On the periodicity of cardiovascular fluid dynamics simulations

TL;DR

This paper introduces an automated method to generate initial conditions for cardiovascular fluid dynamics simulations, significantly reducing the number of cardiac cycles needed for convergence and lowering computational costs.

Contribution

The authors develop an automated framework using lumped-parameter modeling to generate initial conditions, improving efficiency in reaching periodic solutions in cardiovascular simulations.

Findings

Achieved convergence within one or two cardiac cycles using the new initialization method.

Reduced computational cost compared to standard approaches.

Validated on six patient-specific models from the Vascular Model Repository.

Abstract

Three-dimensional cardiovascular fluid dynamics simulations typically require computation of several cardiac cycles before they reach a periodic solution, rendering them computationally expensive. Furthermore, there is currently no standardized method to determine whether a simulation has yet reached that periodic state. In this work, we propose use of the asymptotic error measure to quantify the difference between simulation results and their ideal periodic state using lumped-parameter modeling. We further show that initial conditions are crucial in reducing computational time and develop an automated framework to generate appropriate initial conditions from a one-dimensional model of blood flow. We demonstrate the performance of our initialization method using six patient-specific models from the Vascular Model Repository. In our examples, our initialization protocol achieves periodic convergence within one or two cardiac cycles, leading to a significant reduction in computational cost compared to standard methods. All computational tools used in this work are implemented in the open-source software platform SimVascular. Automatically generated initial conditions have the potential to significantly reduce computation time in cardiovascular fluid dynamics simulations.