Fractional derivative has a memory and non-localization features that make it very useful in modelling epidemics’ transition. The kernel of Caputo-Fabrizio fractional derivative has many features such as non-singularity, non-locality and an exponential form. Therefore, it is preferred for modeling disease spreading systems. In this work, we suggest to formulate COVID-19 epidemic transmission via
paradigm using the Caputo-Fabrizio fractional derivation method. In the suggested fractional order COVID-19
paradigm, the impact of changing quarantining and contact rates are examined. The stability of the proposed fractional order COVID-19
paradigm is studied and a parametric rule for the fundamental reproduction number formula is given. The existence and uniqueness of stable solution of the proposed fractional order COVID-19
paradigm are proved. Since the genetic algorithm is a common powerful optimization method, we propose an optimum control strategy based on the genetic algorithm. By this strategy, the peak values of the infected population classes are to be minimized. The results show that the proposed fractional model is epidemiologically well-posed and is a proper elect.
Heat flow may be improved using a new form of nanofluid known as ternary hybrid nanofluid. Magnetic field, mass suction, and heat source effects on the stagnation area of [Formula: see text]) ternary hybrid nanofluid toward convectively heated stretching/shrinking cylinder with cylindrical shape nanoparticles are studied in this work. There will be an equation modeled under the given assumptions. It is feasible, with the help of similarity transformation, to convert nonlinear partial differential equations that are not quite solvable into ordinary differential equations that can be resolved numerically. The prevailing role of heat transfer and the features of movement of ternary hybrid nanofluids have been found to be significantly affected by the combination of Runge–Kutta-IV and the shotting technique in Mathematica. Many variables, including suction, Reynold number, nanoparticle volume fraction, magnetic field, Biot number, heat source, and stretching/shrinking influenced temperature, velocity, skin friction, and the local heat transfer rate, as shown in the graphs in the study. When magnetic field, suction, and Reynold number are present velocity increases, but inverse is true for nanoparticle volume fraction and stretching/shrinking parameter. The greatest influence on the surface is shown by the ternary hybrid nanofluid. Additionally, the heat transfer rate of the ternary hybrid nanofluid is faster than that of the hybrid and regular nanofluids.
The research of single and multi-wall carbon nanotubes (SWCNTs/MWCNTs) mixed in sodium alginate-based nanofluid with MHD stagnation-point flow on a convective heated stretching disk with viscous dissipation and suction effects is being done with the intention of decoding the heat and mass transmission mechanism. It is possible to transform PDEs that govern the boundary layer into ODEs. MATLAB’s Bvp5c is used to numerically solve the revised equations. The Yamada-Ota model and the Buongiorno model are used in this work to scrutinize the flow, heat, and mass transfer parameters. The following parameters were brought up for discussion: volume fraction nanoparticle, magnetic parameter, suction, Brownian motion, thermophoresis, Lewis number, Eckert number, Biot number, stretching, and thermophoresis. This study found that nanofluid (SWCNT/sodium alginate) has a superior flow, heat, and mass transfer rate than nanofluid (MWCNT/sodium alginate). Graphical representations of the effects of various factors are shown, and a comparison of current and prior findings is given in a table. A comparison of current and previous findings reveals a 0% relative inaccuracy. The velocity ratio parameter has solutions that look close to the separation value. The performance of heat and mass transfer operations may be improved by increasing suction parameters. Increases in Brownian motion [Formula: see text] and suction decrease the temperature profile, whereas increases in velocity ratio and magnetic parameters increase velocity. This research is critical for estimating flow, temperature, and concentration behavior for CNTs with incorporated physical properties.
Hybrid nanofluids play a significant role in the advancement of thermal characteristics of pure fluids both at experimental and industrial levels. This work explores the mixed convective MHD micropolar hybrid nanofluid flow past a flat surface. The hybrid nanofluid flow is composed of alumina and silver nanoparticles whereas water is used as a base fluid. The plate has placed vertical in a permeable medium with suction and injection effects. Furthermore, viscous dissipation, thermal radiation and Joule heating effects are taken into consideration. Specific similarity variables have been used to convert the set of modeled equations to dimension-free form and then has solved by homotopy analysis method (HAM). It has revealed in this investigation that, fluid motion upsurge with growth in magnetic field effects and mixed convection parameter and decline with higher values of micropolar factor. Micro-rotational velocity of fluid is upsurge with higher values of micropolar factor. Thermal flow behavior is augmenting for expended values of magnetic effects, radiation factor, Eckert number and strength of heat source. The intensification in magnetic strength and mixed convection factors has declined the skin friction and has upsurge with higher values of micropolar parameter. The Nusselt number has increased with the intensification in magnetic effects, radiation factor and Eckert number.
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