纳米流体在螺旋通道中数值模拟的研究进展

纳米流体作为一种新型高效的换热介质,其在螺旋通道中的应用被广泛研究。尤其是通过单相和两相模型对其流动及传热特性进行数值模拟,是研究热点。介绍了单相模型中纳米流体物理参数的计算关联式,包括密度、比热、黏度及导热系数等,并分析了不同关联式对同一参数计算结果的影响;总结了单相模型下纳米流体在螺旋通道中的流动及传热特性,并与两相Lagrangian-Eulerian及Mixture模型下得到的结论进行对比分析;展望了未来研究的发展趋势。     

Convection of 3D MHD non-Newtonian couple stress nanofluid flow via stretching surface

This study involvesthe numerical modeling of steady thermal radiation and chemical reaction on non-Newtonian fluid motion via a bidirectional stretching surface. We have taken convective boundary conditions, and heat sources on the stretching surface. The working fluid of the present study is Casson fluid (“non-Newtonian”) with couple stress. The self-similarity forms of the nonlinear thermal radiative flow model are obtained by using similarity variables. Furthermore, the numerical results are computed with the help of fourth-order Runge–Kutta–Fehlberg method with a shooting algorithm after reducing nonlinear partial differential equations have been translated into strong ordinary differential equations (ODEs). Impacts of the various flow physical parameters especially Biot number, nonlinear thermal radiation, and heat source parameters containing nonlinear ODEs are discussed in detail for distinct numerical values. A comparison of calculated results with the known numerical results made with the previously published literature is mentioned and obtained a good agreement. Finally, we found that the $R{e}_x^{1/2}{C}_{fx}$ (“coefficient of skin friction”) declines along $x*,y*$ directions, respectively, with $\beta$ via $\lambda$ while the opposite direction follows $M$ with respect to $\lambda$ and the $R{e}_x^{-1/2}N{u}_x$ (“heat transfer rate”), $R{e}_x^{-1/2}Sh$ (“mass transfer rate”) increase with $\Gamma$ via ${\gamma }_1$ while opposite direction follows ${\gamma }_1$ with respect to ${\gamma }_2$.     

Design of inverse multiquadric radial basis neural networks for the dynamical analysis of MHD casson nanofluid flow along a nonlinear stretchable porous surface with multiple slip conditions

The present research, a numerical approach to examine magnetohydrodynamics (MHD) Casson nanofluid flow in a porous medium along a stretchable surface with different slips using artificial neural networks (ANNs) by taking inverse multiquadric (IMQ) radial basis function (RBF) as an activation function. i.e. ANNs-IMQ-RBF. The hybridization of genetic algorithms (GAs) and sequential quadratic programming (SQP) is used for learning in ANNs-IMQ-RBF. The PDEs representing the fluid flow are converted into a nonlinear system of dimensionless form of ODEs through an appropriate transformation while effects of variation in the values of Casson parameter (β), Brownian motion parameter (Nb), Prandtl number (Pr), stretching parameter (n), porosity parameter (P), Lewis number (Le) along with temperature slip parameter (λ₂) on velocity, temperature and nanofluid concentration are depicted through graphs. The effectiveness, convergence and accuracy of the proposed solver are validated evidently through boxplot analysis, histograms and cumulative distribution function (CDF) plots.     

Characteristics of MHD nanofluid flow towards a vertical cone under convective cross-diffusion effects through numerical solutions

In this study, the aim is to find the numerical solutions of steady, two-dimensional, incompressible, viscous, electrically conducting magnetohydrodynamic (MHD) boundary-layer nanofluid flow towards a vertical cone in the presence of thermal diffusion, diffusion thermo, thermophoresis, and Brownian motion effects subject to porous medium and convective boundary condition. For this investigation, the method of similarity transformations is used for the objective of converting nonlinear partial differential equations into the system of ordinary differential equations. Approximate solutions are obtained using a numerical method of the Runge–Kutta method with the shooting technique for the flow, heat, and mass transfer equations together with boundary conditions. For this flow, the impact of various engineering parameters on MHD, thermal, and solutal boundary layers is investigated and the results are displayed graphically. In addition, the numerical values of the local skin-friction coefficient, rate of heat transfer, and rate of mass transfer coefficients are calculated, and the results are presented numerically. Finally, the comparison with previously published work is made and found in good agreement.     

Variable thermal conductivity influence on micropolar nanofluid flow triggered by a stretchable disk with Arrhenius activation energy

The analysis of magnetized micro–nanoliquid flows generated by the movable disk is executed in this study. The disk is contained under the porous zone influence. The heat generation, heat sink, and temperature-dependent conductance analysis are reported through the energy equation. The activation energy in terms of a chemical reaction is incorporated through the mass equation. The flow model is normalized through the implementation of similarity transformations. The numerical algorithm Runge–Kutta–Fehlberg is used to solve the reduced system. Results are plotted graphically and in tabular format to investigate the velocity, thermal, and concentration fields. Numeric benchmarks of couple and shear stresses, thermal and concentration rates are also computed. The temperature is augmented against the incremented thermophoretic, variable conductivity, and Brownian movement parameters. The presence of variable conductivity parameter resulted in a weaker rate of heat transportation. The heat transportation rate is boosted with an incremented Prandtl number.     

Study of chemically reactive and thermally radiative Casson nanofluid flow past a stretching sheet with a heat source

Nanoparticle (NP) delivery is an exciting and rapidly developing field that adequately takes care of thermal radiation in blood flow and is likely to have bearing on the therapeutic procedure of hyperthermia, blood flow, and heat transfer in capillaries. The NP parameters such as size, shape, and surface characteristics can be regulated to improve nano-drug delivery efficiency in biological systems. The NPs outperform traditional drug delivery processes in drug carrying capacity and controlled release. The current article investigates the boundary layer flow and heat transfer of thermally radiative Casson nanofluid (NF) over a stretching sheet with chemical reaction and internal heat source. In our study, Cu and Al₂O₃ are taken as NPs in a suitable base fluid. The problem is analyzed by using similarity transformations and is solved with MATLAB's built-in solver bvp4c. The effects of pertinent parameters characterizing the flow model are presented through graphs and tables. The important findings of the investigation are noted as: the use of metallic oxide is more beneficial to attain higher temperature within a few layers close to the bounding surface; the appearance of convexity and concavity in the concentration profile attributed to flow instability, and the constructive and destructive heterogeneous reactions at the bounding surface have distinct roles to modify the NF flow in the boundary layer.