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We present a methodology for simulating three-dimensional flow of incompressible viscoplastic fluids modelled by generalised Newtonian rheological equations. It is implemented in a highly efficient framework for massively parallelisable…

Fluid Dynamics · Physics 2019-09-17 Knut Sverdrup , Ann Almgren , Nikolaos Nikiforakis

We develop a new, efficient, and accurate method to simulate frequency-domain borehole electromagnetic (EM) measurements acquired in the presence of three-dimensional (3D) variations of the anisotropic subsurface conductivity. The method is…

This work considers a Stokes flow in a deformable fracture interacting with a linear elastic medium. To this end, we employ a phase-field model to approximate the crack dynamics. Phase-field methods belong to interface-capturing approaches…

Numerical Analysis · Mathematics 2024-04-15 Henry von Wahl , Thomas Wick

We consider the dynamics of two-phase fluids, in particular the moving contact line, on a solid substrate. The dynamics are governed by the sharp-interface model consisting of the incompressible Navier-Stokes\slash Stokes equations with the…

Computational Physics · Physics 2020-07-15 Quan Zhao , Weiqing Ren

This work outlines a new multi-physics-compatible immersed rigid body method for Eulerian finite-volume simulations. To achieve this, rigid bodies are represented as a diffuse scalar field and an interface seeding method is employed to…

Computational Physics · Physics 2022-03-15 Tim Wallis , Philip Barton , Nikolaos Nikiforakis

We demonstrate an object tracking method for 3D images with fixed computational cost and state-of-the-art performance. Previous methods predicted transformation parameters from convolutional layers. We instead propose an architecture that…

Computer Vision and Pattern Recognition · Computer Science 2021-09-28 Daniel Moyer , Esra Abaci Turk , P Ellen Grant , William M. Wells , Polina Golland

The moment-of-fluid method (MOF) is known as an extension of the volume-of-fluid method with piecewise linear interface construction (VOF-PLIC). In this study, several directional splitting advection algorithms are extended from the…

Numerical Analysis · Mathematics 2021-08-13 Zhoueng Ye

An advanced Volume of Fluid (VOF) method is presented that enables performant three-dimensional Direct Numerical Simulations (DNS) of the interaction of two immiscible fluids in a gaseous environment with large topology changes, e.g.,…

Fluid Dynamics · Physics 2023-11-08 Johanna Potyka , Kathrin Schulte

This paper presents an efficient algorithm for the sequential positioning, also called nested dissection, of two planes in an arbitrary polyhedron. Two planar interfaces are positioned such that the first plane truncates a given volume from…

Numerical Analysis · Mathematics 2023-10-10 Johannes Kromer , Johanna Potyka , Kathrin Schulte , Dieter Bothe

We present a hybrid Volume-of-Fluid (VoF) Phase-Field method for general soluble surfactant-laden interfacial flows. The scheme retains the VoF method for interface tracking and momentum solution, while a diffused Phase-Field serves as a…

Fluid Dynamics · Physics 2026-05-28 Ilies Haouche , Benjamin Reichert , Michaël Baudoin , Palas Kumar Farsoiya

Volume of fluid(VOF) method is a sharp interface method employed for simulations of two phase flows. Interface in VOF is usually represented using piecewise linear line segments in each computational grid based on the volume fraction field.…

Computational Physics · Physics 2021-02-02 Ananthan M , Gaurav Tomar

This paper solves the discretised multiphase flow equations using tools and methods from machine-learning libraries. The idea comes from the observation that convolutional layers can be used to express a discretisation as a neural network…

In this paper, we introduce a novel way to represent the interface for two-phase flows with phase change. We combine a level-set method with a Cartesian embedded boundary method and take advantage of both. This is part of an effort to…

Numerical Analysis · Mathematics 2022-12-28 A. Limare , S. Popinet , C. Josserand , Z. Xue , A. Ghigo

This paper presents a method for modelling interfacial mass transfer in Interface Capturing simulations of two-phase flow with phase change. The model enables mechanistic prediction of the local rate of phase change at the vapour-liquid…

Fluid Dynamics · Physics 2021-08-25 G. Giustini , R. I. Issa , M. J. Bluck

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Runze Yuan , Tao Liu , Zijia Dai , Yi-Fan Zuo , Laurent Kneip

Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on the observation that…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Longfei Han , Klaus Kefferpütz , Jürgen Beyerer

Interactions between an evolving solid and inviscid flow can result in substantial computational complexity, particularly in circumstances involving varied boundary conditions between the solid and fluid phases. Examples of such…

Fluid Dynamics · Physics 2022-09-30 Emma M. Schmidt , J. Matt Quinlan , Brandon Runnels

We present a method to simulate fluid flow on evolving surfaces, e.g., an oil film on a water surface. Given an animated surface (e.g., extracted from a particle-based fluid simulation) in three-dimensional space, we add a second simulation…

Graphics · Computer Science 2020-10-08 Dieter Morgenroth , Stefan Reinhardt , Daniel Weiskopf , Bernhard Eberhardt

Immersed methods discretize boundary conditions for complex geometries on background Cartesian grids. This makes such methods especially suitable for two-way coupled flow-body problems, where the body mechanics are partially driven by…

Fluid Dynamics · Physics 2025-04-01 Xinjie Ji , James Gabbard , Wim M. van Rees

Representation learning has overcome the often arduous and manual featurization of networks through (unsupervised) feature learning as it results in embeddings that can apply to a variety of downstream learning tasks. The focus of…

Machine Learning · Computer Science 2021-01-01 Piotr Bielak , Tomasz Kajdanowicz , Nitesh V. Chawla