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 …

Optimization of thermophysical properties of nanofluids using a hybrid procedure based on machine learning, multi-objective optimization, and multi-criteria decision …

T Zhang, AMK Pasha, SM Sajadi, DJ Jasim… - Chemical Engineering …, 2024 - Elsevier
The rheological and thermal behavior of nanofluids in real-world scenarios is significantly
affected by their thermophysical properties (TPPs). Therefore, optimizing TPPs can …

The Applications and Challenges of Nanofluids as Coolants in Data Centers: A Review

L Sun, J Geng, K Dong, Q Sun - Energies, 2024 - mdpi.com
With the rapid development of artificial intelligence, cloud computing and other technologies,
data centers have become vital facilities. In the construction and operation of data centers …

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 …

Thermal conductivity of hydraulic oil-GO/Fe3O4/TiO2 ternary hybrid nanofluid: experimental study, RSM analysis, and development of optimized GPR model

A Shahsavar, M Sepehrnia, H Maleki… - Journal of Molecular …, 2023 - Elsevier
In the present paper, the thermal conductivity (TC) of a hydraulic oil-based nanofluid in the
presence of ternary nano-additives, graphene oxide (GO), iron oxide (Fe 3 O 4), and titanium …

Simulation of seepage flow through embankment dam by using a novel extended Kalman filter based neural network paradigm: Case study of Fontaine Gazelles Dam …

I Rehamnia, B Benlaoukli, M Jamei, M Karbasi, A Malik - Measurement, 2021 - Elsevier
Seepage flow through embankment dam is one of the most influential factors in failures of
them. Thus, the monitoring and accurate measuring of seepage are crucial for the safety and …

Machine learning methods for modeling nanofluid flows: a comprehensive review with emphasis on compact heat transfer devices for electronic device cooling

MS Abhijith, KP Soman - Journal of Thermal Analysis and Calorimetry, 2024 - Springer
A review of studies involving machine learning-based modeling of nanofluid flows with a
specific focus on their utilization in compact heat transfer devices for electronic device …

Assessment of scouring around spur dike in cohesive sediment mixtures: A comparative study on three rigorous machine learning models

M Pandey, M Jamei, I Ahmadianfar, M Karbasi… - Journal of …, 2022 - Elsevier
Spur dike has been widely used as one of the river training structures to increase the
stability of riverbanks and embankments. Scour around spur dikes affects their hydraulic …

Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

Y Shang, KA Hammoodi, A Alizadeh, K Sharma… - Journal of the Taiwan …, 2024 - Elsevier
Background The critical role of thermal conductivity (TC) as a significant thermo-physical
property in MXene/graphene-based nanofluids for photovoltaic/thermal systems has …

Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods

M Jamei, M Karbasi, IA Olumegbon… - Journal of Molecular …, 2021 - Elsevier
The quantitative determination of specific heat capacity (SHC) of molten (nitrate) salt-based
nanofluids helps to control the start-up heat and prevent overheating when deployed as a …