This paper explores the recent advancements in enhancing Computational Fluid Dynamics
(CFD) tasks through Machine Learning (ML) techniques. We begin by introducing …

Learning the long-range interactions on large-scale mesh-based physical systems with flat
Graph Neural Networks (GNNs) and stacking Message Passings (MPs) is challenging due …

The wide applications of plug flows in microscale in science and engineering help them
attract a great deal recent interest. An analytical study is undertaken here to study the …

Learning complex physical dynamics purely from data is challenging due to the intrinsic
properties of systems to be satisfied. Incorporating physics-informed priors, such as in …

Time-independent Partial Differential Equations (PDEs) on large meshes pose significant
challenges for data-driven neural PDE solvers. We introduce a novel graph rewiring …

In this study, new experimental data for the displacement of a Newtonian liquid by three pure
viscoelastic (Boger) fluids with different relaxation times were obtained with imaging in a 500 …

An experiment was carried out on a bayonet tube that was kept at a constant temperature
using condensing steam. In contrast, cold water was permitted to enter the central tube and …

Different from a fully developed continuous flow in an annular pipe, a liquid plug moving in
an annular pipe generates two toroidal vortexes, which cause radial transport that enhances …

Many scientific problems require a deep understanding of internal structures and complex
dynamics, spanning physical interactions within molecules, brain networks, and beyond …

Для всех жидкостей характерно изменение вязкости в зависимости от температуры. В
большинстве случаев данной зависимостью принято пренебрегать, однако при …