Time‐Varying Fluid Injection Mechanism and Enhancing Wall Dilation for Improved Fluid Flow Performance: A Taguchi‐Based L ₁₆ Orthogonal Array Optimization

ABSTRACT Precise forecasting and regulation of heat transfer in porous slider configurations are crucial for enhancing the efficacy of lubricating systems, microscale fluidic devices, and cooling technologies. To achieve these, the present study inspects the unsteady three‐dimensional flow of a ternary nanofluid comprising graphene, carbon nanotubes, and aluminum oxide nanoparticles of various morphologies past a porous slider undergoing spatially varying expansion and contraction. The investigation introduces a novel spatial‐dependent, time‐varying fluid injection mechanism focused on improving and sustaining slider levitation performance. The nonlinear governing equations, based on fundamental assumptions, are reformulated into dimensionless form by using suitable similarity transformations. The resulting equations are numerically solved using the fourth‐fifth order Runge–Kutta method in combination with the shooting method. Moreover, a Taguchi optimization technique, integrated with orthogonal array is employed to optimize the heat transfer rate using the larger‐the‐better criterion. The outcomes demonstrate that slider expansion decreases lift, drag, and frictional forces, whereas contraction markedly improves these aerodynamic and resistive properties. The attenuation of nanofluid velocity distributions caused by wall dilation, in comparison to ternary fluid systems, enhances the operational efficiency of slider bearings across several working circumstances. The optimization analysis reveals that the Biot number is the predominant parameter, accounting for approximately 53.59% of the heat transfer rate, while the influence of temperature difference remains negligible at 6.99%.