Processes, models and the influencing factors for enhanced boiling heat transfer in porous structures

N Xu, Z Liu, X Yu, J Gao, H Chu - Renewable and Sustainable Energy …, 2024 - Elsevier
In order to understand the effect of porous structures on boiling heat transfer, this review
investigates and evaluates the preparation methods, critical heat fluxes and heat transfer …

Nanobiolubricant grinding: a comprehensive review

YX Song, CH Li, ZM Zhou, B Liu, S Sharma… - Advances in …, 2024 - Springer
Minimum quantity lubrication (MQL), which considers the cost, sustainability, flexibility, and
quality, has been actively explored by scholars. Nanoadditive phases have been widely …

An efficient investigation and machine learning-based prediction of decolorization of wastewater by using zeolite catalyst in electro-Fenton reaction

A El Jery, M Aldrdery, UR Shirode, JCO Gavilán… - Catalysts, 2023 - mdpi.com
The shortage of water resources has caused extensive research to be conducted in this field
to develop effective, rapid, and affordable wastewater treatment methods. For the treatment …

A novel experimental and machine learning model to remove COD in a batch reactor equipped with microalgae

AE Jery, A Noreen, M Isam, JL Arias-Gonzáles… - Applied Water …, 2023 - Springer
By using microorganisms and the microalgae Chlorella vulgaris in conjunction with
sequencing batch reactors (SBRs), the performance of a wastewater treatment facility was …

Thermodynamics Investigation and artificial neural network prediction of energy, exergy, and hydrogen production from a solar thermochemical plant using a polymer …

A El Jery, HM Salman, RM Al-Khafaji, MF Nassar… - Molecules, 2023 - mdpi.com
Hydrogen production using polymer membrane electrolyzers is an effective and valuable
way of generating an environmentally friendly energy source. Hydrogen and oxygen …

[HTML][HTML] Proposing empirical correlations and optimization of Nu and Sgen of nanofluids in channels and predicting them using artificial neural network

A El Jery, AA Ramírez-Coronel, JCO Gavilán… - Case Studies in Thermal …, 2023 - Elsevier
Getting the best performance from a thermal system requires two fundamental analyses,
energy and entropy generation. An ideal mechanism has the highest Nu and the lowest …

Sustainable heat transfer management: modeling of entropy generation minimization and Nusselt number development in internal flows with various shapes of cross …

AE Jery, P Satishkumar, M Abdul Jaleel Maktoof… - Water, 2022 - mdpi.com
In order to achieve the best performance of a thermal system, two major analyses must be
carried out on the system: energy and entropy generation. The best scenario is a …

A machine learning based approach for predicting Pool boiling heat transfer coefficient of CNT+ GO nanoparticle coated surfaces

R Kumar, S Dubey, D Sen, SK Mandal - International Communications in …, 2024 - Elsevier
The use of machine learning in the field of thermal engineering not only enhance the
accuracy of predictions but also allows the investigation of parametric effects and the …

Analysis and numerical simulation of pool boiling heat transfer in porous medium combined with 2D MCFC composite structure

Y Kang, Z Lang, G Wu, Y Wang, Y Wang - … Journal of Heat and Fluid Flow, 2024 - Elsevier
As the issue of energy becomes increasingly prominent, the field of heat dissipation
necessitates more advanced thermal energy utilization technologies. Pool boiling is …

Experimental and numerical simulation of the effect of free particles dispersed within microchannels on pool boiling heat transfer

M OuYang, Z Lang, X Xu, Y Kang, G Wu… - International Journal of …, 2024 - Elsevier
Pool boiling represents an efficient method of heat transfer. In this experiment, porous media
with microchannels are prepared using the high-temperature sintering method for copper …