Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Iliev, Oleg P."'
We present ConDiff, a novel dataset for scientific machine learning. ConDiff focuses on the diffusion equation with varying coefficients, a fundamental problem in many applications of parametric partial differential equations (PDEs). The main novelty
Externí odkaz:
http://arxiv.org/abs/2406.04709
Autor:
Herkert, Robin, Buchfink, Patrick, Wenzel, Tizian, Haasdonk, Bernard, Toktaliev, Pavel, Iliev, Oleg
We address the challenging application of 3D pore scale reactive flow under varying geometry parameters. The task is to predict time-dependent integral quantities, i.e., breakthrough curves, from the given geometries. As the 3D reactive flow simulati
Externí odkaz:
http://arxiv.org/abs/2405.19170
Large linear systems are ubiquitous in modern computational science. The main recipe for solving them is iterative solvers with well-designed preconditioners. Deep learning models may be used to precondition residuals during iteration of such linear
Externí odkaz:
http://arxiv.org/abs/2405.15557
In this paper, we investigate the structure of the Schur complement matrix for the fully-staggered finite-difference discretization of the stationary Stokes equation. Specifically, we demonstrate that the structure of the Schur complement matrix depe
Externí odkaz:
http://arxiv.org/abs/2309.01255
If the Stokes equations are properly discretized, it is known that the Schur complement matrix is spectrally equivalent to the identity matrix. Moreover, in the case of simple geometries, it is often observed that most of its eigenvalues are equal to
Externí odkaz:
http://arxiv.org/abs/2307.05266
Reactive flows in porous media play an important role in our life and are crucial for many industrial, environmental and biomedical applications. Very often the concentration of the species at the inlet is known, and the so-called breakthrough curves
Externí odkaz:
http://arxiv.org/abs/2301.04998
Publikováno v:
Journal of the Mechanical Behavior of Materials, Vol 11, Iss 4, Pp 275-294 (2000)
Externí odkaz:
https://doaj.org/article/6268ac65b78a4775929627c41064ff2f
Reactive flows are important part of numerous technical and environmental processes. Often monitoring the flow and species concentrations within the domain is not possible or is expensive, in contrast, outlet concentration is straightforward to measu
Externí odkaz:
http://arxiv.org/abs/2204.11719
Autor:
Pimanov, Vladislav, Lukoshkin, Vladislav, Toktaliev, Pavel, Iliev, Oleg, Muravleva, Ekaterina, Orlov, Denis, Krutko, Vladislav, Avdonin, Alexander, Steiner, Konrad, Koroteev, Dmitry
The paper presents a workflow for fast pore-scale simulation of single-phase flow in tight reservoirs typically characterized by low, multiscale porosity. Multiscale porosity implies that the computational domain contains porous voxels (unresolved po
Externí odkaz:
http://arxiv.org/abs/2203.11782
Autor:
Gavrilenko, Pavel, Haasdonk, Bernard, Iliev, Oleg, Ohlberger, Mario, Schindler, Felix, Toktaliev, Pavel, Wenzel, Tizian, Youssef, Maha
We present an integrated approach for the use of simulated data from full order discretization as well as projection-based Reduced Basis reduced order models for the training of machine learning approaches, in particular Kernel Methods, in order to a
Externí odkaz:
http://arxiv.org/abs/2104.02800