linear regression model

Magnetohydrodynamic application in the biomedical field made the researcher work more on this field in recent years. The major application of this concept is in scanning using laser beams, delivering a drug to the targeted points, cancer treatment, enhancing image contrast, etc. These applications are depending on the flow and heat transfer properties of the magnetic conducting fluid and on the geometry of the flow field. An increase in the demand for the miniature in the shape and size of the clinical devices attracts the researcher to work more on design optimization. In this study optimization of magnetic field strength, geometry of domain, Prandtl number, Reynolds number for a steady, incompressible double-diffusive flow is performed using Taguchi and Analysis of variance technique. Linear regression model is used to predict the average Nusselt and Sherwood numbers. Numerical simulations were performed using finite volume method (FVM) based numerical techniques.  Experiments are designed based on Taguchi orthogonal array and FVM based numerical codes were used to obtain the results. Results show that an increase in the aspect ratio from to 0.5 to 2.0 improves the heat transfer rate by 62.0% and the mass transfer rate by 38.5%. As the Prandtl number increases from 0.7 to 13.0, heat transfer rate increases by 80.0% and mass transfer by 75.0%. This specific study could be applied in designing of solar ponds and to investigate heat and mass transfer effects during cancer treatments.