Article
Computer Science, Interdisciplinary Applications
Nathaniel J. L. MacFadden, Ara N. Knaian
Summary: This article presents a new method for simulating particle transport through aerosols efficiently. By voxelizing the aerosol and generating 'droplets' voxel-by-voxel only when necessary, significant reductions in simulation time and memory usage can be achieved. The presented model demonstrates a decrease in simulation time of 1-2 orders of magnitude and a decrease in simulation memory of about 1 order of magnitude when compared to the benchmark method.
COMPUTER PHYSICS COMMUNICATIONS
(2022)
Article
Mathematics
B. Amaziane, L. Pankratov, A. Piatnitski
Summary: The paper discusses the stochastic homogenization of a system modeling immiscible compressible two-phase flow in random porous media, and successfully proves the convergence of solutions.
JOURNAL OF DIFFERENTIAL EQUATIONS
(2021)
Article
Energy & Fuels
Xuan Qin, Wanjun Yin
Summary: A novel theoretical model for calculating effective thermal conductivity in porous media is proposed in this study. The model takes into account the distribution characteristics of particle size and shows good agreement with existing models and experimental data. This model is of great significance for studying thermophysical mechanisms in granular porous media.
Article
Computer Science, Interdisciplinary Applications
Mikhail Panfilov, Stephane Popinet, Viatcheslav Vostrikov, Zharasbek Baishemirov, Abdumaulen Berdyshev
Summary: A multiscale fractured-porous medium consists of hierarchical levels of heterogeneity, and numerical simulation of fluid flow in such a medium is challenging due to the need for a very fine numerical grid. To reduce the number of numerical cells, irregular grids based on quadtree technology are suggested. Introducing a quantitative criterion allows for formalizing the procedure for building a quadtree and embedding it in the Basilisk platform.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Thermodynamics
Nicolas Favrie, Kevin Schmidmayer, Jacques Massoni
Summary: An Eulerian, hyperbolic, multiphase-flow model for dynamic and irreversible compaction of porous materials is constructed, with a reversible model also derived along with classical homogenization results. The irreversible model is developed based on basic principles, validated in quasi-static loading-unloading experiments, and demonstrated to be effective in capturing strong shock propagation in porous materials and dealing with fluid-porous material interfaces.
CONTINUUM MECHANICS AND THERMODYNAMICS
(2022)
Article
Environmental Sciences
T. Russell, O. Yu Dinariev, L. A. Pessoa Rego, P. Bedrikovetsky
Summary: The study investigates the stochastic distribution of particle velocities in particle flow, proposing a BGK-form of Boltzmann's equation for particulate flow. It explains the observed delay in particle velocity in laboratory studies and explicitly expresses the model coefficients for physical processes and their effects.
WATER RESOURCES RESEARCH
(2021)
Article
Mathematics, Interdisciplinary Applications
Wojciech Sobieski
Summary: The paper introduces the Waterfall Algorithm for calculating parameters characterizing the spatial structure of granular porous media, and investigates the influence of porosity and particle size on these parameters. New sensitive parameters are proposed in the study, and comparisons with other algorithms for calculating tortuosity are made.
COMPUTATIONAL PARTICLE MECHANICS
(2022)
Article
Thermodynamics
Xiaojing Zou, Changyu He, Wei Guan, Yan Zhou, Hongyang Zhao, Mingyu Cai
Summary: A model combining machine learning and stochastic generation of porous media was developed to predict reservoir tortuosity. Real core scanning images were used as reference for stochastic generation, and the particle swarm optimization algorithm was introduced for obtaining the best parameter combination. The model enables precise tortuosity predictions based on a few measurable pore structural features, and can be widely used in the petroleum and logging fields.
Article
Geochemistry & Geophysics
Mengsu Hu, Carl Steefel, Jonny Rutqvist
Summary: The study developed a new microscale mechanical-chemical model that showed sharp corners of mineral grains dominating the contact dynamics, microfracturing, and pressure solution in salt systems, thus influencing structural changes and porosity loss. The analysis revealed that pressure solution dissolved sharp corners and edges, leading to relatively high porosity loss, playing a crucial role in salt creep. Dynamic changes in salt granular systems involving grain relocation and pressure solution were identified as contributing factors to longer-term salt creep at larger scales.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2021)
Article
Engineering, Mechanical
Ji Lang, Qianqian Wang
Summary: This study fills the theoretical gap in the field of squeezing flow within a thin porous gap driven by a moving boundary by introducing Fourier transforms, considering porous media effects, and handling arbitrary moving boundaries. It provides a robust framework for research and development in the field of squeezing flow dynamics.
TRIBOLOGY INTERNATIONAL
(2024)
Article
Engineering, Mechanical
Shiwei Zhao, Hao Chen, Jidong Zhao
Summary: This paper introduces a hierarchical multiscale modeling paradigm for simulating freeze-thaw behavior in granular media. The approach combines a continuum-based mixture theory with a micromechanics-based homogenization technique, allowing for the simulation of freeze-thaw processes based on constitutive responses extracted from representative volume elements (RVEs) using the discrete element method (DEM). The proposed strategy bypasses the need for phenomenological thermo-mechanical constitutive models.
