activity
20202024
most citedViscoelasticNet: A physics informed neural network framework for stress discovery and model selection

35 citations · 94 across the 8 of their papers we have counts for

collaborators

9 papers

cs.NE2024★ 1 cited

Physics-Informed Neural Network based inverse framework for time-fractional differential equations for rheology

Sukirt Thakur, Harsa Mitra, Arezoo M. Ardekani

Time-fractional differential equations offer a robust framework for capturing intricate phenomena characterized by memory effects, particularly in fields like biotransport and rheo…

physics.flu-dyn2023

Stress and stretching regulate dispersion in viscoelastic porous media flows

Manish Kumar, Derek M. Walkama, Arezoo M. Ardekani +1

In this work, we study the role of viscoelastic instability in the mechanical dispersion of fluid flow through porous media at high Peclet numbers. Using microfluidic experiments a…

physics.flu-dyn2023

Temporal Consistency Loss for Physics-Informed Neural Networks

Sukirt Thakur, Maziar Raissi, Harsa Mitra +1

Physics-informed neural networks (PINNs) have been widely used to solve partial differential equations in a forward and inverse manner using deep neural networks. However, training…

physics.flu-dyn2022

Rheology of dense fiber suspensions: Origin of yield stress, shear thinning and normal stress differences

Monsurul Khan, Rishabh V. More, Luca Brandt +1

We explain the origins of yield stress, shear-thinning, and normal stress differences in rigid fiber suspensions. We investigate the interplay between the hydrodynamic, colloidal a…

physics.flu-dyn2022★ 7 cited

A constitutive model for viscosity of dense fiber suspension

Monsurul Khan, Rishabh V. More, Arezoo M. Ardekani

We propose a constitutive model to predict the viscosity of fiber suspensions, which undergoes shear thinning, at various volume fractions, aspect ratios, and shear stresses/rates.…

physics.flu-dyn2022★ 35 cited

ViscoelasticNet: A physics informed neural network framework for stress discovery and model selection

Sukirt Thakur, Maziar Raissi, Arezoo M. Ardekani

Viscoelastic fluids are a class of fluids that exhibit both viscous and elastic nature. Modelling such fluids requires constitutive equations for the stress, and choosing the most…

physics.flu-dyn2022★ 16 cited

Lagrangian stretching reveals stress topology in viscoelastic flows

Manish Kumar, Jeffrey S. Guasto, Arezoo M. Ardekani

Viscoelastic flows are pervasive in a host of natural and industrial processes, where the emergence of nonlinear and time-dependent dynamics regulate flow resistance, energy consum…

physics.flu-dyn2021

Perspectives on viscoelastic flow instabilities and elastic turbulence

Sujit S. Datta, Arezoo M. Ardekani, Paulo E. Arratia +20

Viscoelastic fluids are a common subclass of rheologically complex materials that are encountered in diverse fields from biology to polymer processing. Often the flows of viscoelas…

cond-mat.soft2020★ 35 cited

A unifying mechanism to explain the rate dependent rheological behavior in non-Brownian suspensions: One curve to unify them all

Rishabh V. More, Arezoo M. Ardekani

We propose a unifying mechanism based on the Stribeck curve for the coefficient of friction between the particles to capture the shear thinning - Newtonian plateau - shear thickeni…