Pore structure evolution of Qingshankou shale (kerogen type I) during artificial maturation via hydrous and anhydrous pyrolysis: Experimental study and intelligent …
B Liu, MR Mohammadi, Z Ma, L Bai, L Wang, Y Xu… - Energy, 2023 - Elsevier
In this study, alterations in the pore structure of the Qingshankou shale during hydrous and
anhydrous pyrolysis (HP and AHP) over wide ranges of temperature (300–450° C) were …
anhydrous pyrolysis (HP and AHP) over wide ranges of temperature (300–450° C) were …
Modeling interfacial tension of surfactant–hydrocarbon systems using robust tree-based machine learning algorithms
A Rashidi-Khaniabadi, E Rashidi-Khaniabadi… - Scientific Reports, 2023 - nature.com
Interfacial tension (IFT) between surfactants and hydrocarbon is one of the important
parameters in petroleum engineering to have a successful enhanced oil recovery (EOR) …
parameters in petroleum engineering to have a successful enhanced oil recovery (EOR) …
Prediction of hydrogen solubility in aqueous solutions: Comparison of equations of state and advanced machine learning-metaheuristic approaches
Hydrogen is the primary carrier of renewable energy stored underground. Understanding
the solubility of hydrogen in water is critical for subsurface storage. Accurately measuring the …
the solubility of hydrogen in water is critical for subsurface storage. Accurately measuring the …
Modelling CO2 diffusion coefficient in heavy crude oils and bitumen using extreme gradient boosting and Gaussian process regression
Q Lv, A Rashidi-Khaniabadi, R Zheng, T Zhou… - Energy, 2023 - Elsevier
In this work, five machine learning models based on Gaussian process regression (GPR)
and Extreme gradient boosting (XGBoost) were developed for estimating the diffusion …
and Extreme gradient boosting (XGBoost) were developed for estimating the diffusion …
Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state
Abstract Knowledge of the solubilities of hydrocarbon components of natural gas in pure
water and aqueous electrolyte solutions is important in terms of engineering designs and …
water and aqueous electrolyte solutions is important in terms of engineering designs and …
Experimental measurement and modeling of asphaltene adsorption onto iron oxide and lime nanoparticles in the presence and absence of water
Asphaltene precipitation and its adsorption on different surfaces are challenging topics in
the upstream and downstream of the oil industries and the environment. In this research, the …
the upstream and downstream of the oil industries and the environment. In this research, the …
[HTML][HTML] Hydrogen solubility in different chemicals: A modelling approach and review of literature data
P Foroughizadeh, A Shokrollahi, A Tatar… - … Applications of Artificial …, 2024 - Elsevier
Hydrogen (H 2) solubility is a crucial parameter for industrial processes. This study utilises
various Machine Learning (ML) techniques, including Decision Tree (DT), Multilayer …
various Machine Learning (ML) techniques, including Decision Tree (DT), Multilayer …
Data-driven modeling of H2 solubility in hydrocarbons using white-box approaches
F Hadavimoghaddam, MR Mohammadi… - International Journal of …, 2022 - Elsevier
As a result of technological advancements, reliable calculation of hydrogen (H 2) solubility in
diverse hydrocarbons is now required for the design and efficient operation of processes in …
diverse hydrocarbons is now required for the design and efficient operation of processes in …
Toward predicting SO2 solubility in ionic liquids utilizing soft computing approaches and equations of state
MR Mohammadi, F Hadavimoghaddam… - Journal of the Taiwan …, 2022 - Elsevier
Background The use of novel and green solvents like ionic liquids (ILs) for the capture of air
pollutant gases has gained extensive attention in recent years. However, getting reliable …
pollutant gases has gained extensive attention in recent years. However, getting reliable …
Toward predicting thermal conductivity of hybrid nanofluids: Application of a committee of robust neural networks, theoretical, and empirical models
H Ghadery-Fahliyany, S Ansari, MR Mohammadi… - Powder Technology, 2024 - Elsevier
In this work, three optimized intelligent models on the basis of multilayer perceptron (MLP),
two radial basis function (RBF) models (including RBF-particle swarm optimization (PSO) …
two radial basis function (RBF) models (including RBF-particle swarm optimization (PSO) …