Darcy flow of convective and radiative Maxwell nanofluid over a porous disk with the influence of activation energy.

This study reveals an incompressible steady Darcy flow of Maxwell nanofluid by a porous disk with the impact of activation energy. The liquid flow is due to a stretchable rotating disk. The heat equation also includes the impact of heat source/sink and radiation for the purpose of heat transportation. The von Karman transformations are utilized to gain the dimensionless form of ordinary differential equations (ODEs). The solutions are visualised in the form of graphical results using bvp 4c method in Matlab software. The ranges of the associated physical parameters as, 0.0≤ß≤0.9, 0.0≤M≤0.9, 0.0≤λ≤1.5, 0.1≤R≤0.9, -0.2≤s≤1.3, 0.3≤Bi≤0.6, 0.0≤γ≤0.15, 0.1≤Nt≤2.0, 0.2≤Nb≤0.8, 0.0≤Rd≤0.3, 0.0≤σ≤1.5, and 0.0≤E≤0.9 are provided for the graphical solutions developed for the problem. The data of Nussetl and Sherwood numbers are presented here with regard to various physical parameters. According to the numerical results, increasing the Deborah number has a trend to decrease the radial curves. Moreover, the temperature distribution is increased considerably for rising the radiation parameter and the higher rate of the rotation parameter shows a weaker concentration trend. To validate the numerical approach, an excellent comparison is established using a tabular description. To sum up, the current study effectively fills a gap in the antecedent literature.

Efficient class of ratio cum median estimators for estimating the population median.

In estimation theory, the use of auxiliary information significantly improves precision while estimating population parameters. In this paper, an efficient class of ratio cum median estimators of the population median is suggested using simple random sampling without replacement. The expressions for bias and mean square error of the proposed class are derived theoretically. The condition for the asymptotic optimum estimator is obtained with its bias and mean square error expressions. Under certain realistic conditions, the asymptotic optimum estimator is more proficient, based on analytical and numerical comparisons with some existing estimators that are members of the suggested class of estimators. The superiority of the proposed ratio cum median estimators is shown through real data applications. Such a new proposed estimator will be useful in the future for data analysis and making decisions.