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In this work, we propose a novel model order reduction approach for two-phase flow in porous media by introducing a formulation in which the mobility, which realizes the coupling between phase saturations and phase pressures, is regarded as…

Numerical Analysis · Mathematics 2014-05-13 Sven Kaulmann , Bernd Flemisch , Bernard Haasdonk , Knut-Andreas Lie , Mario Ohlberger

The accurate and stable simulation of viscoelastic flows remains a significant computational challenge, exacerbated for flows in non-trivial and practical geometries. Here we present a new high-order meshless approach with variable…

Fluid Dynamics · Physics 2024-05-01 Jack R. C. King , Steven J. Lind

With meshfree and fully Lagrangian features of particle methods, smoothed particle hydrodynamics (SPH) is suitable to achieve high-accurate simulations of multiphase flows with large interfacial deformations, discontinuities, and…

Fluid Dynamics · Physics 2020-10-26 Feiguo Chen

Computational Fluid Dynamics (CFD) is a hugely important subject with applications in almost every engineering field, however, fluid simulations are extremely computationally and memory demanding. Towards this end, we present Lat-Net, a…

Machine Learning · Statistics 2017-05-26 Oliver Hennigh

We develop and fully characterize a meshfree Lagrangian (particle) model for continuum-based numerical modeling of dry and submerged granular flows. The multiphase system of the granular material and the ambient fluid is treated as a…

Soft Condensed Matter · Physics 2017-11-02 Ehsan Jafari-Nodoushan , Ahmad Shakibaeinia , Khosrow Hosseini

First, a meshless simulation method is presented for multiphase fluid-particle flows with a two-way coupled Smoothed Particle Hydrodynamics (SPH) for the fluid and the Discrete Element Method (DEM) for the solid phase. The unresolved fluid…

Fluid Dynamics · Physics 2014-02-28 Martin Robinson , Stefan Luding , Marco Ramaioli

High-fidelity computational fluid dynamics (CFD) simulations for design space explorations can be exceedingly expensive due to the cost associated with resolving the finer scales. This computational cost/accuracy trade-off is a major…

Fluid Dynamics · Physics 2024-03-14 Peetak Mitra , Majid Haghshenas , Niccolo Dal Santo , Conor Daly , David P. Schmidt

Monte Carlo methods play important part in modern statistical physics. The application of these methods suffer from two main difficulties.The first is caused by the relatively small number of particles that can participate in any numerical…

Statistical Mechanics · Physics 2007-05-23 A. Brandt , V. Ilyin

Accurately resolving the coupled momentum transfer between the liquid and solid phases of complex fluids is a fundamental problem in multiphase transport processes, such as hydraulic fracture operations. Specifically we need to characterize…

Fluid Dynamics · Physics 2021-12-22 Célio Fernandes , Salah Faroughi , Ricardo Ribeiro , Ana Isabel , Gareth McKinley

The separation between molecular and mesoscopic length and time scales poses a severe limit to molecular simulations of mesoscale phenomena. We describe a hybrid multiscale computational technique which address this problem by keeping the…

Fluid Dynamics · Physics 2009-11-13 G. De Fabritiis , R. Delgado-Buscalioni , P. V. Coveney

Our goal of this paper is to develop a new upscaling method for multicontinua flow problems in fractured porous media. We consider a system of equations that describes flow phenomena with multiple flow variables defined on both matrix and…

Numerical Analysis · Mathematics 2018-07-17 Maria Vasilyeva , Eric T. Chung , Siu Wun Cheung , Yating Wang , Georgy Prokopev

Mixtures of fluids and granular sediments play an important role in many industrial, geotechnical, and aerospace engineering problems, from waste management and transportation (liquid--sediment mixtures) to dust kick-up below helicopter…

Computational Engineering, Finance, and Science · Computer Science 2021-07-07 Aaron S. Baumgarten , Benjamin L. S. Couchman , Ken Kamrin

Despite the recent interest in the discontinuous shear-thickening (DST) behaviour, few computational works tackle the rich hydrodynamics of these fluids. In this work, we present the first implementation of a microstructural DST model in…

Fluid Dynamics · Physics 2023-11-27 Peter Angerman , Sagaya Prasanna Kumar , Bjornar Sandnes , Ryohei Seto , Marco Ellero

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations…

In order to reduce the computational cost of the simulation of electromagnetic responses in geophysical settings that involve highly heterogeneous media, we develop a multiscale finite volume method with oversampling for the quasi-static…

Computational Physics · Physics 2016-10-10 Luz Angelica Caudillo Mata , Eldad Haber , Christoph Schwarzbach

Particle methods play an important role in computational fluid dynamics, but they are among the most difficult to implement and solve. The most common method is smoothed particle hydrodynamics, which is suitable for problem settings that…

Fluid Dynamics · Physics 2025-08-26 Masato Shibukawa , Naoya Ozaki , Maximilien Berthet

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

Systems comprising a turbulent channel flow overlaying a permeable bed can be found in a variety of industrial and natural applications (e.g. urban planning, fracking, submerged vegetation). One important realization of this system is at…

Fluid Dynamics · Physics 2017-08-01 Benjamin H. Sonin

Fluid simulation is an important research topic in computer graphics (CG) and animation in video games. Traditional methods based on Navier-Stokes equations are computationally expensive. In this paper, we treat fluid motion as point cloud…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Yu Chen , Shuai Zheng , Nianyi Wang , Menglong Jin , Yan Chang

In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3D heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural…

Geophysics · Physics 2021-05-21 Bicheng Yan , Dylan Robert Harp , Bailian Chen , Rajesh Pawar
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