Session: 04-01-01 Biomedical Fluid Mechanics 1

Paper Number: 182682

182682 - Development of a Two-Way Coupled Fluid-Structure Interaction Model for Aortic Blood Flow 

Abstract: 

The study of blood flow dynamics is critical in understanding cardiovascular diseases and developing and timing effective treatments or interventions. The modeling of aortic blood flow, in particular, has been studied for decades. The aorta experiences complex hemodynamic forces which affect its function and structural integrity. The blood flow’s effects on the aorta are especially prevalent in patients with abnormal aortic material properties, such as those with connective tissue disorders or previous surgical interventions. Traditional modeling methods, often the result of limited computational power and limited complexity, of studying aortic blood flow have relied on rigid wall assumptions and one-way coupling approaches. These methods often fail to capture the full interactions between the blood flow and the aortic wall. Fluid–Structure Interaction (FSI) modeling allows simultaneous simulation of fluid and structural dynamics, providing a more complete representation of these interactions. Although FSI increases complexity, this approach can more realistically capture phenomena like aortic wall expansion, its damping effect on pressure and flow, and even interactions between the aortic wall and surrounding tissues. This paper will present the development, methodology, and preliminary results of a two-way, fully coupled FSI model of aortic blood flow, developed using Ansys LS-DYNA. The results will concentrate on two novel developments. First, development, methodology, and results will be presented for three different models of the exact same aortic geometry: (1) a rigid-wall CFD model, (2) a one-way structural model, and (3) a two-way coupled FSI model. These results will be compared to identify the sources of differences with the use of the FSI model compared to CFD and structural models. To compare these models, the results will include how long each model takes to reach steady state for the following clinically important quantities: wall-shear stress, cross-sectional velocity field, pressure field, and wall displacement.  Next, the paper will present results for a model run with several (dozens to hundreds) of cardiac cycles. Currently, any aortic FSI models have only been run with a limited number (1-5) of cardiac cycles. Without the constraining steady-state assumption and by using a transient solver, the results presented in this paper will reveal how the aortic structure and flow develops across the temporal domain. Models will also be run on at least two patient-specific aortic geometries. The long-term goal of this research is to develop a patient-specific dynamic digital twin (for both healthy patients and those with connective tissue disorders), which is capable of predicting aortic failure or timing of intervention by measuring change over thousands of cardiac cycles.

Presenting Author: Paul Burke The Johns Hopkins University Applied Physics Laboratory

Presenting Author Biography: Dr. Burke is also an engineer and computational physicist within Johns Hopkins Applied Physics Lab’s Space Exploration Sector, where he serves as an international expert in the area of multi-phase fluid dynamics in variable gravity environments. He has applied his expertise to study ocean worlds, astrobiology, human space exploration, and In-Situ Resource Utilization (ISRU). Dr. Burke’s work has utilized data from or directly supported multiple interplanetary missions, including NASA’s Europa Clipper and the European Space Agency’s Jupiter Icy Moons Explorer (JUICE). His fluid modeling has also supported projects outside of space flight, including modeling of human systems and biological flows. Dr. Burke also teaches and develops computational fluid dynamics curriculum for Johns Hopkins University’s Department of Mechanical Engineering.

Authors:

Paul Burke The Johns Hopkins University Applied Physics Laboratory
Antonio Martinez Pascual Ansys
Paige Owen Ansys
Michel Rochette Ansys
Bharath Ambale-Venkatesh Johns Hopkins School of Medicine