Search results

In the present article, sensitivity analysis was studied in the presence of the combined effects of thermal radiation, suction and magnetohydrodynamics (MHD) effects on a Nimonic 80A-Fe_3O4/water hybrid nanofluid across moving a wedge with variable surface temperature and buoyancy effects.

The governing equations were transformed using similarity transformations and solved using MATLAB bvp4c code and response surface methodology (RSM), with quadratic face-centred central composite design being implemented. All results and graphs were formulated after positive outcomes of our results with existing literature.

An increase in magnetic parameter (M) and velocity ratio parameter (R) resulted in an increase in velocity profiles and local Nusselt number, while a reverse trend was observed for temperature profiles. With radiation parameter Rd = 0.8, the local Nusselt number increased by 4.08% as the velocity ratio parameter increased from R = 0.0 to R = 0.5. The Nusselt number was found to be most sensitive to R, while the latter produced negative sensitivity on skin friction coefficient. The skin friction coefficient for the hybrid nanofluid model increased by 35.39% compared to the regular fluid model, with a very low standard deviation value of 10⁻⁴. The Model F-value for Nusselt number model was found to be 939278.49 with a noise ratio of 3618.711. Skin friction coefficient was found to be most sensitive with respect to changes in the parametric values of M.

Nimonic 80A being a super-alloy of nickel-iron-chromium and built in high frequency melting, it can work up to 1500°F and is extensively used in automobile exhaust valves.

The present study finds numerous applications in biotoxicity studies, medical industries, water heaters and the forging of hot exhaust valve heads.

In view of various applications of our present study, there remains a gap in examining the sensitivity analysis of a hybrid nanofluid flow model across a moving permeable wedge using the Tiwari–Das model, which required clinical investigations numerically and statistically.

This study aims to optimize heat transfer efficiency and minimize friction factor and entropy generation in hybrid nanofluid flows through porous media. By incorporating factors such as melting effect, buoyancy, viscous dissipation and no-slip velocity on a stretchable surface, the aim is to enhance overall performance. Additionally, sensitivity analysis using response surface methodology is used to evaluate the influence of key parameters on response functions.

After deriving suitable Lie-group transformations, the modeled equations are solved numerically using the “spectral local linearization method.” This approach is validated through rigorous numerical comparisons and error estimations, demonstrating strong alignment with prior studies.

The findings reveal that higher Darcy numbers and melting parameters are associated with decreased entropy (35.86% and 35.93%, respectively) and shear stress, increased heat transmission (16.4% and 30.41%, respectively) in hybrid nanofluids. Moreover, response surface methodology uses key factors, concerning the Nusselt number and shear stress as response variables in a quadratic model. Notably, the model exhibits exceptional accuracy with $R^2$ values of 99.99% for the Nusselt number and 100.00% for skin friction. Additionally, optimization results demonstrate a notable sensitivity to the key parameters.

Lubrication is a vital method to minimize friction and wear in the automobile sector, contributing significantly to energy efficiency, environmental conservation and carbon reduction. The incorporation of nickel and manganese zinc ferrites into SAE 20 W-40 motor oil lubricants, as defined by the Society of Automotive Engineers, significantly improves their performance, particularly in terms of tribological attributes.

This work stands out for its focus on applications such as hybrid electromagnetic fuel cells and nano-magnetic material processing. While these applications are gaining interest, there is still a research gap regarding the effects of melting on heat transfer in a NiZnFe_2O_4-MnZnFe_2O_4/20W40 motor oil hybrid nanofluid over a stretchable surface, necessitating a thorough investigation that includes both numerical simulations and statistical analysis.

This study aims to enhance heat transfer efficiency while minimizing friction factor and entropy generation in the flow of Nickel zinc ferrite (NiZnFe₂O₄) nanoparticles suspended in multigrade 20W-40 motor oil (as specified by the Society of Automotive Engineers). The investigation focuses on the effects of the melting process, nonspherical particle shapes, thermal dispersion and viscous dissipation on the nanofluid flow.

The fundamental governing equations are transformed into a set of similarity equations using Lie group transformations. The resulting set of equations is numerically solved using the spectral local linearization method. Additionally, sensitivity analysis using response surface methodology (RSM) is conducted to evaluate the influence of key parameters on response function.

Higher dispersion reduces entropy production. Needle-shaped particles significantly enhance heat transfer by 27.65% with melting and reduce entropy generation by 45.32%. Increasing the Darcy number results in a reduction of friction by 16.06%, lower entropy by 31.72% and an increase in heat transfer by 17.26%. The Nusselt number is highly sensitive to thermal dispersion across melting and varying volume fraction parameters.

This study addresses a significant research gap by exploring the combined effects of melting, particle shapes and thermal dispersion on nanofluid flow, which has not been thoroughly investigated before. The focus on practical applications such as fuel cells, material processing, biomedicine and various cooling systems underscores its relevance to sectors such as nuclear reactors, tumor treatments and manufacturing. The incorporation of RSM for friction factor analysis introduces a unique dimension to the research, offering novel insights into optimizing nanofluid performance under diverse conditions.