A review on the utilized machine learning approaches for modeling the dynamic viscosity of nanofluids
M Ramezanizadeh, MH Ahmadi, MA Nazari… - … and Sustainable Energy …, 2019 - Elsevier
Nanofluids are broadly applied in energy systems such as solar collector, heat exchanger
and heat pipes. Dynamic viscosity of the nanofluids is among the most important features …
and heat pipes. Dynamic viscosity of the nanofluids is among the most important features …
Asphaltene induced changes in rheological properties: A review
AA Moud - Fuel, 2022 - Elsevier
Asphaltene is a component of crude oil that has been linked to serious production and
transportation issues. It is a solid oil component with various shapes and molecular …
transportation issues. It is a solid oil component with various shapes and molecular …
Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
[HTML][HTML] Improving the thermal efficiency of a solar flat plate collector using MWCNT-Fe3O4/water hybrid nanofluids and ensemble machine learning
Z Said, P Sharma, LS Sundar, C Li, DC Tran… - Case Studies in Thermal …, 2022 - Elsevier
The thermal performance of a flat plate solar collector using MWCNT+ Fe 3 O 4/Water hybrid
nanofluids was examined in this research. The flat plate solar collector was tested using …
nanofluids was examined in this research. The flat plate solar collector was tested using …
[HTML][HTML] Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm
Y Cao, E Kamrani, S Mirzaei, A Khandakar, B Vaferi - Energy Reports, 2022 - Elsevier
Abstract Photovoltaic/thermal (PV/T) are high-tech devices to transform solar radiation into
electrical and thermal energies. Nano-coolants are recently considered to enhance the …
electrical and thermal energies. Nano-coolants are recently considered to enhance the …
Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid
MH Ahmadi, B Mohseni-Gharyehsafa… - Journal of Thermal …, 2020 - Springer
Nanofluids are broadly employed in heat transfer mediums to enhance their efficiency and
heat transfer capacity. Thermophysical properties of nanofluids play a crucial role in their …
heat transfer capacity. Thermophysical properties of nanofluids play a crucial role in their …
Modeling of CO2 capture ability of [Bmim][BF4] ionic liquid using connectionist smart paradigms
The burning of fossil fuels produces large amounts of exhaust gases containing carbon
dioxide (CO 2). The emission of CO 2 into the atmosphere is widely known as the leading …
dioxide (CO 2). The emission of CO 2 into the atmosphere is widely known as the leading …
Thermophysical properties using ND/water nanofluids: An experimental study, ANFIS-based model and optimization
The research work was achieved to optimize the experimentally determined thermophysical
properties of water based nanodiamond nanofluids using the Adaptive network-based fuzzy …
properties of water based nanodiamond nanofluids using the Adaptive network-based fuzzy …
Application of hybrid artificial neural networks for predicting rate of penetration (ROP): A case study from Marun oil field
SB Ashrafi, M Anemangely, M Sabah… - Journal of petroleum …, 2019 - Elsevier
Rate of Penetration (ROP) can be considered as a crucial factor in optimization and cost
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …
Hydrogen solubility in aromatic/cyclic compounds: Prediction by different machine learning techniques
Y Jiang, G Zhang, J Wang, B Vaferi - International Journal of Hydrogen …, 2021 - Elsevier
A systematic procedure based on adaptive neuro-fuzzy inference systems (ANFIS), artificial
neural networks, and least-squares support vector machines develop to estimate hydrogen …
neural networks, and least-squares support vector machines develop to estimate hydrogen …