Optimizing pressure gradient on the MHD peristaltic blood flow of nanofluids by - response surface methodology

This study focuses on optimization of pressure gradient on MHD peristaltic nanofluid flow by response surface methodology (RSM). The governing equations, including continuity, motion, nanoparticle, and concentration force are solved by disregarding inertial forces and employing the approximation of long-wavelength. The perturbation method is used to solve the resultant nonlinear coupled partial differential equation analytically. Mathematical and graphical outputs for concentration, temperature, and pressure rise, considering all physical parameters, are presented. Numerical computation is applied to assess expressions for friction forces and pressure rise. Magnetohydrodynamics has various applications in various microchannel designs for efficacious flow control in pumping fluids for both pulsating and non-pulsating continuous flow. Finally, Response Surface Methodology (RSM) is used for performing sensitivity analysis and its optimization. ANOVA tables are generated with the help of MINITAB-19 which is a statistical software. The sensitivity results are displayed in tabular and graphical form and concluded that M is more sensitive than other input parameters for $\Delta P$at the low level and the input parameter Nt is most sensitive among others at middle and high levels. Further, Temperature and pressure of the flow has different responses for various values of magnetic, thermophoresis and Brownian motion parameter.