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An improved numerical solver for the unified solution of compressible and incompressible fluids involving interfaces is proposed. The present method is based on the CIP-CUP (Cubic Interpolated Propagation / Combined, Unified Procedure)…

Computational Physics · Physics 2007-05-23 Masato Ida

Implicit neural representations have emerged as a powerful approach for encoding complex geometries as continuous functions. These implicit models are widely used in computer vision and 3D content creation, but their integration into…

The relationship between the spatiotemporal distribution of oxygen transport and blood flow dynamics, accounting for the motion and deformation of individual red blood cells (RBCs), is of fundamental importance for understanding…

Fluid Dynamics · Physics 2026-04-29 Naoki Takeishi , Junya Kobayashi , Shigeo Wada , Satoshi Ii

We present a partitioned Model Order Reduction method for multiphysics problems, that is based on a semi-implicit treatment of the coupling conditions, and on a projection scheme. The proposed Reduced Order Method is based on the Proper…

Numerical Analysis · Mathematics 2023-08-08 Monica Nonino , Francesco Ballarin , Gianluigi Rozza , Yvon Maday

A new method for interface tracking is presented. The interface representation, based on domain decomposition, provides the interface location explicitly, yet is Eulerian. This allows for well established finite difference methods on…

Fluid Dynamics · Physics 2013-02-20 Dag Lindbo , Anna-Karin Tornberg

The numerical simulation of fluid flow through a complex geometry with heat transfer is of strong interest for many applications, such as oil-filled power transformers. A fundamental challenge here is that high resolution is necessary to…

Computational Physics · Physics 2020-10-19 Ole H. H. Meyer , Karl Yngve Lervåg , Åsmund Ervik

A comprehensive scheme for the spatial discretisation of continuity equation, momentum advection and normal and shear stresses at the fluid interfaces is presented for numerically simulating the incompressible two phase flows based on the…

Fluid Dynamics · Physics 2014-08-11 Jun-De Li

We introduce differentiable indirection -- a novel learned primitive that employs differentiable multi-scale lookup tables as an effective substitute for traditional compute and data operations across the graphics pipeline. We demonstrate…

Graphics · Computer Science 2023-11-21 Sayantan Datta , Carl Marshall , Derek Nowrouzezahrai , Zhao Dong , Zhengqin Li

We present a loosely coupled approach for the solution of fluid-structure interaction problems between a compressible flow and a deformable structure. The method is based on staggered Dirichlet-Neumann partitioning. The interface motion in…

We study the convergence of the new family of mimetic finite difference schemes for linear diffusion problems recently proposed in [38]. In contrast to the conventional approach, the diffusion coefficient enters both the primary mimetic…

Numerical Analysis · Mathematics 2016-12-07 G. Manzini , K. Lipnikov , J. D. Moulton , M. Shashkov

We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of…

Fluid Dynamics · Physics 2016-11-29 Johan Roenby , Henrik Bredmose , Hrvoje Jasak

Simulation of fluid flow in porous media has many applications, from the micro-scale (cell membranes, filters, rocks) to macro-scale (groundwater, hydrocarbon reservoirs, and geothermal) and beyond. Direct simulation of flow in porous media…

Fluid Dynamics · Physics 2020-04-27 Ying Da Wang , Traiwit Chung , Ryan T. Armstrong , Peyman Mostaghimi

We develop a novel `moving capacitor' dynamic network model to simulate immiscible fluid-fluid displacement in porous media. Traditional network models approximate the pore geometry as a network of fixed resistors, directly analogous to an…

The numerical simulation of large-scale multiphase flow in porous media is of considerable importance across various application fields, particularly in the petroleum industry. The fully implicit method is preferred in reservoir simulations…

Numerical Analysis · Mathematics 2026-04-13 Shizhe Li , Li Zhao , Chen-Song Zhang

Specific molecular interactions underlie unexpected and useful phenomena in nanofluidic systems, but require descriptions that go beyond traditional macroscopic hydrodynamics. In this letter, we demonstrate how equilibrium molecular…

Mesoscale and Nanoscale Physics · Physics 2023-06-07 Phillip Helms , Anthony R. Poggioli , David T. Limmer

In this paper, a novel meshless method that can handle porous flow problems with singular source terms is developed by virtually constructing the node control domains. By defining the connectable node cloud, this novel meshless method uses…

Numerical Analysis · Mathematics 2022-08-03 Xiang Rao

In this paper, a pore-scale network modeling method, based on the flow continuity residual in conjunction with a Newton-Raphson non-linear iterative solving technique, is proposed and used to obtain the pressure and flow fields in a network…

Fluid Dynamics · Physics 2014-12-02 Taha Sochi

It is well known that domain-decomposition-based multiscale mixed methods rely on interface spaces, defined on the skeleton of the decomposition, to connect the solution among the non-overlapping subdomains. Usual spaces, such as…

Numerical Analysis · Mathematics 2023-04-10 Franciane F. Rocha , Fabricio S. Sousa , Roberto F. Ausas , Felipe Pereira , Gustavo C. Buscaglia

Generalizable 3D object reconstruction from single-view RGB-D images remains a challenging task, particularly with real-world data. Current state-of-the-art methods develop Transformer-based implicit field learning, necessitating an…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Yushuang Wu , Luyue Shi , Junhao Cai , Weihao Yuan , Lingteng Qiu , Zilong Dong , Liefeng Bo , Shuguang Cui , Xiaoguang Han

The interaction of neural networks with physical equations offers a wide range of applications. We provide a method which enables a neural network to transform objects subject to given physical constraints. Therefore an U-Net architecture…

Artificial Intelligence · Computer Science 2021-03-22 Lukas Harsch , Johannes Burgbacher , Stefan Riedelbauch