Efficient multi-fidelity computation of blood coagulation under flow.

Area of Science:

• Biophysics
• Computational Biology
• Biochemical Engineering

Background:

• Blood clot formation is vital but complex, regulated by the coagulation cascade.
• Simulating this cascade involves computationally intensive partial differential equations (PDEs).
• Existing models struggle with the large size and multi-scale nature of these systems.

Approach:

• A multi-fidelity strategy transforms PDEs into ordinary differential equations (ODEs) based on blood residence time.
• Taylor expansion around the zero-diffusivity limit approximates species concentrations using statistical moments.
• This reduces a system of N PDEs to N ODEs and p PDEs for statistical moments.

Key Points:

• The multi-fidelity approach offers a speedup of over N/p compared to high-fidelity models.
• Low-order models (p=1, p=2) show favorable accuracy, with errors under 16% and 5% respectively.
• This method balances computational cost and accuracy for complex simulations.

Conclusions:

• The multi-fidelity models enable efficient and accurate simulations of coagulation cascades.
• This approach can be applied to analyze coagulation in complex flow scenarios and large reaction networks.
• The methodology is generalizable to other blood flow-affected systems biology networks.