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Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solutions are tedious and require high computational power.…

Machine Learning · Computer Science 2024-02-21 Janny Steeven , Nadri Madiha , Digne Julie , Wolf Christian

We study segregation of an impurity in a driven granular fluid under two types of \emph{steady} states. In the first state, the granular gas is driven by a stochastic volume force field with a Fourier-type profile while in the second state,…

Soft Condensed Matter · Physics 2015-01-05 Francisco Vega Reyes , Vicente Garzó

In this review we discuss the recent progress in the simulation of soft active matter systems and in particular the hydrodynamics of microswimmers using the method of multiparticle collision dynamics, which solves the hydrodynamic flows…

Soft Condensed Matter · Physics 2020-09-03 Andreas Zöttl

We describe a method to address efficiently problems of two-phase flow in the regime of low particle Reynolds number and negligible Brownian motion. One of the phases is an incompressible continuous fluid and the other a discrete…

Condensed Matter · Physics 2016-08-31 Stefan Schwarzer

Meandering instability is familiar to everyone through river meandering or small rivulets of rain flowing down a windshield. However, its physical understanding is still premature, although it could inspire researchers in various fields,…

Soft Condensed Matter · Physics 2016-12-13 Yuki Yoshimura , Yui Yagisawa , Ko Okumura

Sediment transport over an erodible sediment bed is studied by particle resolved simulations with a hybrid parallel approach. To overcome the challenges of load imbalance in the traditional domain decomposition method when encountering…

Fluid Dynamics · Physics 2022-07-27 Zhengping Zhu , Ruifeng Hu , Yinghaonan Lei , Lian Shen , Xiaojing Zheng

A consistent and conservative Phase-Field method, including both the model and scheme, is developed for multiphase flows with an arbitrary number of immiscible and incompressible fluid phases. The consistency of mass conservation and the…

Computational Physics · Physics 2022-02-15 Ziyang Huang , Guang Lin , Arezoo M. Ardekani

Liquid may give strong cohesion properties to a granular medium, and confer a solid-like behavior. We study the erosion of a fixed circular aggregate of wet granular matter subjected to a flow of dry grains inside a half-filled rotating…

Soft Condensed Matter · Physics 2014-12-09 Gautier Lefebvre , Pierre Jop

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

We present a multi-resolution approach for constructing model-based simulations of hydraulic fracturing, wherein flow through porous media is coupled with fluid-driven fracture. The approach consists of a hybrid scheme that couples a…

Computational Engineering, Finance, and Science · Computer Science 2022-07-05 Andre Costa , Matteo Cusini , Tao Jin , Randolph Settgast , John Dolbow

The Multiparticle Collision Dynamics technique (MPC) for hydrodynamics simulations is generalized to binary fluid mixtures and multiphase flows, by coupling the particle-based fluid dynamics to a Ginzburg-Landau free-energy functional for…

Soft Condensed Matter · Physics 2024-06-03 Thomas Eisenstecken , Raphael Hornung , Roland G. Winkler , Gerhard Gompper

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

Numerical simulators are essential tools in the study of natural fluid-systems, but their performance often limits application in practice. Recent machine-learning approaches have demonstrated their ability to accelerate spatio-temporal…

Fluid Dynamics · Physics 2022-05-06 Mario Lino , Stathi Fotiadis , Anil A. Bharath , Chris Cantwell

We employ a multi-phase smoothed particle hydrodynamics (SPH) method to study droplet dynamics in shear flow. With an extensive range of Reynolds number, capillary number, wall confinement, and density/viscosity ratio between the droplet…

Fluid Dynamics · Physics 2023-07-07 Kuiliang Wang , Hong Liang , Chong Zhao , Xin Bian

A minimal Lagragian two-phase model to study turbulent bedload transport focusing on the granular phase is presented, and validated with experiments. The model intends to describe bedload transport of massive particles in fully rough flows…

Geophysics · Physics 2016-05-20 Raphael Maurin , Julien Chauchat , Bruno Chareyre , Philippe Frey

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

Modeling mass flows is classically based on hydrostatic balance equations. However, if momentum transfers scale similarly in slope parallel and flow depth directions, then the gravity and acceleration can have the same order of magnitude…

Fluid Dynamics · Physics 2022-10-12 Shiva P. Pudasaini

The Discrete Particle Method (DPM) is used to model granular flows down an inclined chute. We observe three major regimes: static piles, steady uniform flows and accelerating flows. For flows over a smooth base, other (quasi-steady) regimes…

Soft Condensed Matter · Physics 2011-08-26 Thomas Weinhart , Anthony Thornton , Stefan Luding , Onno Bokhove

We computationally study the flow of Newtonian fluids through sinusoidal expansion-contraction microchannels at low Reynolds number. We first use a perturbation method to analytically derive series solutions for the stream function and…

We present a novel method for guaranteeing linear momentum in learned physics simulations. Unlike existing methods, we enforce conservation of momentum with a hard constraint, which we realize via antisymmetrical continuous convolutional…

Machine Learning · Computer Science 2022-11-03 Lukas Prantl , Benjamin Ummenhofer , Vladlen Koltun , Nils Thuerey
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