An ensemble solver for segregated cardiovascular FSI

TL;DR

This paper introduces an efficient ensemble solver for cardiovascular fluid-structure interaction that improves computational performance over traditional methods, enabling better uncertainty quantification in cardiovascular modeling.

Contribution

It presents a novel explicit-in-time ensemble solver for segregated cardiovascular FSI, with detailed numerics and implementation on CPU and GPU systems, enhancing uncertainty analysis.

Findings

Superior performance of the ensemble solver over implicit methods.

Effective application to both idealized and patient-specific models.

Demonstrated efficiency on CPU and GPU architectures.

Abstract

Computational models are increasingly used for diagnosis and treatment of cardiovascular disease. To provide a quantitative hemodynamic understanding that can be effectively used in the clinic, it is crucial to quantify the variability in the outputs from these models due to multiple sources of uncertainty. To quantify this variability, the analyst invariably needs to generate a large collection of high-fidelity model solutions, typically requiring a substantial computational effort. In this paper, we show how an explicit-in-time ensemble cardiovascular solver offers superior performance with respect to the embarrassingly parallel solution with implicit-in-time algorithms, typical of an inner-outer loop paradigm for non-intrusive uncertainty propagation. We discuss in detail the numerics and efficient distributed implementation of a segregated FSI cardiovascular solver on both CPU and GPU systems, and demonstrate its applicability to idealized and patient-specific cardiovascular models, analyzed under steady and pulsatile flow conditions.