lifex-cfd: An open-source computational fluid dynamics solver for cardiovascular applications
Computational fluid dynamics (CFD) is an important tool for the simulation of the
cardiovascular function and dysfunction. Due to the complexity of the anatomy, the …
cardiovascular function and dysfunction. Due to the complexity of the anatomy, the …
lifex-ep: a robust and efficient software for cardiac electrophysiology simulations
Background Simulating the cardiac function requires the numerical solution of multi-physics
and multi-scale mathematical models. This underscores the need for streamlined, accurate …
and multi-scale mathematical models. This underscores the need for streamlined, accurate …
Fast and robust parameter estimation with uncertainty quantification for the cardiac function
Background and objectives Parameter estimation and uncertainty quantification are crucial
in computational cardiology, as they enable the construction of digital twins that faithfully …
in computational cardiology, as they enable the construction of digital twins that faithfully …
[HTML][HTML] Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression
Uncertainty quantification (UQ) tasks, such as sensitivity analysis and parameter estimation,
entail a huge computational complexity when dealing with input-output maps involving the …
entail a huge computational complexity when dealing with input-output maps involving the …
Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations
Cardiac digital twins provide a physics and physiology informed framework to deliver
personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to …
personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to …
Branched latent neural maps
M Salvador, AL Marsden - Computer Methods in Applied Mechanics and …, 2024 - Elsevier
Abstract We introduce Branched Latent Neural Maps (BLNMs) to learn finite dimensional
input–output maps encoding complex physical processes. A BLNM is defined by a simple …
input–output maps encoding complex physical processes. A BLNM is defined by a simple …
[HTML][HTML] Proper orthogonal decomposition method of constructing a reduced-order model for solving partial differential equations with parametrized initial values
This paper proposes a novel proper orthogonal decomposition method for constructing a
reduced-order model. This model effectively computes solutions for various initial conditions …
reduced-order model. This model effectively computes solutions for various initial conditions …
Real-time whole-heart electromechanical simulations using latent neural ordinary differential equations
Cardiac digital twins provide a physics and physiology informed framework to deliver
predictive and personalized medicine. However, high-fidelity multi-scale cardiac models …
predictive and personalized medicine. However, high-fidelity multi-scale cardiac models …
A non-conforming-in-space numerical framework for realistic cardiac electrophysiological outputs
Computer-based simulations of non-invasive cardiac electrophysiological outputs, such as
electrocardiograms and body surface potential maps, usually entail severe computational …
electrocardiograms and body surface potential maps, usually entail severe computational …
Branched Latent Neural Operators
M Salvador, AL Marsden - arXiv preprint arXiv:2308.02599, 2023 - arxiv.org
We introduce Branched Latent Neural Operators (BLNOs) to learn input-output maps
encoding complex physical processes. A BLNO is defined by a simple and compact …
encoding complex physical processes. A BLNO is defined by a simple and compact …