ACTA MECHANICA SINICA
(2023)
Article
Environmental Sciences
Gerardo Severino, Francesco De Paola
Summary: This study investigates the steady flow generated by an injecting and a pumping well in a porous formation with spatially variable hydraulic conductivity. The breakthrough curve (BTC) and its moments are computed to analyze the transportation of a solute. By adopting assumptions and simplifications, a simple analytical solution is obtained and the statistical properties of the travel time along the central trajectory are calculated. It is found that the spatial variability enhances dispersion of fluid particles, especially in the early arrivals.
WATER RESOURCES RESEARCH
(2022)
Article
Thermodynamics
Ashes Banerjee, Srinivas Pasupuleti, Koushik Mondal, M. Mousavi Nezhad
Summary: Modeling the relationship between volumetric flux and hydraulic head gradient in non-linear filtration is challenging due to uncertainties in characteristic length and velocity quantification. Machine learning algorithms, such as ANN, RF, and Boosted Tree, have shown to be effective in predicting the target variable. These methods perform well in predicting hydraulic head gradient accurately with significant accuracies for a wide range of data sources.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Review
Thermodynamics
Li Chen, An He, Jianlin Zhao, Qinjun Kang, Zeng-Yao Li, Jan Carmeliet, Naoki Shikazono, Wen-Quan Tao
Summary: This review summarizes the recent advances and challenges in pore-scale modeling, discussing its practical applications in geoscience, polymer exchange membrane fuel cells, and solid oxide fuel cells. Notable results from pore-scale modeling are presented, while the challenges facing the development of pore-scale models are also discussed.
PROGRESS IN ENERGY AND COMBUSTION SCIENCE
(2022)
Article
Mathematics, Applied
Ioana Ciotir, Dan Goreac, Ionut Munteanu
Summary: This paper aims to characterize the ability to maintain a stochastic coupled system with porous media components in a prescribed set of constraints by using internal controls. This property is proven by establishing a quasi-tangency local-in-time condition inspired by Euler approximation schemes. Specifically, by utilizing one of the components of the system as an asymptotic supervisor, conditions for the exponential asymptotic stabilizability of controlled porous media equations are provided.
JOURNAL OF EVOLUTION EQUATIONS
(2023)
Article
Engineering, Chemical
Muhammad Sahimi
Summary: Experiments, simulations, and models have shown that the dynamic permeability of porous media can be described by a universal function of the rescaled frequency, regardless of the morphology. Two approaches, the dynamic effective-medium approximation and critical-path analysis, both support the universality of the rescaled dynamic permeability in heterogeneous porous media. This has important implications for the electrical conductivity, formation factor, and diffusion coefficients of porous media.
TRANSPORT IN POROUS MEDIA
(2022)
Article
Thermodynamics
Yuqi Wu, Pejman Tahmasebi, Keyu Liu, Samuel Fagbemi, Chengyan Lin, Senyou An, Lihua Ren
Summary: Pore-scale fluid flow simulation on digital rocks is crucial for environmental remediation and geo-materials. This study presents a unified modeling approach for constructing multiscale digital images and simulating multiphase flow in complex and heterogeneous pore systems. By using a hybrid modeling method and non-uniform meshes, the computational efficiency of the simulations is improved.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Chemistry, Physical
Nasrin Torabi, Fatemeh Ebrahimi, G. R. Maktabdaran, Muhammad Sahimi
Summary: This article investigates the impact of nano-junctions on the rate of water transport in a nanostructured system. It reveals that the wall-water friction coefficient increases dramatically with roughness, but water flow in relatively complex nanochannels is still significantly enhanced.
JOURNAL OF MOLECULAR LIQUIDS
(2022)
Review
Engineering, Chemical
Muhammad Sahimi, Pejman Tahmasebi
Summary: This article discusses the development of quantum computer algorithms and their potential applications in geoscience. Despite the challenges that still need to be overcome, there are already intermediate-scale quantum computers available for various problems.
TRANSPORT IN POROUS MEDIA
(2022)
Article
Geochemistry & Geophysics
Xiaojun Chen, Luong Duy Thanh, Chengfei Luo, Pejman Tahmasebi, Jianchao Cai
Summary: The relationship between electrical conduction and pore structure in reservoir rocks was analyzed through theoretical development, petrophysical experiments, error analysis, core-scale displacement experiments, and pore-scale numerical simulations. The electric formation factor was found to be a function of porosity, tortuosity fractal dimension, and pore fractal dimension. The model provided satisfactory predictions for reservoir rocks when the ratio of minimum to maximum pore radius was suitable. Porosity-based formation factor models had high errors at high formation factors, but our model improved predictions with an error factor of +/- 10. Hydraulic and electrical conductions showed different dependencies on pore structure, with hydraulic conductance being influenced by pore size, dominant flow channels, and threshold pressure, while electrical conduction had no dominant channel and did not reflect pore size information at the same porosity.
