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Flood mapping is crucial for assessing and mitigating flood impacts, yet traditional methods like numerical modeling and aerial photography face limitations in efficiency and reliability. To address these challenges, we propose PIFF, a…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 ChunLiang Wu , Tsunhua Yang , Hungying Chen

In this paper we study the use of Virtual Element method for geomechanics. Our emphasis is on applications to reservoir simulations. The physical processes that form the reservoirs, such as sedimentation, erosion and faulting, lead to…

Numerical Analysis · Mathematics 2017-02-09 Odd Andersen , Halvor M. Nilsen , Xavier Raynaud

Precise estimation of Crash Modification Factors (CMFs) is central to evaluating the effectiveness of various road safety treatments and prioritizing infrastructure investment accordingly. While customized study for each countermeasure…

Machine Learning · Computer Science 2023-11-16 Yanlin Qi , Jia Li , Michael Zhang

Performance analysis based on modelling consists of two major steps: model construction and model analysis. Formal modelling techniques significantly aid model construction but can exacerbate model analysis. In particular, here we consider…

Performance · Computer Science 2013-09-09 Alireza Pourranjbar , Jane Hillston

We studied the effects on oil sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial…

We used numerical simulations based on the finite element method (FEM) to calculate both the amplitude and phase information of the scattered electric field from random rough surfaces, which can be directly compared to ellipsometric…

Computational Physics · Physics 2019-02-27 B. Fodor , P. Kozma , S. Burger , M. Fried , P. Petrik

Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces. This understanding is crucial for the rational design of new solid catalysts as well as materials to store energy and mitigate greenhouse…

Predicting the geometrical evolution of the pore space in geological formations due to fluid-solid interactions has applications in reservoir engineering, oil recovery, and geological storage of carbon dioxide. However, modeling frameworks…

In the application of the combustion models based on low-dimensional manifolds (for instance flamelet models) to large-eddy simulation (LES) of reactive turbulent flows, the modeling simplifications of the combustion process is a critical…

Fluid Dynamics · Physics 2017-12-05 Hao Wu , Peter C. Ma , Thomas Jaravel , Matthias Ihme

Material properties such as permeability fields in heterogeneous porous media are often represented as discontinuous, piecewise constant data tied to a given spatial discretization. Such representations are inherently mesh-dependent,…

Numerical Analysis · Mathematics 2026-05-19 Kapil Chawla , Sanghyun Lee , Yeonjong Shin

The accurate representation of variable renewable generation (RES, e.g., wind, solar PV) assets in capacity expansion planning (CEP) studies is paramount to capture spatial and temporal correlations that may exist between sites and impact…

Systems and Control · Electrical Eng. & Systems 2021-04-14 David Radu , Antoine Dubois , Mathias Berger , Damien Ernst

A heterogeneous brittle material characterized by a random field of local toughness Kc(x) can be represented by an equivalent homogeneous medium of toughness, Keff. Homogenization refers to a process of estimating Keff from the local field…

Other Condensed Matter · Physics 2015-06-24 Stephane Roux , Damien Vandembroucq , Francois Hild

The quality of astrochemical models is highly dependent on reliable binding energy (BE) values that consider the morphological and energetic variety of binding sites on the surface of ice-grain mantles. Here, we present the Binding Energy…

Instrumentation and Methods for Astrophysics · Physics 2022-08-31 Giulia M. Bovolenta , Stefan Vogt-Geisse , Stefano Bovino , Tommaso Grassi

In many CAD-based applications, complex geometries are defined by a high number of design parameters. This leads to high-dimensional design spaces that are challenging for downstream engineering processes like simulations, optimization, and…

Machine Learning · Computer Science 2026-03-24 Alexander Köhler , Michael Breuß

The phase field fracture method has emerged as a promising computational tool for modelling a variety of problems including, since recently, hydrogen embrittlement and stress corrosion cracking. In this work, we demonstrate the potential of…

Applied Physics · Physics 2020-11-17 P. K. Kristensen , C. F. Niordson , E. Martínez-Pañeda

We consider the problem of describing excursion sets of a real-valued function $f$, i.e. the set of inputs where $f$ is above a fixed threshold. Such regions are hard to visualize if the input space dimension, $d$, is higher than 2. For a…

Methodology · Statistics 2019-05-28 Dario Azzimonti , David Ginsbourger , Jérémy Rohmer , Déborah Idier

We use density functional theory (DFT) with the generalized gradient approximation (GGA) and our first-principles extrapolation method for accurate chemisorption energies {[Mason {\em et al.}, Phys. Rev. B {\bf 69}, 161401R (2004)]} to…

Materials Science · Physics 2007-05-23 Sara E. Mason , Ilya Grinberg , Andrew M. Rappe

To reduce the experimental validation workload for chemical researchers and accelerate the design and optimization of high-energy-density lithium metal batteries, we aim to leverage models to automatically predict Coulombic Efficiency (CE)…

Machine Learning · Computer Science 2024-07-31 Xinhe Li , Zhuoying Feng , Yezeng Chen , Weichen Dai , Zixu He , Yi Zhou , Shuhong Jiao

Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform…

Chemical Physics · Physics 2018-03-19 Pascal Pernot , Andreas Savin

Over the years data assimilation methods have been developed to obtain estimations of uncertain model parameters by taking into account a few observations of a model state. The most reliable methods of MCMC are computationally expensive.…

Applications · Statistics 2018-11-14 Sangeetika Ruchi , Svetlana Dubinkina