A surrogate model for the prediction of permeabilities and flow through porous media: a machine learning approach based on stochastic Brownian motion
Work
Year: 2022
Type: article
Abstract: In this contribution we propose a data-driven surrogate model for the prediction of permeabilities and laminar flow through two-dimensional random micro-heterogeneous materials; here Darcy’s law is u... more
Source: Computational Mechanics
Institution University of Duisburg-Essen
Cites: 35
Cited by: 12
Related to: 10
FWCI: 1.603
Citation percentile (by year/subfield): 75.8
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Sustainable Development Goal Peace, justice, and strong institutions
Open Access status: hybrid
APC paid (est): $3,590
Grant ID 05553726-TRR 270