nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling

M Mahmoudabadbozchelou, GE Karniadakis, S Jamali - Soft Matter, 2022 - pubs.rsc.org
Time-and rate-dependent material functions in non-Newtonian fluids in response to different
deformation fields pose a challenge in integrating different constitutive models into …

[HTML][HTML] Heat transport and nonlinear mixed convective nanomaterial slip flow of Walter-B fluid containing gyrotactic microorganisms

MI Khan, F Alzahrani, A Hobiny - Alexandria Engineering Journal, 2020 - Elsevier
Here nonlinear mixed convective nanoliquid slip flow of Walter-B fluid is addressed subject
to stretched surface with gyrotactic microorganisms. The flow is generated via nonlinear …

On the evaluation of thermal conductivity of nanofluids using advanced intelligent models

A Hemmati-Sarapardeh, A Varamesh, MN Amar… - … Communications in Heat …, 2020 - Elsevier
Accurate knowledge of thermal conductivity (TC) of nanofluids is emphasized in studies
related to the thermophysical aspects of nanofluids. In this work, a comprehensive review of …

CO2 geological sequestration in heterogeneous binary media: Effects of geological and operational conditions

R Ershadnia, CD Wallace… - Advances in Geo …, 2020 - ager.yandypress.com
Realistic representation of subsurface heterogeneity is essential to better understand and
effectively predict the migration and trap** patterns of carbon dioxide (CO2) during …

Modeling of methane adsorption capacity in shale gas formations using white-box supervised machine learning techniques

MN Amar, A Larestani, Q Lv, T Zhou… - Journal of Petroleum …, 2022 - Elsevier
Energy demand is increasing worldwide and shale gas formations have gained increasing
attention and have become crucial energy sources. Therefore, accurate determination of …

Predicting formation damage of oil fields due to mineral scaling during water-flooding operations: Gradient boosting decision tree and cascade-forward back …

A Larestani, SP Mousavi, F Hadavimoghaddam… - Journal of Petroleum …, 2022 - Elsevier
Water-flooding is one of the main options employed by the oil industry to meet the world's
ever-increasing demand for oil, as the primary source of energy. This approach is highly …

Application of advanced correlative approaches to modeling hydrogen solubility in hydrocarbon fuels

F Hadavimoghaddam, S Ansari, S Atashrouz… - International Journal of …, 2023 - Elsevier
In petroleum and petrochemical refineries, having precise knowledge regarding H 2
solubility in hydrocarbon fuels and feedstocks is critical. In this study, the hydrogen solubility …

Prediction of pressure in different two-phase flow conditions: machine learning applications

E Khamehchi, A Bemani - Measurement, 2021 - Elsevier
The accurate prediction of pressure has extensive applications in the petroleum industry,
especially in the optimization of continuous field production, quantifying reservoir …

Modeling interfacial tension of methane-brine systems at high pressure and high salinity conditions

H Mehrjoo, M Riazi, MN Amar… - Journal of the Taiwan …, 2020 - Elsevier
Natural gas which consists mainly of methane (usually more than 90% in volume), is
becoming increasingly an important and efficient source of energy because of the lower …

Experimental measurement and compositional modeling of crude oil viscosity at reservoir conditions

M Talebkeikhah, MN Amar, A Naseri, M Humand… - Journal of the Taiwan …, 2020 - Elsevier
In the present study, experimental and modeling investigations were performed and
combined to implement trustworthy paradigms to predict the viscosity value under different …