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 …

[HTML][HTML] Optimization and analysis of bioenergy production using machine learning modeling: Multi-layer perceptron, Gaussian processes regression, K-nearest …

H Jin, YG Kim, Z Jin, AA Rushchitc, AS Al-Shati - Energy Reports, 2022 - Elsevier
Since fossil fuels are slowly depleting, bio and renewable energies are now given more
attention. The main purpose of this research is to investigate and optimize the influencing …

Investigation of effective parameters on relative thermal conductivity of SWCNT (15%)-Fe3O4 (85%)/water hybrid ferro-nanofluid and presenting a new correlation with …

S Alidoust, F AmoozadKhalili, S Hamedi - Colloids and Surfaces A …, 2022 - Elsevier
In this study, the parameters affecting the relative thermal conductivity (RTC) of SWCNT
(15%)-Fe 3 O 4 (85%)/Water Hybrid Ferro-Nanofluid (HFNF) are investigated. The …

Thermal conductivity prediction of nano enhanced phase change materials: a comparative machine learning approach

F Jaliliantabar - Journal of Energy Storage, 2022 - Elsevier
Thermal conductivity is one of the crucial properties of nano enhanced phase change
materials (NEPCM). Then, in this study three different machine learning methods namely …

Experimental and artificial neural network based study on the heat transfer and flow performance of ZnO-EG/water nanofluid in a mini-channel with serrated fins

T Wen, G Zhu, L Lu - International Journal of Thermal Sciences, 2021 - Elsevier
The adoptions of mini-channel and nanofluid are potential technologies to improve the heat
transfer capability. The present study experimentally investigated the flow and thermal …

An overview of vapor compression refrigeration system performance enhancement mechanism by utilizing nanolubricants

A Nugroho, R Mamat, Z Bo, WH Azmi, R Alenezi… - Journal of Thermal …, 2022 - Springer
Nanolubricants are dispersed nano-scales solid particles in a base fluid. Due to high
demand for higher efficiency in thermal application systems, nanolubricants is an ideal …

[HTML][HTML] Appropriate budget contingency determination for construction projects: State-of-the-art

T Ammar, M Abdel-Monem, K El-Dash - Alexandria Engineering Journal, 2023 - Elsevier
Contingency is a critical component in the cost estimation process for any construction
project. The contingency reserve considers potential costs related to risks and uncertainties …

Optimization of 2024-T3 aluminum alloy friction stir welding using random forest, XGBoost, and MLP machine learning techniques

P Myśliwiec, A Kubit, P Szawara - Materials, 2024 - mdpi.com
This study optimized friction stir welding (FSW) parameters for 1.6 mm thick 2024T3
aluminum alloy sheets. A 3× 3 factorial design was employed to explore tool rotation speeds …

[图书][B] Nano Enhanced Phase Change Materials: Preparation, Properties and Applications

Z Said, AK Pandey - 2023 - books.google.com
This book provides information on thermal energy storage systems incorporating phase
change materials (PCMs) which are widely preferred owing to their immense energy storage …

Artificial neural network technique for estimating the thermo-physical properties of water-alumina nanofluid

S Ravi Babu, KPV Krishna Varma… - Ecological Engineering …, 2022 - yadda.icm.edu.pl
With its superior thermo-physical characteristics to the carrier fluid, nanofluid is the most
impactful heat transfer fluid. Thermal conductivity, density, viscosity, specific heat, coefficient …