Parametric sensitivity analysis using RSM of axisymitric flow through a permeable tube

The heat and mass transfer of a stretched permeable cylinder is a core process in a broad range of complex engineering applications, such as the production of polymer fibers, the design of high-performance heat exchangers and localized drug delivery concepts. It is critical to understand which parameters have the strongest impact on the rates of heat and mass transfer to optimize performance and control the process correctly. This paper will provide a parametric sensitivity analysis of axisymmetric boundary-layer flow of a viscous nanofluid around a stretching permeable cylinder. The mathematical model includes the influences of thermal radiation, viscous dissipation, Brownian movement, and thermophoresis. The governing partial differential equations were reduced to a system of nonlinear ordinary differential equations which were resolved analytically by the Homotopy Analysis Method (HAM). Performance indicators discussed included the reduce Nusselt number (which is a measure of the rate of heat transfer) and the reduce Sherwood number (which is a measure of the mass transfer rate), at the cylinder surface. Using Response Surface Methodology (RSM) using a Central Composite Face-centered (CCF) design, second order predictive models were formulated with high accuracy. These models had very good goodness of fit values with R 2 = 99.55% of the reduced Nusselt number and R 2 = 99.20 of the reduced Sherwood number. Further sensitivity analysis on the globe showed that the radiation parameter ( Rd ) had the highest sensitivity coefficient, with maximum sensitivity coefficients of 0.08469 to one unit change in the Reynolds number ( Re ) and 0.07679 to one unit change in the Prandtl number ( Pr ). In the case of the lower Sherwood number, the Brownian motion parameter ( Nb ) showed a steady positive sensitivity, coefficients of +0.584 per unit change in Re and +0.1111 per unit change in the Lewis number ( Le ). These quantitative results offer practical, straightforward recommendations on what engineers should prioritize and manage in the design and optimization of applicable, industrial and biomedical applications.

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