以及我们利用这一过程的能力。该项目将开发一个交互式三维视觉计算系统，作为（1）研究游泳微生物流体动力学的研究工具，（2）测试和改进人造生物启发微型游泳者设计的工程工具，以及（3）向各级学生介绍这一领域的教育工具。该项目还将为本科生和研究生、博士后研究人员和高中教师提供直接培训和研究机会。该项目包括开发基于微型游泳者的虚拟现实游戏的计划，这些游戏将在科学技术博物馆和公共图书馆展出。该项目的研究目标包括开发一种有效的、类似多重网格的方法，用于操纵来自相互作用的微型游泳者的模拟的大的、密集的矩阵，一种数据驱动的、用于跟踪流体粒子的降阶模型，一种有效的数值方法，用于优化给定任务的生物启发游泳者的设计，以及用于实时流体可视化和操纵的三维交互式可视化计算系统。多重网格方法利用游泳者的几何形状，因此预计将比目前的数值方法更有效。将利用人工神经网络作为流体颗粒位置变化的数据驱动的降阶模型。这种方法旨在非常有效地模拟流体粒子的轨迹，因为它不需要计算流体-结构相互作用，这是实时和/或多查询场景中的一个重要方面。计划的数值优化方法利用了遗传算法在寻找全局最优解时的可靠性和基于梯度的方法在给定良好初始猜测时的效率。交互式视觉计算系统的目的是作为一个虚拟实验室的参数变化的影响进行分析。该项目由数学科学部的计算数学和数学生物学项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。