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Network Extraction algorithms from X-ray microcomputed tomography have become a routine method to obtain pore connectivity and pore morphology information from porous media. The main approaches for this extraction are either based on Max…

Numerical modelling of flow in stepped spillways is considered, focusing on a highly economical approach combining interface capturing with explicit modelling of air entrainment. Simulations are performed on spillways at four different…

Fluid Dynamics · Physics 2020-09-11 Silje Kreken Almeland , Timofey Mukha , Rickard E. Bensow

In this paper, Physics Informed Neural Network (PINN) is explored in order to obtain flow predictions near the wall region accurately with measurements (or sampling points) away from the wall. Often, in fluid mechanics experiments, it is…

Fluid Dynamics · Physics 2022-04-08 Vinothkumar Sekar , Qinghua Jiang , Chang Shu , Boo Cheong Khoo

We present a Markov Chain Monte Carlo algorithm based on the Metropolis algorithm for simulation of the flow of two immiscible fluids in a porous medium under macroscopic steady-state conditions using a dynamical pore network model that…

Fluid Dynamics · Physics 2016-12-20 Isha Savani , Santanu Sinha , Alex Hansen , Dick Bedeaux , Signe Kjelstrup , Morten Vassvik

The oversampling multiscale finite element method (MsFEM) is one of the most popular methods for simulating composite materials and flows in porous media which may have many scales. But the method may be inapplicable or inefficient in some…

Numerical Analysis · Mathematics 2012-11-16 Weibing Deng , Haijun Wu

Point cloud upsampling aims to generate dense point clouds from given sparse ones, which is a challenging task due to the irregular and unordered nature of point sets. To address this issue, we present a novel deep learning-based model,…

Computer Vision and Pattern Recognition · Computer Science 2022-06-09 Aihua Mao , Zihui Du , Junhui Hou , Yaqi Duan , Yong-jin Liu , Ying He

We propose a learned precomputation for the heterogeneous multiscale method (HMM) for rough-wall Stokes flow. A Fourier neural operator is used to approximate local averages over microscopic subsets of the flow, which allows to compute an…

Numerical Analysis · Mathematics 2025-07-21 Emanuel Ström , Anna-Karin Tornberg , Ozan Öktem

Many methods have been proposed to quantify the predictive uncertainty associated with the outputs of deep neural networks. Among them, ensemble methods often lead to state-of-the-art results, though they require modifications to the…

Machine Learning · Computer Science 2021-05-11 Zhiyun Lu , Eugene Ie , Fei Sha

A nonlinear ensemble-variational (EnVar) data assimilation is performed in order to estimate the unknown flow field over a slender cone at Mach-6, from isolated wall-pressure measurements. The cost functional accounts for discrepancies in…

Fluid Dynamics · Physics 2022-09-14 David A. Buchta , Stuart J. Laurence , Tamer A. Zaki

Fluid properties near rough surfaces are crucial in describing fundamental surface phenomena and modern industrial material design implementations. One of the most powerful approaches to model real rough materials is based on the surface…

Disordered Systems and Neural Networks · Physics 2021-02-10 Aleksey Khlyupin , Timur Aslyamov

We introduce a new and general continuum thermodynamic framework for the mathematical analysis and computation of adsorption on dynamic interfaces. To the best of our knowledge, there is no formulation available that accounts for the…

Fluid Dynamics · Physics 2013-07-31 Markus Schmuck , Serafim Kalliadasis

Fluid flow through intricate confining geometries often exhibits complex behaviors, certainly in porous materials, e.g. in groundwater flows or the operation of filtration devices and porous catalysts. However, it has remained extremely…

An active area of research interest is the inference of ecological models of complex microbial communities. Inferring such ecological models entails understanding the interactions between microbes and how they affect each other's growth.…

Applications · Statistics 2022-10-19 William Krinsman

Friction drag from a turbulent fluid moving past or inside an object plays a crucial role in domains as diverse as transportation, public utility infrastructure, energy technology, and human health. As a direct measure of the shear-induced…

Fluid Dynamics · Physics 2023-10-19 Esther Lagemann , Steven L. Brunton , Christian Lagemann

In this paper, we combine discrete empirical interpolation techniques, global mode decomposition methods, and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM), to reduce the computational…

Numerical Analysis · Mathematics 2023-07-19 Manal Alotaibi , Victor M. Calo , Yalchin Efendiev , Juan Galvis , Mehdi Ghommem

In this paper, we present a multiscale method for simulations of the multicontinua unsaturated flow problems in heterogeneous fractured porous media. The mathematical model is described by the system of Richards equations for each continuum…

Numerical Analysis · Mathematics 2019-08-02 Denis Spiridonov , Maria Vasilyeva , Eric T. Chung

A volume-averaged global model is developed to investigate surface-wave discharges inside either cylindrical or coaxial structures. The neutral and ion wall flux is self-consistently estimated based on a simplified analytical description…

This study presents a novel pressure-based methodology for the efficient numerical solution of a four-equation two-phase diffuse interface model. The proposed methodology has the potential to simulate low-Mach flows with mass transfer. In…

Fluid Dynamics · Physics 2021-10-12 Andreas D. Demou , Nicoló Scapin , Marica Pelanti , Luca Brandt

In the context of flow in porous media, up-scaling is the coarsening of a geological model and it is at the core of water resources research and reservoir simulation. An ideal up-scaling procedure preserves heterogeneities at different…

Statistical Mechanics · Physics 2007-05-23 V. Pancaldi , K. Christensen , P. R. King

Over the past decades, the volume-of-fluid (VOF) method has been the method of choice for simulating atomization processes, owing to its unique ability to discretely conserve mass. Current state-of-the-art VOF methods, however, rely on the…

Computational Physics · Physics 2024-01-29 Fabien Evrard , Robert Chiodi , Berend van Wachem , Olivier Desjardins