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An adaptive model for the description of flows in highly heterogeneous porous media is developed in~\cite{FP21,FP23}. There, depending on the magnitude of the fluid's velocity, the constitutive law linking velocity and pressure gradient is…

Numerical Analysis · Mathematics 2024-05-06 Alessio Fumagalli , Francesco S. Patacchini

In this work, we contribute to the broader understanding of inverse problems by introducing a versatile multiscale modeling framework tailored to the challenges of sediment concentration estimation. Specifically, we propose a novel approach…

Numerical Analysis · Mathematics 2025-03-14 Jiwei Li , Lingyun Qiu , Zhongjing Wang , Hui Yu , Siqin Zheng

In this paper a spatial homogeneous vehicular traffic flow model based on a stochastic master equation of Boltzmann type in the acceleration variable is solved numerically for a special driver interaction model. The solution is done by a…

Other Condensed Matter · Physics 2009-11-10 K. Thomas Waldeer

The objective for this work is to develop a data-driven proxy to high-fidelity numerical flow simulations using digital images. The proposed model can capture the flow field and permeability in a large verity of digital porous media based…

Image and Video Processing · Electrical Eng. & Systems 2019-05-16 Ali Takbiri-Borujeni , Hadi Kazemi , Nasser Nasrabadi

A stochastic system of particles is considered in which the sizes of the particles increase by successive binary mergers with the constraint that each coagulation event involves a particle with minimal size. Convergence of a suitably…

Probability · Mathematics 2011-10-31 Anne-Laure Basdevant , Philippe Laurencot , James R. Norris , Clement Rau

In this work we propose upscaling method for nonlinear Forchheimer flow in highly heterogeneous porous media. The generalized Forchheimer law is considered for incompressible and slightly-compressible single-phase flows. We use recently…

Numerical Analysis · Mathematics 2015-06-15 Eugenio Aulisa , Lidia Bloshanskaya , Yalchin Efendiev , Akif Ibragimov

Stochastic mathematical models are essential tools for understanding and predicting complex phenomena. The purpose of this work is to study the exit times of a stochastic dynamical system-specifically, the mean exit time and the…

Probability · Mathematics 2025-08-06 Eric José Ávila-Vales , José Villa-Morales

A two-phase model and its application to wavefields numerical simulation are discussed in the context of modeling of compressible fluid flows in elastic porous media. The derivation of the model is based on a theory of thermodynamically…

Fluid Dynamics · Physics 2020-06-11 Evgeniy Romenski , Galina Reshetova , Ilya Peshkov , Michael Dumbser

We investigate two-phase flow in porous media and derive a two-scale model, which incorporates pore-scale phase distribution and surface tension into the effective behavior at the larger Darcy scale. The free-boundary problem at the pore…

Analysis of PDEs · Mathematics 2023-07-03 Mathis Kelm , Carina Bringedal , Bernd Flemisch

We study the interplay of pore-scale mixing and network-scale advection through heterogeneous porous media, and its role for the evolution and asymptotic behavior of hydrodynamic dispersion. In a Lagrangian framework, we identify three…

Fluid Dynamics · Physics 2021-04-28 Alexandre Puyguiraud , Philippe Gouze , Marco Dentz

We analyze diffusion processes with finite propagation speed in a non-homogeneous medium in terms of the heterogeneous telegrapher's equation. In the diffusion limit of infinite-velocity propagation we recover the results for the…

Statistical Mechanics · Physics 2022-11-18 Trifce Sandev , Ljupco Kocarev , Ralf Metzler , Aleksei Chechkin

In this article we study (possibly degenerate) stochastic differential equations (SDE) with irregular (or discontiuous) coefficients, and prove that under certain conditions on the coefficients, there exists a unique almost everywhere…

Probability · Mathematics 2009-08-18 Xicheng Zhang

Point processes are stochastic models generating interacting points or events in time, space, etc. Among characteristics of these models, first-order intensity and conditional intensity functions are often considered. We focus on…

Statistics Theory · Mathematics 2023-05-24 Jean-François Coeurjolly , Ismaïla Ba , Achmad Choiruddin

We determine the asymptotic behavior of the solutions to the linear elastodynamic equations in a stratified medium comprising an alternation of possibly very stiff layers with much softer ones, when the thickness of the layers tends to…

Analysis of PDEs · Mathematics 2015-10-09 Michel Bellieud

Solving flow through porous media is a crucial step in the topology optimisation of cold plates, a key component in modern thermal management. Traditional computational fluid dynamics (CFD) methods, while accurate, are often prohibitively…

Fluid Dynamics · Physics 2026-03-10 Jinhong Wang , Matei C. Ignuta-Ciuncanu , Ricardo F. Martinez-Botas , Teng Cao

Computational models in cardiac electrophysiology are notorious for long runtimes, restricting the numbers of nodes and mesh elements in the numerical discretisations used for their solution. This makes it particularly challenging to…

We compare the computational performance of two modeling approaches for the flow of dilute cavitation bubbles in a liquid. The first approach is a deterministic model, for which bubbles are represented in a Lagrangian framework as advected…

Fluid Dynamics · Physics 2023-02-23 Spencer H. Bryngelson , Kevin Schmidmayer , Tim Colonius

Multiphase flow in porous media occurs in several disciplines including petroleum reservoir engineering, petroleum systems' analysis, and CO$_2$ sequestration. While simulations often use a fully implicit discretization to increase the time…

Fluid Dynamics · Physics 2017-06-12 Daniel A. Cogswell , Michael L. Szulczewski

In this paper, a useful reinterpretation of the city as a porous medium justifies the application of well-known models on fluid dynamics to develop a multi-model study of urban air pollution due to traffic flow in a large city. Thus, to…

Numerical Analysis · Mathematics 2025-02-21 N. Garcia-Chan , L. J. Alvarez-Vazquez , A. Martinez , M. E. Vazquez-Mendez

In this paper, we propose a deep learning based reduced order modeling method for stochastic underground flow problems in highly heterogeneous media. We aim to utilize supervised learning to build a reduced surrogate model from the…

Numerical Analysis · Mathematics 2022-07-27 Yiran Wang , Eric Chung , Shubin Fu