Heat and Mass Transfer of Natural Convective Flow with Slanted Magnetic Field via Fractional Operators

被引:15
作者
Iftikhar, Nazish [1 ]
Baleanu, Dumitru [2 ,3 ,4 ]
Riaz, Muhammad Bilal [5 ,6 ]
Husnine, Syed Muhammad [1 ]
机构
[1] Natl Univ Comp & Emerging Sci, Dept Sci & Humanities, Lahore Campus, Lahore 54000, Pakistan
[2] Cankaya Univ, Dept Math, TR-06790 Ankara, Turkey
[3] Inst Space Sci, Bucharest 077125, Romania
[4] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung 40402, Taiwan
[5] Univ Management & Technol, Dept Math, Lahore 54000, Pakistan
[6] Univ Free State, Inst Groundwater Studies IGS, ZA-9301 Bloemfontein, South Africa
关键词
Fractional order derivatives; Inclined magnetic field; Laplace transformation; Inversion algorithm; VERTICAL PLATE; POROUS-MEDIUM; CONSTANT HEAT; FLUID; DIFFUSION;
D O I
10.22055/JACM.2020.34930.2514
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
This article explores the MHD natural convective viscous and incompressible fluid flow along with radiation and chemical reaction. The flow is confined to a moving tilted plate under slanted magnetic field with variable temperature in a porous medium. Non-dimensional parameter along Laplace transformation and inversion algorithm are used to investigate the solution of system of dimensionless governing equations. Fractional differential operators namely, Caputo (C), Caputo-Fabrizio (CF) and Atangana-Baleanu in Caputo sense (ABC) are used to compare graphical behavior of for velocity, temperature and concentration for emerging parameters. On comparison, it is observed that fractional order model is better in explaining the memory effect as compared to classical model. Velocity showing increasing behavior for fractional parameter a whereas there is a decline in temperature, and concentration profiles for alpha. Fluid velocity goes through a decay due to rise in the values of M, Sc and phi. However, velocity shows a reverse profile for augmented inputs of K-p, G(r) and S. Tabular comparison is made for velocity and Nusselt number and Sherwood number for fractional models.
引用
收藏
页码:189 / 212
页数:24
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