Application of Heat and Mass Transfer to Convective Flow of Casson Fluids in a Microchannel with Caputo–Fabrizio Derivative Approach

Abstract

AbstractIt has been demonstrated that fractional derivatives exhibit a range of solutions that are helpful in the engineering, medical, and manufacturing sciences. Particularly in analytical research, investigations on using fractional derivatives in fluid flow are still in their infancy. Therefore, it is still being determined whether fractional derivatives may be represented geometrically in the mechanics of the flow of fluids. However, theoretical research will be helpful in supporting upcoming experimental research. Therefore, the aim of this study is to showcase an application of Caputo–Fabrizio toward the Casson fluid flowing in an unsteady boundary layer. Mass diffusion and heat radiation are taken into account while analyzing the PDEs that governed the problem. Dimensionless governing equations are formed from the fractional PDEs by utilizing the necessary dimensionless variables. Once the equations have been transformed into linear ODEs, the solution may then be found by applying the Laplace transform technique. Inverting Laplace transforms by Stehfest’s and Tzou’s Algorithm is then used to retrieve the original variables and the solutions as concentration, temperature, and velocity fields. Graphical illustrations sketched using the Mathcad program are used to show how physical parameters affect temperature, velocity, and concentration profiles. Findings show that the velocity, temperature, and concentration profiles have been improved by thermal radiation, mass diffusion, and fractional parameters. The fractional derivative is a more general derivative due to its nonlocal and flexible nature the flow model that is formulated by applying the fractional derivative is suitable to address the memory effect. The present fractionalized results of velocity, concentration, and temperature are more general and applicable to the wide range of orders of fractional derivatives.