Thermal investigation and physiochemical interaction of H₂O and C₂H₆O₂ saturated by Al₂O₃ and γAl₂O₃ nanomaterials

Abstract

Applications: The interaction of nanoparticles and base solvents of different nature attained much interest of the researchers in the recent time. These use in medication, detection of cancer cells, applied thermal engineering, and electrical and mechanical engineering. Among the broad range of applications, investigation of nanofluid through converging/diverging channel is important which is of much interest in the field of medical sciences. Purpose and methodology: The core purpose of this study is to introduce a new heat transfer model for two natures of nanofluids with bi host solvents. The model in hand achieved through nanofluid expressions, similarity equations and induction of novel dissipation effects. At later stage, numerical treatment is performed to explore the actual behaviour of nanofluids inside the oblique walls which is very important. Core findings: From the drawn results, it is found that the motion could be controlled by expanding the channel walls ([Formula: see text]) and high Re and in Al2O3-H2O it is optimum. The nanofluids based on Al2O3 and C2H6O2 have much ability to transmit heat than the other nanofluids. Moreover, dissipation effects ([Formula: see text]) played significant role and boosted the temperature while keeping [Formula: see text] and [Formula: see text], respectively. Also, the study is validated and achieved good agreement between existing and the current study.

Numerical analysis of thermal improvement in hydrogen‐based host fluids under buoyancy force and EPNM effects: Study for vertical cylinder

“…where 𝜁 is the solid volume fraction of nanoparticles and γAO indicates aluminum oxide nanoparticles, "W" stands for water and "EG" is ethylene glycol [44]. Dynamic viscosity…”

“…$$$$\begin{equation*} {\rho }_{nf} = \left( {1 - \zeta } \right) {\rho }_f + \zeta {\rho }_s, {\left( {\rho {C}_p} \right)}_{nf} = \left( {1 - \zeta } \right) {\left( {\rho {C}_p} \right)}_f + \zeta {\left( {\rho {C}_p} \right)}_s,\end{equation*}$$$$ $$$$\begin{equation}{\left( {\rho \beta } \right)}_{nf} = \left( {1 - \zeta } \right) {\left( {\rho \beta } \right)}_f + \zeta {\left( {\rho \beta } \right)}_s\end{equation}$$$$where $$\zeta $$ is the solid volume fraction of nanoparticles and γAO indicates aluminum oxide nanoparticles, “ W ” stands for water and “ EG ” is ethylene glycol [44].…”

Analytical Study of (Ag–Graphene)/Blood Hybrid Nanofluid Influenced by (Platelets-Cylindrical)nanoparticles and Joule Heating via VIM

“…In 2022, Indumathi et al examined a hybrid nanofluid with a permeable surface under the suction and injection process. The results of the physical model showed that increasing the number of nanoparticles in the basic fluid will result in a decrease in the velocity of hybrid nanofluids. − In 2022, Mburu et al investigated the unsteady, two-dimensional, viscous, and incompressible flow of the boundary layer of an electrically conducting nanofluid through porous plates. Bivariate spectral quasilinearization (BSQL) was used for the model study.…”

Energy transfer in Carreau Yasuda liquid influenced by engine oil with Magnetic dipole using tri-hybrid nanoparticles

“…As a result, using TiO 2 particles yielded the highest energy conversion efficiency (35.67%). Alharbi et al 28 – 30 created a nanofluid model with TiO 2 in the base fluid within a squeezing/dilating channel, which included nanoparticle accumulation effects and nonlinear thermal radiations. The outcome confirmed that the fluid mobility is substantially controlled by the high viscosity variation caused by nanomaterials aggregation.…”