Swimming of microbes in blood flow of nano-bioconvective Williamson fluid

Rana, Biswarup; Arifuzzaman, S. M.; Islam, Saiful; Reza‐E‐Rabbi, Sk.; Al‐Mamun, Abdullah; Mazumder, Malati; Roy, Kanak Chandra; Khan, Mohidus Samad

doi:10.1016/j.tsep.2021.101018

Cited by 48 publications

(21 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this ongoing flow model stratification features have been taken into account because this process has multitudinous down‐to‐earth applications, such as for illustration, human transpiration, desalination, diluting of sheets and wires, fabricating of plastics and rubber sheets, and solar energy accumulators. Conclusively, the obtained upshots for triple stratification on this nano‐bioconvective flow problem are identical to the uncovered outcomes of Chu et al, 10 Areekara et al, 12 and Rana et al 13 Pictorial illustrations of some fascinating physical quantities for influential factors are uncovered in Figure 9A–H. Figure 9A portrays the skin friction for multifarious magnitudes of W 1 and W 2 .…”

Section: Resultssupporting

confidence: 76%

“…Additionally, comparative statistical analysis is carried out through a bar diagram (see Figure 4.). Note that, the experimental validation of this finite difference method was uncovered by Rana et al 13 …”

Section: Numerical Analysismentioning

confidence: 87%

“…To procure the dimensionless ruling expressions, the following nondimensional quantities are adopted, 13

\left.\begin{array}{c}X=\displaystyle \tfrac{x{U}_{0}}{\upsilon }{e}^{\displaystyle \tfrac{x}{L}},Y=\displaystyle \tfrac{y{U}_{0}}{\upsilon }{e}^{\displaystyle \tfrac{x}{L}},U=\displaystyle \tfrac{u}{{U}_{0}}{e}^{-\displaystyle \tfrac{x}{L}},V=\displaystyle \tfrac{v}{{U}_{0}}{e}^{-\displaystyle \tfrac{x}{L}},\tau =\displaystyle \tfrac{t{{U}_{0}}^{2}}{\upsilon }{e}^{\displaystyle \tfrac{2x}{L}},\\ \theta =\displaystyle \tfrac{T-{T}_{\infty }}{{T}_{w}-{T}_{0}},\phi =\displaystyle \tfrac{C-{C}_{\infty }}{{C}_{w}-{C}_{0}},N=\displaystyle \tfrac{\bar{N}-{\bar{N}}_{\infty }}{{\bar{N}}_{w}-{\bar{N}}_{0}}.\end{array}\right\}

…”

Section: Mathematical Modelingmentioning

confidence: 99%

See 2 more Smart Citations

Swimming of microbes in entropy optimized nano‐bioconvective flow of Prandtl–Erying fluid

Rana

Arifuzzaman²,

Islam

et al. 2022

Heat Trans

Self Cite

View full text Add to dashboard Cite

Microbes swimming in a fluid that contains nanoparticles is an intriguing characteristic having ramifications in biomedicine, petroleum science, biofuels, and biotechnology applications. This study gives a theoretical evaluation of the bioconvection phenomena with swimming microorganisms in a Prandtl-Erying nanofluid constructed by an exponential stretched surface, given the amazing applications of bioconvection and nanoparticles. Additionally, the problem is modeled by considering intriguing phenomena such as thermophoretic particle deposition, Darcy-Forchheimer medium, exothermic/endothermic process, and activation energy vitality.The leading problem comprises nonlinear, coupled, partial differential expressions. To run the appraisal process, the controlling problem is transfigured into dimensionless patterns through the usual transformations. A computational finite difference approach is used to quantify the numerical evaluation of fabricated flow problems. To obtain the parametric constraints, stability and convergency were also assessed. Improved visualizations (streamlines, isothermal line, iso-concentration,

show abstract

Section: Resultssupporting

confidence: 76%

Section: Numerical Analysismentioning

confidence: 87%

“…To procure the dimensionless ruling expressions, the following nondimensional quantities are adopted, 13

\left.\begin{array}{c}X=\displaystyle \tfrac{x{U}_{0}}{\upsilon }{e}^{\displaystyle \tfrac{x}{L}},Y=\displaystyle \tfrac{y{U}_{0}}{\upsilon }{e}^{\displaystyle \tfrac{x}{L}},U=\displaystyle \tfrac{u}{{U}_{0}}{e}^{-\displaystyle \tfrac{x}{L}},V=\displaystyle \tfrac{v}{{U}_{0}}{e}^{-\displaystyle \tfrac{x}{L}},\tau =\displaystyle \tfrac{t{{U}_{0}}^{2}}{\upsilon }{e}^{\displaystyle \tfrac{2x}{L}},\\ \theta =\displaystyle \tfrac{T-{T}_{\infty }}{{T}_{w}-{T}_{0}},\phi =\displaystyle \tfrac{C-{C}_{\infty }}{{C}_{w}-{C}_{0}},N=\displaystyle \tfrac{\bar{N}-{\bar{N}}_{\infty }}{{\bar{N}}_{w}-{\bar{N}}_{0}}.\end{array}\right\}

