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In this contribution we present the first formulation of a heterogeneous multiscale method for an incompressible immiscible two-phase flow system with degenerate permeabilities. The method is in a general formulation which includes…

Numerical Analysis · Mathematics 2014-11-24 Patrick Henning , Mario Ohlberger , Ben Schweizer

Two-phase flow of two Newtonian incompressible viscous fluids with a soluble surfactant and different densities of the fluids can be modeled within the diffuse interface approach. We consider a Navier-Stokes/Cahn-Hilliard type system…

Analysis of PDEs · Mathematics 2017-10-10 Helmut Abels , Harald Garcke , Josef Weber

The present study presents a simple but effective method for 3D visualization of the two-phase flow in the micro-tube. An isosceles right-angle prism combined with a mirror located 45^o bevel to the prism is employed to obtain synchronously…

Fluid Dynamics · Physics 2009-07-12 X. Fu , P. Zhang , H. Hu , C. J. Huang , Y. Huang , R. Z. Wang

Microfluidic devices manufactured from soft polymeric materials have emerged as a paradigm for cheap, disposable and easy-to-prototype fluidic platforms for integrating chemical and biological assays and analyses. The interplay between the…

Soft Condensed Matter · Physics 2021-11-25 Ivan C. Christov

Convection-driven porous media flows are common in industrial processes and in nature. The multiscale and multiphase character of these systems and the inherent non-linear flow dynamics make convection in porous media a complex phenomenon.…

Fluid Dynamics · Physics 2024-08-02 Marco De Paoli

We investigate quasi-two-dimensional relaxation, by surface tension, of a long straight stripe of inviscid fluid trapped inside a viscous fluid in a Hele-Shaw cell. Combining analytical and numerical solutions, we describe the emergence of…

Fluid Dynamics · Physics 2009-11-11 Arkady Vilenkin , Baruch Meerson , Pavel V. Sasorov

Significant progress has been made for estimating optical flow using deep neural networks. Advanced deep models achieve accurate flow estimation often with a considerable computation complexity and time-consuming training processes. In this…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Lingtong Kong , Jie Yang

In this work, we used a coupled level set and volume of fluid (CLSVOF) computational method for studying the generation of microdroplets in a two dimensional circular co-flow microfluidic device. The fundamental understanding of shear…

Fluid Dynamics · Physics 2025-07-17 Manohar Jammula , Somasekhara Goud Sontti

In this paper, the interaction between two immiscible fluids with a finite mobility ratio is investigated numerically within a Hele-Shaw cell. Fingering instabilities initiated at the interface between a low viscosity fluid and a high…

Fluid Dynamics · Physics 2021-04-01 S. J. Jackson , D. Stevens , H. Power , D. Giddings

The structural properties of single component fluids of hard hyperspheres in odd space dimensionalities $d$ are studied with an analytical approximation method that generalizes the Rational Function Approximation earlier introduced in the…

Statistical Mechanics · Physics 2011-11-10 Rene D. Rohrmann , Andres Santos

The influence of rough surfaces on fluid flow is characterized by the downward shift in the logarithmic layer of velocity and temperature profiles, namely the velocity roughness function $\Delta U^+$ and the corresponding temperature…

Fluid Dynamics · Physics 2025-02-20 Simon Dalpke , Jiasheng Yang , Pourya Forooghi , Bettina Frohnapfel , Alexander Stroh

Finding meaningful distances between high-dimensional data samples is an important scientific task. To this end, we propose a new tree-Wasserstein distance (TWD) for high-dimensional data with two key aspects. First, our TWD is specifically…

Machine Learning · Computer Science 2025-02-25 Ya-Wei Eileen Lin , Ronald R. Coifman , Gal Mishne , Ronen Talmon

We present the results of the first application in the naval architecture field of a methodology based on active subspaces properties for parameters space reduction. The physical problem considered is the one of the simulation of the…

Numerical Analysis · Mathematics 2018-10-12 Marco Tezzele , Filippo Salmoiraghi , Andrea Mola , Gianluigi Rozza

A data-driven algorithm is proposed that employs sparse data from velocity and/or scalar sensors to forecast the future evolution of three dimensional turbulent flows. The algorithm combines time-delayed embedding together with Koopman…

Fluid Dynamics · Physics 2026-03-04 George Papadakis , Shengqi Lu

The current resurgence in the phase diagram study beyond the critical point has questioned the conventional belief of supercritical fluid as a single phase with varying properties. On the same line, a novel two-phase approach has been…

Fluid Dynamics · Physics 2021-05-14 Piyush Mani Tripathi , Saptarshi Basu

Wedge-shaped geometries in low-Reynolds-number flows are of increasing importance, for instance, in the design of microfluidic devices. The corresponding Green's functions describing the induced flow in response to a locally applied force…

In the last decade, progresses in additive manufacturing (AM) have paved the way for optimized heat exchangers, whose disruptive design will depend on predictive numerical simulations. Typical AM rough surfaces show limited resemblance to…

Fluid Dynamics · Physics 2023-05-10 Himani Garg , Lei Wang , Guillaume Sahut , Christer Fureby

Motivated by the desire to understand complex transient behaviour in fluid flows, we study the dynamics of an air bubble driven by the steady motion of a suspending viscous fluid within a Hele-Shaw channel with a centred depth perturbation.…

Multiphase flows are commonly found in chemical engineering processes such as distillation columns, bubble columns, fluidized beds and heat exchangers. The physical boundaries of domains in numerical simulations of multiphase flows are…

Fluid Dynamics · Physics 2023-04-21 Tanyakarn Treeratanaphitak , Nasser Mohieddin Abukhdeir

Computational fluid dynamics (CFD) provides high-fidelity simulations of fluid flows but remains computationally expensive for many-query applications. In recent years deep learning (DL) has been used to construct data-driven fluid-dynamic…

Machine Learning · Computer Science 2026-04-13 David Ramos , Lucas Lacasa , Fermín Gutiérrez , Eusebio Valero , Gonzalo Rubio