[Књига][B] Multiscale Model Reduction

E Chung, Y Efendiev, TY Hou - 2023 - Springer
The mathematization of all sciences, the fading of traditional scientific boundaries, the
impact of computer technology, the growing importance of computer modeling and the …

[HTML][HTML] Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

Z Ma, X Ou, B Zhang - Journal of Rock Mechanics and Geotechnical …, 2024 - Elsevier
Geomechanical assessment using coupled reservoir-geomechanical simulation is
becoming increasingly important for analyzing the potential geomechanical risks in …

Prediction of numerical homogenization using deep learning for the Richards equation

S Stepanov, D Spiridonov, T Mai - Journal of Computational and Applied …, 2023 - Elsevier
For the nonlinear Richards equation as an unsaturated flow through heterogeneous media,
we build a new coarse-scale approximation algorithm utilizing numerical homogenization …

Multicontinuum homogenization and its relation to nonlocal multicontinuum theories

Y Efendiev, WT Leung - Journal of Computational Physics, 2023 - Elsevier
In this paper, we present a general derivation of multicontinuum equations and discuss cell
problems. We present constraint cell problem formulations in a representative volume …

Decoupled multiscale numerical approach for reactive transport in marine sediment column

M Vasilyeva, RB Coffin, I Pecher - Computer Methods in Applied Mechanics …, 2024 - Elsevier
In this work, we consider biotic and abiotic reactive transport processes through marine
sediment vertical profiles. The mathematical model is described by a multicomponent …

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Z Wang, I Battiato - Advances in Water Resources, 2024 - Elsevier
Pore-scale modeling has limited applicability at large scales due to its high computational
cost. One common approach to upscale pore-scale models is the use of effective medium …

Generalized Multiscale Finite Element Method for discrete network (graph) models

M Vasilyeva - Journal of Computational and Applied Mathematics, 2025 - Elsevier
In this paper, we consider a time-dependent discrete network model with highly varying
connectivity. The approximation by time is performed using an implicit scheme. We propose …

[HTML][HTML] Machine learning for accelerating macroscopic parameters prediction for poroelasticity problem in stochastic media

M Vasilyeva, A Tyrylgin - Computers & Mathematics with Applications, 2021 - Elsevier
In this paper, we consider a coarse grid approximation (numerical homogenization and
multiscale finite element method) for the poroelasticity problem with stochastic properties …

[HTML][HTML] Estimation of macroscopic failure strength of heterogeneous geomaterials containing inclusion and pore with artificial neural network approach

J Xue, Y Cao, Z Yin, J Shao, N Burlion - Computers and Geotechnics, 2024 - Elsevier
This work is devoted to estimation of macroscopic failure strength of heterogeneous rock-like
and cement-based materials. Three representative microstructures are considered …

[HTML][HTML] Generalized multiscale finite element method for multicontinua unsaturated flow problems in fractured porous media

D Spiridonov, M Vasilyeva, ET Chung - Journal of Computational and …, 2020 - Elsevier
In this paper, we present a multiscale method for simulations of the multicontinua
unsaturated flow problems in heterogeneous fractured porous media. The mathematical …