72 citations · 125 across the 5 of their papers we have counts for
5 papers
Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression
Shaghayegh Z. Ashtiani, Mohammad Sarabian, Kaveh Laksari +1
Blood flow reconstruction in the vasculature is important for many clinical applications. However, in clinical settings, the available data are often quite limited. For instance, T…
Physics-informed neural networks for improving cerebral hemodynamics predictions
Mohammad Sarabian, Hessam Babaee, Kaveh Laksari
Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases. In this work, we put forth a physics-informed deep learning…
Numerical simulations of a sphere settling in simple shear flows of yield stress fluids
Mohammad Sarabian, Marco E. Rosti, Luca Brandt +1
We perform D numerical simulations to investigate the sedimentation of a single sphere in the absence and presence of a simple cross shear flow in a yield stress fluid with weak…
Fully developed and transient concentration profiles of particulate suspensions sheared in a cylindrical Couette
Mohammad Sarabian, Mohammadhossein Firouznia, Bloen Metzger +1
We experimentally investigate particle migration in a non-Brownian suspension sheared in a Taylor-Couette configuration and in the limit of vanishing Reynolds number. Highly resolv…
Computational modeling of multiphase viscoelastic and elastoviscoplastic flows
Daulet Izbassarov, Marco E. Rosti, M. Niazi Ardekani +4
In this paper, a three-dimensional numerical solver is developed for suspensions of rigid and soft particles and droplets in viscoelastic and elastoviscoplastic (EVP) fluids. The p…