…”

Section: Mathematical Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Swimming of microbes in entropy optimized nano‐bioconvective flow of Prandtl–Erying fluid

Rana

Arifuzzaman²,

Islam

et al. 2022

Heat Trans

Self Cite

View full text Add to dashboard Cite

show abstract

“…The investigation was done on the Forchheimer Williamson visco-elastic fluid stream through non-linearly extending sheet and entropy production and implications of dual chemical process on magnetohydrodynamics taken by Rasool et al [17]. Rana et al [18] analyzed the microbes swimming in nano-bioconvective Williamson fluid's blood flow. The researcher utilized the non-Newtonian fluid models (e.g., hyperbolic tangent fluid, Powell Eyring fluid, Casson fluid, Williamson fluid, etc.)…”

Section: Introductionmentioning

confidence: 99%

MHD Williamson Nanofluid Flow over a Slender Elastic Sheet of Irregular Thickness in the Presence of Bioconvection

et al. 2021

View full text Add to dashboard Cite

Bioconvection phenomena for MHD Williamson nanofluid flow over an extending sheet of irregular thickness are investigated theoretically, and non-uniform viscosity and thermal conductivity depending on temperature are taken into account. The magnetic field of uniform strength creates a magnetohydrodynamics effect. The basic formulation of the model developed in partial differential equations which are later transmuted into ordinary differential equations by employing similarity variables. To elucidate the influences of controlling parameters on dependent quantities of physical significance, a computational procedure based on the Runge–Kutta method along shooting technique is coded in MATLAB platform. This is a widely used procedure for the solution of such problems because it is efficient with fifth-order accuracy and cost-effectiveness. The enumeration of the results reveals that Williamson fluid parameter λ, variable viscosity parameter Λμ and wall thickness parameter ς impart reciprocally decreasing effect on fluid velocity whereas these parameters directly enhance the fluid temperature. The fluid temperature is also improved with Brownian motion parameter Nb and thermophoresis parameter Nt. The boosted value of Brownian motion Nb and Lewis number Le reduce the concentration of nanoparticles. The higher inputs of Peclet number Pe and bioconvection Lewis number Lb decline the bioconvection distribution. The velocity of non-Newtonian (Williamson nanofluid) is less than the viscous nanofluid but temperature behaves oppositely.

show abstract

“…Some recent and useful work has also been done for SGF with fractional differential operators [60][61][62][63][64][65]. Heat and mass transfer phenomena in nanofluids with a porous medium have been investigated by [66][67][68]. Some significant work in the field of nanoparticles and carbon nanotubes via fractional derivatives have been done by researchers [69][70][71].…”

Section: Introductionmentioning

confidence: 99%

Effect of Magnetic Field with Parabolic Motion on Fractional Second Grade Fluid

et al. 2021

View full text Add to dashboard Cite

This paper is an analysis of the flow of magnetohydrodynamics (MHD) second grade fluid (SGF) under the influence of chemical reaction, heat generation/absorption, ramped temperature and concentration and thermodiffusion. The fluid was made to flow through a porous medium. It has been proven in many already-published articles that heat and mass transfer do not always follow the classical mechanics process that is known as memoryless process. Therefore, the model using classical differentiation based on the rate of change cannot really replicate such a dynamical process very accurately; thus, a different concept of differentiation is needed to capture such a process. Very recently, new classes of differential operators were introduced and have been recognized to be efficient in capturing processes following the power law, the decay law and the crossover behaviors. For the study of heat and mass transfer, we applied the newly introduced differential operators to model such flow. The equations for heat, mass and momentum are established in the terms of Caputo (C), Caputo–Fabrizio (CF) and Atangana–Baleanu in Caputo sense (ABC) fractional derivatives. The Laplace transform, inversion algorithm and convolution theorem were used to derive the exact and semi-analytical solutions for all cases. The obtained analytical solutions were plotted for different values of existing parameters. It is concluded that the fluid velocity shows increasing behavior for κ, Gr and Gm, while velocity decreases for Pr and M. For Kr, both velocity and concentration curves show decreasing behavior. Fluid flow accelerates under the influence of Sr and R. Temperature and concentration profiles increase for Sr and R. Moreover, the ABC fractional operator presents a larger memory effect than C and CF fractional operators.

show abstract

Swimming of microbes in blood flow of nano-bioconvective Williamson fluid

Cited by 48 publications

References 41 publications

Swimming of microbes in entropy optimized nano‐bioconvective flow of Prandtl–Erying fluid

Swimming of microbes in entropy optimized nano‐bioconvective flow of Prandtl–Erying fluid

MHD Williamson Nanofluid Flow over a Slender Elastic Sheet of Irregular Thickness in the Presence of Bioconvection

Effect of Magnetic Field with Parabolic Motion on Fractional Second Grade Fluid

Contact Info

Product

Resources

About