A review of nonlinear FFT-based computational homogenization methods
M Schneider - Acta Mechanica, 2021 - Springer
Since their inception, computational homogenization methods based on the fast Fourier
transform (FFT) have grown in popularity, establishing themselves as a powerful tool …
transform (FFT) have grown in popularity, establishing themselves as a powerful tool …
The role of chemistry in fracture pattern development and opportunities to advance interpretations of geological materials
Fracture pattern development has been a challenging area of research in the Earth sciences
for more than 100 years. Much has been learned about the spatial and temporal complexity …
for more than 100 years. Much has been learned about the spatial and temporal complexity …
Versatile and efficient pore network extraction method using marker-based watershed segmentation
JT Gostick - Physical Review E, 2017 - APS
Obtaining structural information from tomographic images of porous materials is a critical
component of porous media research. Extracting pore networks is particularly valuable since …
component of porous media research. Extracting pore networks is particularly valuable since …
Imaging and image-based fluid transport modeling at the pore scale in geological materials: A practical introduction to the current state-of-the-art
Fluid flow and mass transport in geological materials are crucial in diverse Earth science
applications. To fully understand the behavior of geological materials in this context, the …
applications. To fully understand the behavior of geological materials in this context, the …
Driving digital rock towards machine learning: Predicting permeability with gradient boosting and deep neural networks
We present a research study aimed at testing of applicability of machine learn-ing
techniques for permeability prediction. We prepare a training set containing. 3D scans of …
techniques for permeability prediction. We prepare a training set containing. 3D scans of …
[HTML][HTML] Deep CNNs as universal predictors of elasticity tensors in homogenization
B Eidel - Computer Methods in Applied Mechanics and …, 2023 - Elsevier
In the present work, 3D convolutional neural networks (CNNs) are trained to link random
heterogeneous, multiphase materials to their elastic macroscale stiffness thus replacing …
heterogeneous, multiphase materials to their elastic macroscale stiffness thus replacing …
Determining Young's modulus of granite using accurate grain-based modeling with microscale rock mechanical experiments
It is critical to rigorously determine the mechanical properties of granitic rocks to effectively
analyze and manage subsurface engineering activities, such as geothermal energy …
analyze and manage subsurface engineering activities, such as geothermal energy …
Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods
Permeability prediction is crucial in shale gas and CO 2 geological sequestration. However,
the intricate pore structure complicates the prediction of permeability. Machine learning (ML) …
the intricate pore structure complicates the prediction of permeability. Machine learning (ML) …
Computational homogenization of elasticity on a staggered grid
In this article, we propose to discretize the problem of linear elastic homogenization by finite
differences on a staggered grid and introduce fast and robust solvers. Our method shares …
differences on a staggered grid and introduce fast and robust solvers. Our method shares …
A general review of CO2 sequestration in underground geological formations and assessment of depleted hydrocarbon reservoirs in the Niger Delta
This paper investigates the viability of CO 2 storage in geological formations, including
depleted hydrocarbon reservoirs applying 3-dimensional seismic and well data of the Niger …
depleted hydrocarbon reservoirs applying 3-dimensional seismic and well data of the Niger …