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Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses.…

Physics and Society · Physics 2015-05-08 Sarah LaRocca , Jonas Johansson , Henrik Hassel , Seth Guikema

In recent years, convolutional neural networks (CNNs) have experienced an increasing interest in their ability to perform a fast approximation of effective hydrodynamic parameters in porous media research and applications. This paper…

Machine Learning · Computer Science 2022-04-14 Stephan Gärttner , Faruk O. Alpak , Andreas Meier , Nadja Ray , Florian Frank

Kinetic models provide highly accurate descriptions of plasma waves but involve complex integrals that are computationally expensive to solve. To facilitate a fluid-like treatment of the system, we propose rational approximations for both…

Plasma Physics · Physics 2025-08-13 Huasheng Xie

The goal of this study is to propose an efficient numerical model for the predictions of capillary adsorption phenomena in a porous material. The Scharfetter-Gummel numerical scheme is proposed to solve an advection-diffusion equation with…

Computational Engineering, Finance, and Science · Computer Science 2020-02-20 Ainagul Jumabekova , Julien Berger , Denys Dutykh , Hervé Le Meur , Aurélie Foucquier , Mickaël Pailha , Christophe Ménézo

Computational models in chemistry rely on a number of approximations. The effect of such approximations on observables derived from them is often unpredictable. Therefore, it is challenging to quantify the uncertainty of a computational…

Chemical Physics · Physics 2017-04-21 Gregor N. Simm , Jonny Proppe , Markus Reiher

During the last decade, lattice-Boltzmann (LB) simulations have been improved to become an efficient tool for determining the permeability of porous media samples. However, well known improvements of the original algorithm are often not…

Fluid Dynamics · Physics 2010-11-30 Ariel Narváez , Thomas Zauner , Frank Raischel , Rudolf Hilfer , Jens Harting

Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a…

Neural and Evolutionary Computing · Computer Science 2013-01-15 Tina Yu , Dave Wilkinson , Julian Clark , Morgan Sullivan

The adsorption energy of benzene on various metal substrates is predicted using the random phase approximation (RPA) for the correlation energy. Agreement with available experimental data is systematically better than 10% for both coinage…

Chemical Physics · Physics 2017-11-29 J. A. Garrido Torres , B. Ramberger , H. Früchtl , R. Schaub , G. Kresse

Subsurface storage of CO$_2$ is an important means to mitigate climate change, and to investigate the fate of CO$_2$ over several decades in vast reservoirs, numerical simulation based on realistic models is essential. Faults and other…

Numerical Analysis · Mathematics 2023-12-12 Per Pettersson , Eirik Keilegavlen , Tor Harald Sandve , Sarah Gasda , Sebastian Krumscheid

The random phase approximation (RPA) has emerged as a prominent first-principles method in material science, particularly to study the adsorption and chemisorption of small molecules on surfaces. However, its widespread application is…

Materials Science · Physics 2025-09-01 Edoardo Spadetto , Pier Herman Theodoor Philipsen , Arno Förster , Lucas Visscher

Improving hydrocarbon production with hydraulic fracturing from unconventional reservoirs requires investigating transport phenomena at the single fracture level. In this study, we simulated geomechanical deformation, fluid flow, and…

Fluid Dynamics · Physics 2026-01-21 Morteza Heydari , Feng Liang , Hui-Hai Liu , Behzad Ghanbarian

The random process theory (RPT) has been widely applied to predict the joint probability distribution functions (PDFs) of asperity heights and curvatures of rough surfaces. A check of the predictions of RPT against the actual statistics of…

Materials Science · Physics 2015-06-24 Claudia Borri , Marco Paggi

Radiative transfer effects need to be taken into account when analysing spectral line observations. When the data are not sufficient for detailed modelling, simpler methods are needed. The escape probability formalism (EPF) is one such…

Instrumentation and Methods for Astrophysics · Physics 2025-04-16 Mika Juvela

Effective bending moduli of a fluid membrane are investigated by means of the transfer-matrix method developed in our preceding paper. This method allows us to survey various statistical measures for the partition sum. The role of the…

Soft Condensed Matter · Physics 2009-11-10 Yoshihiro Nishiyama

For rockfall hazard assessment on areas more than several km2 in size, the quantification of runout probability is usually done empirically. Classical methods use statistical distributions of reach or energy angles derived from rockfall…

Geophysics · Physics 2024-04-24 Marc Peruzzetto , Bastien Colas , Clara Lévy , Jérémy Rohmer , Franck Bourrier

We propose a machine-learning-based (ML-based) method for efficiently predicting atomic diffusivity in crystals, in which the potential energy surface (PES) of a diffusion carrier is partially evaluated by first-principles calculations. To…

Materials Science · Physics 2020-06-24 Kazuaki Toyoura , Takeo Fujii , Kenta Kanamori , Ichiro Takeuchi

The study of flow in fractured porous media is a key ingredient for many geoscience applications, such as reservoir management and geothermal energy production. Modelling and simulation of these highly heterogeneous and geometrically…

Numerical Analysis · Mathematics 2022-12-28 Davide Losapio , Anna Scotti

Pipelines for water supply are susceptible to burst-leakage due to fluid pressures of various nature. High pressure heads resulting in circumferential and (or) axial stresses larger than the material yield stress could cause pipe failure.…

Signal Processing · Electrical Eng. & Systems 2021-08-24 Radhika P , Anu Mol Joy

The development of semilocal models for the kinetic energy density (KED) is an important topic in density functional theory (DFT). This is especially true for subsystem DFT, where these models are necessary to construct the required…

Other Condensed Matter · Physics 2017-02-15 S. Śmiga , E. Fabiano , L. A. Constantin , F. Della Sala

Employing physically-consistent numerical methods is an important step towards attaining robust and accurate numerical simulations. When addressing compressible flows, in addition to preserving kinetic energy at a discrete level, as done in…

Fluid Dynamics · Physics 2024-08-13 Carlo De Michele , Gennaro Coppola