Recent progress of artificial intelligence for liquid-vapor phase change heat transfer

Y Suh, A Chandramowlishwaran, Y Won - npj Computational Materials, 2024‏ - nature.com
Artificial intelligence (AI) is shifting the paradigm of two-phase heat transfer research. Recent
innovations in AI and machine learning uniquely offer the potential for collecting new types …

Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system

P Sharma, Z Said, A Kumar, S Nizetic, A Pandey… - Energy & …, 2022‏ - ACS Publications
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 …

Performance characterization of a solar-powered shell and tube heat exchanger utilizing MWCNTs/water-based nanofluids: an experimental, numerical, and artificial …

Z Said, S Rahman, P Sharma, AA Hachicha… - Applied Thermal …, 2022‏ - Elsevier
In the present work, Multi-Wall Carbon Nanotubes (MWCNT)/water nanofluids are used to
increase the performance of a shell and tube heat exchanger (STHX) while reducing energy …

Examining rheological behavior of MWCNT-TiO2/5W40 hybrid nanofluid based on experiments and RSM/ANN modeling

YM Chu, M Ibrahim, T Saeed, AS Berrouk… - Journal of Molecular …, 2021‏ - Elsevier
In this study, the rheological behavior of MWCNT-TiO 2/5W40 hybrid nanofluid was
examined experimentally and then the results were compared with regression-based …

Sonication impact on thermal conductivity of f-MWCNT nanofluids using XGBoost and Gaussian process regression

Z Said, P Sharma, BJ Bora, AK Pandey - Journal of the Taiwan Institute of …, 2023‏ - Elsevier
Background Previous research has revealed that nanofluids are capable of improving the
heat transfer performance of energy systems. Researchers devote a considerable deal of …

An experimental investigation of thermal conductivity and dynamic viscosity of Al2O3-ZnO-Fe3O4 ternary hybrid nanofluid and development of machine learning …

H Adun, D Kavaz, M Dagbasi, H Umar, I Wole-Osho - Powder Technology, 2021‏ - Elsevier
The growing interest in hybrid nanofluids is due to the synergistic effects of nanoparticles,
which could give them better heat transfer properties as compared to base fluids, and …

An experimental comparative assessment of the energy and exergy efficacy of a ternary nanofluid-based photovoltaic/thermal system equipped with a sheet-and …

AN Abdalla, A Shahsavar - Journal of Cleaner Production, 2023‏ - Elsevier
The usability of water based GO-TiO 2-Fe 3 O 4 ternary nanofluid in a photovoltaic/thermal
(PV/T) collector from both energy and exergy perspectives is inspected in the present …

Deep machine learning potentials for multicomponent metallic melts: Development, predictability and compositional transferability

RE Ryltsev, NM Chtchelkatchev - Journal of Molecular Liquids, 2022‏ - Elsevier
The use of machine learning interatomic potentials (MLIPs) in simulations of materials is a
state-of-the-art approach, which allows achieving nearly ab initio accuracy with orders of …

[HTML][HTML] Performance of magnetic dipole contribution on electromagnetic Ellis tetra hybrid nanofluid with the applications of surface tension gradient: A Xue model …

M Abbas, R Marzouki, HFM Ameen, A Dilsora… - International Journal of …, 2024‏ - Elsevier
The objective of this work is to examine the enhancement of thermal energy transfer in Ellis
THNF (tetra hybrid nanofluid) flow with magnetic dipole permits on a vertical surface. Using …