THEORETICAL STUDY OF MHD MAXWELL FLUID WITH COMBINED EFFECT OF HEAT AND MASS TRANSFER VIA LOCAL AND NONLOCAL TIME DERIVATIVES

Muhammad Bilal Riaz (), Fahd Jarad, Dumitru Baleanu and Maryam Asgir ()
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Muhammad Bilal Riaz: Department of Mathematics, University of Management and Technology, C-II Johar Town, Lahore 54770, Pakistan
Fahd Jarad: Department of Mathematics, Faculty of Arts and Sciences, Cankaya University, Etimesgut Ankara, Turkey3Department of Medical Research, China Medical University Hospital, China Medical University, Taichung Taiwan
Dumitru Baleanu: Department of Mathematics, Cankaya University, Turkey5Institute of Space Sciences, Magurele, Bucharest, 077125, Romania
Maryam Asgir: Department of Mathematics, Government College University Lahore, Pakistan

FRACTALS (fractals), 2022, vol. 30, issue 01, 1-22

Abstract: This study highlights the combined effect of heat and mass transfer on MHD Maxwell fluid under time-dependent generalized boundary conditions for velocity, temperature, and concentration. The classical calculus due to the fact that it is assumed as the instant rate of change of the output when the input level changes. Therefore, it is not able to include the previous state of the system called the memory effect. But in the fractional calculus (FC), the rate of change is affected by all points of the considered interval, so it can incorporate the previous history/memory effects of any system. Due to this reason, we applied the modern definition of fractional derivatives (local and nonlocals kernels). Here, the order of fractional derivative will be treated as an index of memory. The exact and semi-analytical solutions are obtained using the integral transform and inversion algorithm. Several important properties of different parameters are analyzed by graphs. Interesting results are revealed by this investigation due to their vast applications in engineering and applied sciences.

Keywords: Memory Effect; MHD; Free Convection; Integral Transform; Fractional Time Derivatives; Local and Nonlocal Kernels; Algorithm (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22400102

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