Article
Engineering, Civil
Xiaojun Chen, Xiaobo Zhao, Pejman Tahmasebi, Chengfei Luo, Jianchao Cai
Summary: A data-driven model based on nuclear magnetic resonance (NMR) was developed to predict matrix permeability using nine machine learning models. The type of input data had a strong influence on the machine learning modeling. By using cumulative T2 relaxation data instead of the original T2 data, the gradient boosting decision tree model tuned by GridsearchCV showed a stronger agreement between experimental results and NMR estimates of matrix permeability. The correlation coefficient reached 0.92 with the lowest MSE of 0.12. Evaluation: 9 out of 10.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Tao Bai, Pejman Tahmasebi
Summary: In this study, a graph neural network (GNN) is used for accurate prediction of groundwater dynamics. The model incorporates spatial relationships between wells using graph convolution layers and temporal features using gated temporal convolutional networks. The proposed model outperforms two baseline models in terms of evaluation metrics, even when the spatial dependencies are unknown.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Chemical
Mehryar Amir Hosseini, Serveh Kamrava, Muhammad Sahimi, Pejman Tahmasebi
Summary: The wettability of porous media significantly impacts the spatial distribution of fluid phases. Computer simulations show that contact angle affects particle dynamics, fluid velocity, and rupture in the pore space. Additionally, increasing contact angle reduces inter-particle interactions and increases drag force, leading to larger particle displacement.
CHEMICAL ENGINEERING SCIENCE
(2023)
Article
Mechanics
Xiaoming Zhang, Pejman Tahmasebi
Summary: In this study, the DKT process of irregular particles was investigated numerically, and it was found that the particle shape plays an important role. Particles with low sphericity are more sensitive to orientation, and lower roundness accelerates the separation of particle pairs. The vertical velocity decreases when roundness or sphericity is smaller.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
(2023)
Article
Computer Science, Interdisciplinary Applications
Mehryar Amir Hosseini, Pejman Tahmasebi
Summary: This paper investigates the influence of particle morphology on granular collapse behavior and wave generation in multiphase fluid systems. The study establishes a clear relationship between particle morphology and important characteristics such as displacement, velocity, inter-particle forces, and kinetic energy. The findings demonstrate that as irregularity increases, interlocking between particles becomes more prominent, leading to reduced particle travel distances. Additionally, interlocking also influences particle-fluid interactions, resulting in significant alterations in the formation of generated waves.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Thermodynamics
Yuqi Wu, Pejman Tahmasebi, Keyu Liu, Chengyan Lin, Serveh Kamrava, Shengbiao Liu, Samuel Fagbemi, Chang Liu, Rukuai Chai, Senyou An
Summary: This study proposes a novel hybrid modeling approach integrating X-ray CT imaging technology, morphological operation algorithm, and quartet structure generation set method to investigate the dependence of the physical properties of hydrate-bearing sediments (HBS) on hydrate occurrence patterns and saturation levels. The findings suggest that different hydrate types have varying heterogeneity in the distribution of pore and throat radii.
Review
Energy & Fuels
Hossein Mirzaee, Serveh Kamrava, Pejman Tahmasebi
Summary: This article reviews the most promising studies in machine learning-assisted reconstruction of porous media, categorizing the approaches and discussing their characteristics, advantages, and disadvantages. It also provides information on various methods for evaluating algorithm performance. Furthermore, the article explores the current research status and challenges in ML-assisted porous media reconstruction in energy-related applications and suggests potential areas for future studies.
Review
Materials Science, Multidisciplinary
Pejman Tahmasebi
Summary: Modeling of heterogeneous materials and media plays a crucial role in various phenomena and systems, including condensed matter physics, soft materials, composite media, porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science, and space discoveries. This review paper examines recent developments in experimental and computational methods, such as neutron and nanometer-scale tomography, magnetic resonance imaging, digital image correlation, and 4D techniques. It also explores the shift towards micro-scale and the development of multiscale approaches in modeling, as well as the exploration of coupled or multiphysics systems.
PROGRESS IN MATERIALS SCIENCE
(2023)
Article
Physics, Fluids & Plasmas
Jinwoo Im, Felipe P. J. de Barros, Sami Masri, Muhammad Sahimi, Robert M. Ziff
Summary: With advancements in instrumentation and computational power, we now have access to large amounts of data for complex phenomena in macroscopically heterogeneous media. The traditional method of averaging equations over heterogeneity is no longer valid, leading to an open question of discovering governing equations for flow and transport processes. In this study, a data-driven approach using stochastic optimization and symbolic regression is proposed to discover these equations, which can be based on experimental data or microscopic simulation. As an example, the equation for anomalous diffusion on the critical percolation cluster is discovered and found to agree with previous proposals.
