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Physics-driven CFD modeling of complex anatomical cardiovascular flows-a TCPC case study.
Kerem Pekkan1, Diane de Zélicourt, Liang Ge
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Annals of Biomedical Engineering
|May 5, 2005
Summary
Advanced computational fluid dynamics (CFD) models are crucial for patient-specific surgical planning. This study developed an in-house CFD solver that accurately predicts complex blood flow in total cavopulmonary connections (TCPC), outperforming commercial software.
Area of Science:
- Biomedical Engineering
- Fluid Dynamics
- Medical Imaging
Background:
- Computational fluid dynamics (CFD) offers potential for patient-specific surgical planning.
- Accurate CFD requires physics-driven numerical modeling, especially for complex cardiovascular flows.
Purpose of the Study:
- To develop and validate an advanced CFD simulation tool for predicting flow in patient-specific total cavopulmonary connections (TCPC).
- To compare the performance of a novel in-house CFD solver against commercial software and experimental data.
Main Methods:
- Reconstruction of an anatomically correct intra-atrial TCPC model from MRI data.
- Experimental assessment using transparent rapid prototyping, flow visualization, and particle image velocimetry (PIV).
- Numerical simulations using a commercial CFD software and a newly developed second-order accurate in-house solver.
Main Results:
- Commercial CFD captured global flow quantities but missed complex, unsteady 3D flow structures observed experimentally.
- The in-house solver successfully predicted these complex flow features, showing good agreement with PIV measurements.
- Hydrodynamic power loss increased significantly with cardiac output, indicating high energy demand during exercise.
Conclusions:
- A physics-based, integrated approach combining high-resolution CFD and experimental measurements is essential for accurate cardiovascular flow simulation.
- The developed in-house CFD solver demonstrates superior capability in capturing intricate flow dynamics within TCPC models.
- Findings highlight the significant energy demands of cardiovascular flow under varying conditions, relevant for surgical planning and understanding physiological states.