Insights into the thermodynamic efficiency of Homann-Agrawal hybrid nanofluid flow

Sarfraz, Mahnoor; Khan, Masood; Al-Zubaidi, A.; Saleem, S.

doi:10.1016/j.aej.2023.09.074

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…In essence, the situation is like an electrical jerk that encourages charged particles to flow in a fluid near the charged surface. Sarfraz et al (2023a, 2023b) conducted a thorough examination of the tribological effects induced by a ternary hybrid nanofluid on an inclined stretching surface. Buie et al (2006) focused on the development and performance assessment of a minimal direct methanol fuel cell that incorporates an electroosmotic pump for delivering methanol.…”

Section: Introductionmentioning

confidence: 99%

“…Peristaltic plays a very important role in fluid transport of bodily fluids and finds important applications in several biological and biomedical contexts, including small intestine, lymph, esophagus, finger pumps and heart-lung machines, by various scholars, such as Mishra and Ramachandra Rao (2003), Ali et al (2007), Makinde and Mhone (2005), Reddy et al (2007), Kothandapani and Srinivas (2008). Othman et al (2020), Sarfraz et al (2023a, 2023b) and Sarfraz and Khan (2024) highlighted recent research endeavors that explored hybrid nanofluids and their magnetic implications. These studies delve into the intricate interplay between magnetic fields and nanofluid properties, shedding light on potential applications and novel phenomena in this field.…”

Section: Introductionmentioning

confidence: 99%

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AI based optimal analysis of electro-osmotic peristaltic motion of non-Newtonian fluid with chemical reaction using artificial neural networks and response surface methodology

Zeeshan,

Asghar,

Rehaman

2024

HFF

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Purpose The present work is devoted to investigating the sensitivity analysis of the electroosmotic peristaltic motion of non-Newtonian Casson fluid with the effect of the chemical reaction and magnetohydrodynamics through the porous medium. The main focus is on flow efficiency quantities such as pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. This initiative is to bridge the existing gap in the available literature. Design/methodology/approach The governing equations of the problem are mathematically formulated and subsequently simplified for sensitivity analysis under the assumptions of a long wavelength and a small Reynolds number. The simplified equations take the form of coupled nonlinear differential equations, which are solved using the built-in Matlab routine bvp4c. The response surface methodology and artificial neural networks are used to develop the empirical model for pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. Findings The empirical model demonstrates an excellent fit with a coefficient of determination reaching 100% for responses, frictional forces on the upper wall and frictional forces on the lower wall and 99.99% for response, for pressure rise per wavelength. It is revealed through the sensitivity analysis that pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall are most sensitive to the permeability parameter at all levels. Originality/value The objective of this study is to use artificial neural networks simulation and analyze the sensitivity of electroosmotic peristaltic motion of non-Newtonian fluid with the effect of chemical reaction.

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Section: Introductionmentioning

confidence: 99%