The impact of fluid drops on solid substrates is a cardinal fluid dynamics phenomenon
intrinsically related to many fields. Although these impacting objects are very often non …

This research gauges the ability of deep reinforcement learning (DRL) techniques to assist
the optimization and control of fluid mechanical systems. It relies on introducing single-step …

This theoretical and numerical study focuses on the physical mechanism driving the
spreading of viscoplastic elliptical millimetric/centimetric objects after they impact a solid …

Develo** new capabilities to predict the risk of intracranial aneurysm rupture and to
improve treatment outcomes in the follow-up of endovascular repair is of tremendous …

We investigate the spreading of falling ambient-temperature Newtonian drops after their
normal impact on a quartz plate covered with a thin layer of liquid nitrogen. As a drop …

We propose in this work an adaptive variational multiscale method for two-fluid flows with
surface tension. A level set function is used to provide a precise position of the interfaces …

Numerical solution of Richards' equation remains challenging to get robust, accurate and
cost-effective results, particularly for moving sharp wetting fronts. An adaptive strategy for …

Abstract The Cahn-Hilliard Navier-Stokes (CHNS) system provides a computationally
tractable model that can be used to effectively capture interfacial dynamics in two-phase …

This research gauges the capabilities of deep reinforcement learning (DRL) techniques for
direct optimal shape design in computational fluid dynamics (CFD) systems. It uses policy …

The fast stretching of fluid filaments to form either drops or broken threads is sensitive to both
fluid rheology and surface tension and in this paper numerical tools are used to simulate the …