NUMERICAL ANALYSIS OF DUSTY HYBRID NANOFLUID FLOW IN A POROUS MEDIUM UNDER LTNE CONDITIONS IN THE IMPACTS OF THERMOPHORESIS AND GRAVITY-BUOYANCY FORCES

The present study numerically investigates the flow and heat transfer behaviors of a dusty hybrid nanofluid over a stretchable surface embedded within a porous medium, taking account of the local thermal nonequilibrium (LTNE) approach along with the thermophoresis and gravitation-buoyancy effects. The transformation of the partial differential equations into ordinary differential equations is performed through a similarity transformation and subsequently solved using the Runge-Kutta-Fehlberg scheme with a shooting technique. The outcomes demonstrate the effects of various parameters on velocity and temperature profiles for the hybrid nanofluid, solid-matrix, and dust phases. The analysis of momentum and thermal boundary layer clarifies the interactions between these three phases in the influence of LTNE. It is found that with high values of both β_vand β_Tthe velocity and temperature distributions for the hybrid nanofluid and dust particle phases become nearly identical. Adding multi-walled carbon nanotube iron oxide (MWCNT-Fe₃O₄) nanoparticles enhances the momentum boundary layer thickness and temperature for all phases. The findings show that an enhancement in the parameters K_pand ϵ, which represent porous medium characteristics, significantly influences the density of the dust particle phase, leading to its elevation. Moreover, this research provides clear insights into the crucial influences of thermophoresis (F_T) and gravity-buoyancy (F_gb) forces on the behavior of the dust phase. It is revealed that the F_Tforce exhibits greater effectiveness in smaller dust particles with elevated β_vvalues, and the F_gbforce has distinct effects at low and high ω values. This study investigates the interactions among the three phases, emphasizing the critical influence of LTNE, F_Tand F_gbforces on the dust phase. Incorporating these effects in specific applications contributes to achieving more precise and reliable results.