Distributed and reduced computational models for cardiac fluid-solid interaction

 
Speaker:
Marc Hirschvogel
Affiliation:
MOX, Dipartimento di Matematica, Politecnico di Milano
When:
Thursday 22nd February 2024
Time:
15:00:00
Where:
Aula Saleri
Abstract:
The ongoing prevalence of cardiovascular disease entities as the number one cause of mortality in the industrialized world drives the development of novel in-silico tools for assessment of cardiac function and disease characterization. Given the complexity and multiscale nature of biophysical processes involved, efficient physics-based simulations of the cardiovascular system remain challenging, which promotes the need for intelligent model designs blending between reduced and distributed representations. Concepts of modeling multi-physics phenomena in cardiac mechanics are presented, encompassing the fusion of distributed (3D) and reduced (0D) models of the heart and the circulatory system along with efficient model personalization. These allow to quantify ventricular growth & remodeling as well as function of novel cardiac assist devices for heart failure patients. Further, blood flow-centered reduced models for cardiac fluid-solid interaction (FSI) are presented, where an efficient physics- and projection-based reduced-order model (ROM) approach allows realistic hemodynamics assessment of patient-specific left ventricular FSI without the need for a structural representation of the myocardium. Last, monolithic solvers and block preconditioning strategies are introduced that are tailored towards the solution of combined distributed and reduced models. An efficient monolithic 3D-0D coupling framework for linking fluid and solid mechanics to arbitrary reduced system models is exemplified, along with POD-based ROMs that operate on subsets of the discretization.This allows for a flexible design of cardiovascular mechanics models, providing efficient solution algorithms also for large-scale problems on patient-specific geometries. Contatti: francesco.regazzoni@polimi.it luca.dede@polimi.it
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