7 citations · 8 across the 4 of their papers we have counts for
4 papers
Machine learning methods for prediction of breakthrough curves in reactive porous media
Daria Fokina, Pavel Toktaliev, Oleg Iliev +1
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 th…
On the Performance of Machine Learning Methods for Breakthrough Curve Prediction
Daria Fokina, Oleg Iliev, Pavel Toktaliev +2
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 ex…
On a workflow for efficient computation of the permeability of tight sandstones
Vladislav Pimanov, Vladislav Lukoshkin, Pavel Toktaliev +7
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 impli…
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows
Pavel Gavrilenko, Bernard Haasdonk, Oleg Iliev +5
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 ma…