English
Related papers

Related papers: A DuMux Framework for Data-Driven Multi-Scale Para…

200 papers

In this paper, we propose a deep-learning-based approach to a class of multiscale problems. THe Generalized Multiscale Finite Element Method (GMsFEM) has been proven successful as a model reduction technique of flow problems in…

Numerical Analysis · Mathematics 2018-10-30 Min Wang , Siu Wun Cheung , Eric T. Chung , Yalchin Efendiev , Wing Tat Leung , Yating Wang

In this thesis, we develop multiscale models for particle simulations in population dynamics. These models are characterised by prescribing particle motion on two spatial scales: microscopic and macroscopic. At the microscopic level, each…

Computational Engineering, Finance, and Science · Computer Science 2016-09-14 Omar Richardson

This paper develops a computational framework for optimizing the parameters of data assimilation systems in order to improve their performance. The approach formulates a continuous meta-optimization problem for parameters; the…

Computational Engineering, Finance, and Science · Computer Science 2015-06-16 Alexandru Cioaca , Adrian Sandu

The effective mixing behavior of solutes in porous media is fundamentally connected to the development of a local mixing interface between the two initial solutions, which is characterized by a complex lamellar structure. The deformation of…

Fluid Dynamics · Physics 2025-02-28 Daniel M C Hallack , Guillem Sole-Mari , Saif Farhat , Diogo Bolster

Multiphase flow through a porous medium involves complex interactions between gravity, wettability and capillarity during drainage process. In contrast to these factors, the effect of pore distribution on liquid retention is less…

Soft Condensed Matter · Physics 2018-10-30 Guanzhe Cui , Mingchao Liu , Weijing Dai , Yixiang Gan

This study performs parameter inference in a partial differential equations system of pulmonary circulation. We use a fluid dynamics network model that takes selected parameter values and mimics the behaviour of the pulmonary haemodynamics…

This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of micro-CT images of real microgeometries. The primary goal is to develop an efficient,…

Fluid Dynamics · Physics 2025-01-14 Yousef Heider , Fadi Aldakheel , Wolfgang Ehlers

Physics-based models often involve large systems of parametrized partial differential equations, where design parameters control various properties. However, high-fidelity simulations of such systems on large domains or with high grid…

Computational Physics · Physics 2025-05-15 Diba Behnoudfar

Density level sets can be estimated using plug-in methods, excess mass algorithms or a hybrid of the two previous methodologies. The plug-in algorithms are based on replacing the unknown density by some nonparametric estimator, usually the…

Statistics Theory · Mathematics 2016-11-26 A. Rodríguez-Casal , P. Saavedra-Nieves

Two-fluid interfaces in porous media, an example of driven disordered systems, were studied by a real time three-dimensional imaging technique with pore scale resolution for a less viscous fluid displacing a more viscous one. With…

Soft Condensed Matter · Physics 2011-03-23 Prerna Sharma , P. Aswathi , Anit Sane , Shankar Ghosh , S. Bhattacharya

In this paper, we present a residual-driven multiscale method for simulating Darcy flow in perforated domains, where complex geometries and highly heterogeneous permeability make direct simulations computationally expensive. To address…

Numerical Analysis · Mathematics 2026-03-11 Wei Xie , Shubin Fu , Yin Yang , Yunqing Huang

We performed a set of numerical simulations to characterize the interplay of fracture network topology, upscaling, and mesh refinement on flow and transport properties in fractured porous media. We generated a set of generic…

Computational Engineering, Finance, and Science · Computer Science 2023-02-23 Aleksandra A. Pachalieva , Matthew R. Sweeney , Hari Viswanathan , Emily Stein , Rosie Leone , Jeffrey D. Hyman

Many-Objective Feature Selection (MOFS) approaches use four or more objectives to determine the relevance of a subset of features in a supervised learning task. As a consequence, MOFS typically returns a large set of non-dominated…

Machine Learning · Computer Science 2023-12-01 Uchechukwu F. Njoku , Alberto Abelló , Besim Bilalli , Gianluca Bontempi

The novel neural networks show great potential in solving partial differential equations. For single-phase flow problems in subsurface porous media with high-contrast coefficients, the key is to develop neural operators with accurate…

Machine Learning · Computer Science 2025-09-17 Peiqi Li , Jie Chen

Drops on a free-flow/porous-medium-flow interface have a strong influence on the exchange of mass, momentum and energy between the two macroscopic flow regimes. Modeling droplet-related pore-scale processes in a macro-scale context is…

Computational Physics · Physics 2021-03-17 Sina Ackermann , Carina Bringedal , Rainer Helmig

Direct pore scale simulations of two-fluid flow on digital rock images provide a promising tool to understand the role of surface wetting phenomena on flow and transport in geologic reservoirs. We present computational protocols that mimic…

Geophysics · Physics 2020-07-27 James E. McClure , Zhe Li , Mark Berrill , Thomas Ramstad

Field-of-view and resolution trade-offs in X-Ray micro-computed tomography (micro-CT) imaging limit the characterization, analysis and model development of multi-scale porous systems. To this end, we developed an applied methodology…

The established macroscopic equations of motion for two phase immiscible displacement in porous media are known to be physically incomplete because they do not contain the surface tension and surface areas governing capillary phenomena.…

Materials Science · Physics 2009-10-31 R. Hilfer

The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can…

Machine Learning · Statistics 2017-07-20 Julia Ling , Max Hutchinson , Erin Antono , Sean Paradiso , Bryce Meredig

Microtomography is a powerful method of materials investigation. It enables to obtain physical properties of porous media non-destructively that is useful in studies. One of the application ways is a calculation of porosity, pore sizes,…

Computational Physics · Physics 2020-07-08 Maxim Grigoriev , Anvar Khafizov , Vladislav Kokhan , Viktor Asadchikov