Next Generation Computational Tools for Particle-laden Biological Flows in Subject-specific Geometries

Fluid mechanics plays a crucial role in many physiological processes on health and disease. Given recent advances in medical imaging, computational power, and mathematical algorithms, real-time patient-specific computational fluid dynamics is now becoming possible. Yet, many problems involve complex interactions between fluid and biological particles in which existing models are either too expensive to simulate at full scale or unable to properly capture important hydrodynamics taking place at the smallest scales. This project will develop a versatile and massively parallel framework to bridge this gap. The numerical framework will be designed to simulate a large number of particles within the human body. This will help better understand cardiovascular diseases, from stroke, to rigid calcite particles in the ear canal responsible for vertigo.

Example of an image-based geometric model of a human aorta, discretized using an unstructured linear tetrahedral mesh.

Fluid mechanics plays a crucial role in many physiological processes on health and disease. Given recent advances in medical imaging, computational power, and mathematical algorithms, real-time patient-specific computational fluid dynamics is now becoming possible. Yet, many problems involve complex interactions between fluid and biological particles in which existing models are either too expensive to simulate at full scale or unable to properly capture important hydrodynamics taking place at the smallest scales. This project will develop a versatile and massively parallel framework to bridge this gap. The numerical framework will be designed to simulate a large number of particles within the human body, from deformable red blood cells within arteries to better understand stroke, to rigid calcite particles in the ear canal responsible for vertigo.

U-M Researchers

Jesse Capecelatro