Complex and active fluids find broad applications in flows through porous materials.
Nontrivial rheology can couple to porous microstructure leading to surprising flow patterns …

Abstract Generalised Newtonian Fluid (GNF) models which assume that the viscosity of a
non-Newtonian fluid can be modelled inelastically as a time-independent, ie instantaneous …

Active processes drive biological dynamics across various scales and include subcellular
cytoskeletal remodelling, tissue development in embryogenesis and the population-level …

Data-driven turbulence modeling is receiving considerable attention specially when Direct
Numerical Simulations (DNS) are the physics-informed learning environment and Reynolds …

Time-dependent yield stress materials abound in nature and in industrial processes.
Examples include clays, light metal alloys, paints and inks, adhesives, gelled waxy crude …

Creating an entry vortex growth simulation to show viscous and elastic fluid behaviors has
always been a major challenge for the computational rheology of well-characterized …

Vesicles are hollow aggregates, composed of bilayers of amphiphilic molecules, dispersed
into and filled with a liquid solvent. These aggregates can be formed either as equilibrium or …

A new streamfunction/log-conformation formulation of incompressible viscoelastic flows is
presented. The log-conformation representation guaranties the positive-definiteness of the …

By considering the rotationality of shear flow, we distinguish between tube segments created
by reptation before the inception of shear flow and those created during flow. Tube …

We develop a data-driven machine learning (ML) turbulence model and conduct a
comparative study with representative approaches employed in the literature. The new …