5 papers
Data assimilation of flow MRI data into RANS models with algebraic closures
C. Namuroy, M. P. Juniper, P. Nair +4
We adopt the Bayesian inference framework to solve an inverse Reynolds-Averaged Navier-Stokes (RANS) problem for the approximate posterior probability distribution of the turbulenc…
Accelerated Patient-Specific Hemodynamic Simulations with Hybrid Physics-Based Neural Surrogates
Natalia L. Rubio, Eric F. Darve, Alison L. Marsden
Physics-based 0D reduced-order models provide computationally lightweight predictions of cardiovascular flows, resolving bulk hemodynamics in fractions of a second that would take…
FalconBC: Flow matching for Amortized inference of Latent-CONditioned physiologic Boundary Conditions
Chloe H. Choi, Alison L. Marsden, Daniele E. Schiavazzi
Boundary condition tuning is a fundamental step in patient-specific cardiovascular modeling. Despite an increase in offline training cost, recent methods in data-driven variational…
On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiological boundary conditions
Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi +1
Solving inverse problems in cardiovascular modeling is particularly challenging due to the high computational cost of running high-fidelity simulations. In this work, we focus on B…
Optimal patient allocation for echocardiographic assessments
Bozhi Sun, Seda Tierney, Jeffrey A. Feinstein +3
Scheduling echocardiographic exams in a hospital presents significant challenges due to non-deterministic factors (e.g., patient no-shows, patient arrival times, diverse exam durat…