You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on Dec 16, 2023. It is now read-only.
Currently we can only model open-loop models, i.e. models that terminate with prescribed distal boundary conditions (like a distal pressure). I am adding the following:
A heart/pulmonary circulation block that will connect outlet BCs back to the inlet of the model in a closed-loop fashion. Ref [1] for details.
Blocks to model coronary and RCR BCs that do not have a prescribed distal pressure, and can be connected either to the heart/pulmonary circulation on the distal side (closed-loop) or to a prescribed pressure block (open-loop).
Other functions to incorporate these blocks, perform usual book-keeping, etc.
There is no simple analytical test case for this. So I will add a test case to compare this with existing solvers used in previous papers [2]-[3].
Any suggestions on better/different tests?
Refs:
[1] Sankaran, S. et al. (2012).Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery. Annals of Biomedical Engineering, 40(10), 2228–2242.
[2] Tran, J. S., et al. (2017). Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations. Computers and Fluids, 142, 128–138.
[3] Tran, J. S., et al. (2019). Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts. Computer Methods in Applied Mechanics and Engineering, 345, 402–428.
Currently we can only model open-loop models, i.e. models that terminate with prescribed distal boundary conditions (like a distal pressure). I am adding the following:
Any suggestions on better/different tests?
Refs:
[1] Sankaran, S. et al. (2012).Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery. Annals of Biomedical Engineering, 40(10), 2228–2242.
[2] Tran, J. S., et al. (2017). Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations. Computers and Fluids, 142, 128–138.
[3] Tran, J. S., et al. (2019). Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts. Computer Methods in Applied Mechanics and Engineering, 345, 402–428.