Microchannel heat sinks with nanofluids for cooling electronic components: Performance enhancement, challenges, and limitations
Nowadays, the cooling of electronic components that are widely spread globally is
considered a critical issue. Designers and engineers alike confront major obstacles in …
considered a critical issue. Designers and engineers alike confront major obstacles in …
On the evaluation of the viscosity of nanofluid systems: Modeling and data assessment
A Hemmati-Sarapardeh, A Varamesh… - … and Sustainable Energy …, 2018 - Elsevier
Viscosity of nanofluids can significantly affect pumping power, pressure drop, workability of
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …
[HTML][HTML] Nanofluids in solar thermal collectors: review and limitations
Solar thermal collectors are systems that allow for the use of solar energy in thermal
applications. These collectors utilize a heat transfer fluid to transport absorbed solar …
applications. These collectors utilize a heat transfer fluid to transport absorbed solar …
[HTML][HTML] Intensification of heat exchanger performance utilizing nanofluids
HM Maghrabie, K Elsaid, ET Sayed… - International Journal of …, 2021 - Elsevier
Heat exchangers are widely utilized in different thermal systems for diverse industrial
aspects. The selection of HEx depends on the thermal efficiency, operating load, size …
aspects. The selection of HEx depends on the thermal efficiency, operating load, size …
Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid
This paper focuses on designing an artificial neural network which can predict thermal
conductivity and dynamic viscosity of ferromagnetic nanofluids from input experimental data …
conductivity and dynamic viscosity of ferromagnetic nanofluids from input experimental data …
Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network
In this paper, at first, a new correlation was proposed to predict the relative viscosity of
MWCNTs-SiO 2/AE40 nano-lubricant using experimental data. Then, considering minimum …
MWCNTs-SiO 2/AE40 nano-lubricant using experimental data. Then, considering minimum …
Prediction of thermal conductivity of various nanofluids using artificial neural network
E Ahmadloo, S Azizi - International Communications in Heat and Mass …, 2016 - Elsevier
This paper presents a 5-input artificial neural network (ANN) model for the prediction of the
thermal conductivity ratio of nanofluids to the base fluid (k nf/kf) of various nanofluids based …
thermal conductivity ratio of nanofluids to the base fluid (k nf/kf) of various nanofluids based …
Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods
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 …
nanofluids helps to control the start-up heat and prevent overheating when deployed as a …
Artificial intelligence in the field of nanofluids: A review on applications and potential future directions
Artificial Intelligence (AI) algorithms are becoming beneficial as substitute methods to
conventional approaches or as components of incorporated systems. They have been …
conventional approaches or as components of incorporated systems. They have been …
Predicting the viscosity of multi-walled carbon nanotubes/water nanofluid by developing an optimal artificial neural network based on experimental data
Regarding the viscosity of the fluids which is an imperative parameter for calculating the
required pumping power and convective heat transfer, based on experimental data, an …
required pumping power and convective heat transfer, based on experimental data, an …