Integrated intelligent computing application for effectiveness of Au nanoparticles coated over MWCNTs with velocity slip in curved channel peristaltic flow
Abstract:Estimation of the effectiveness of Au nanoparticles concentration in peristaltic flow through a curved channel by using a data driven stochastic numerical paradigm based on artificial neural network is presented in this study. In the modelling, nano composite is considered involving multi-walled carbon nanotubes coated with gold nanoparticles with different slip conditions. Modeled differential system of the physical problem is numerically analyzed for different scenarios to predict numerical data for velocity… Show more
“…46 ]. Figure 18 Profiles of shear stress versus normalized velocity difference ( a ) at different values of near the wall ( b ) for and without nanoparticles 1 . Figure 19 Profiles of ( a ) missing velocity slope and ( b ) missing temperature slope with different values of near wall .…”
Section: Resultsmentioning
confidence: 99%
“… Profiles of shear stress versus normalized velocity difference ( a ) at different values of near the wall ( b ) for and without nanoparticles 1 . …”
Section: Resultsmentioning
confidence: 99%
“…Common liquids considered under some conditions by scientists and engineers, such as oils, water and air, can be classified as Newtonian fluids. In several circumstances, Newtonian behavior assumptions are not applicable in the real sense, Raja et al 1 . However, scientists respond to formulate a non-Newtonian fluid model based on some basic assumptions and fluid behavior.…”
Section: Introductionmentioning
confidence: 99%
“…Raja et al 37 investigated the entropy characteristics in magnetohydrodynamics (MHD) nanofluidic flow model by varying surface thickness. Estimation of the effectiveness of Au nanoparticles concentration in peristaltic flow through a curved channel by using a data driven stochastic numerical paradigm based on artificial neural network is presented by Raja et al 38 . A novel application of an intelligent numerical computing paradigm via artificial neural networks optimized with a Bayesian regularization approach has been presented by Awan et al 39 for the investigation of the non-uniform heat absorption process with the bio-convective flow dynamics of nanomaterial involving gyro-tactic microorganisms.…”
This communication focuses on assessing the effectiveness of nanoparticles, and a power-law variation fluid on a moving stretching surface is analyzed. Newtonian fluids for different nanomaterials are considered due to its industrial demand. The partial differential equations describing the flow are transformed to ordinary differential equations by employing local similarity transformations and then solved numerically by an effective numerical approach, namely, the local nonsimilarity method (LNS). The numerical solution is computed for different parameters by using the computational software MATLAB. Different types of nanoparticles are considered, and the impact of those nanoparticles as well as the impact of different pertaining parameters on velocity, temperature, missing velocity slope, and missing temperature slope are presented graphically. Comparisons are made with the available results in the open literature. Our investigation conveys a better impact on $${\text{Ag}}$$
Ag
nanoparticles due to their higher thermal conductivity. Furthermore, an increase in the free stream velocity, missing temperature slope and velocity slope is enhanced, but after a point of separation, the missing temperature slope decays.
“…46 ]. Figure 18 Profiles of shear stress versus normalized velocity difference ( a ) at different values of near the wall ( b ) for and without nanoparticles 1 . Figure 19 Profiles of ( a ) missing velocity slope and ( b ) missing temperature slope with different values of near wall .…”
Section: Resultsmentioning
confidence: 99%
“… Profiles of shear stress versus normalized velocity difference ( a ) at different values of near the wall ( b ) for and without nanoparticles 1 . …”
Section: Resultsmentioning
confidence: 99%
“…Common liquids considered under some conditions by scientists and engineers, such as oils, water and air, can be classified as Newtonian fluids. In several circumstances, Newtonian behavior assumptions are not applicable in the real sense, Raja et al 1 . However, scientists respond to formulate a non-Newtonian fluid model based on some basic assumptions and fluid behavior.…”
Section: Introductionmentioning
confidence: 99%
“…Raja et al 37 investigated the entropy characteristics in magnetohydrodynamics (MHD) nanofluidic flow model by varying surface thickness. Estimation of the effectiveness of Au nanoparticles concentration in peristaltic flow through a curved channel by using a data driven stochastic numerical paradigm based on artificial neural network is presented by Raja et al 38 . A novel application of an intelligent numerical computing paradigm via artificial neural networks optimized with a Bayesian regularization approach has been presented by Awan et al 39 for the investigation of the non-uniform heat absorption process with the bio-convective flow dynamics of nanomaterial involving gyro-tactic microorganisms.…”
This communication focuses on assessing the effectiveness of nanoparticles, and a power-law variation fluid on a moving stretching surface is analyzed. Newtonian fluids for different nanomaterials are considered due to its industrial demand. The partial differential equations describing the flow are transformed to ordinary differential equations by employing local similarity transformations and then solved numerically by an effective numerical approach, namely, the local nonsimilarity method (LNS). The numerical solution is computed for different parameters by using the computational software MATLAB. Different types of nanoparticles are considered, and the impact of those nanoparticles as well as the impact of different pertaining parameters on velocity, temperature, missing velocity slope, and missing temperature slope are presented graphically. Comparisons are made with the available results in the open literature. Our investigation conveys a better impact on $${\text{Ag}}$$
Ag
nanoparticles due to their higher thermal conductivity. Furthermore, an increase in the free stream velocity, missing temperature slope and velocity slope is enhanced, but after a point of separation, the missing temperature slope decays.
“…Abd-Alla et al [46] analyzed the numerical solution for MHD peristaltic transport in an inclined nanofluid symmetric channel with a porous medium. Raja et al [47] examined the integrated intelligent computing application for the effectiveness of Au nanoparticles coated over MWCNTs with velocity slip in curved channel peristaltic flow.…”
This article includes a numerical study of the double-diffusive peristaltic flow of a non-Newtonian Sisko nanofluid through a porous medium inside a horizontal symmetric flexible channel under the influence of Joule heating, nonlinear thermal radiation, viscous dissipation, and heat generation/absorption in presence of heat and mass convection, considering effects of the Brownian motion and the thermophoresis coefficients. On the other side, the long wave approximation was used to transform the nonlinear system of partial differential equations into the nonlinear system of ordinary differential equations which were later solved numerically using the fourth-order Runge-Kutta method with shooting technique using MATLAB program code. The effects of all physical parameters resulting from this study on the distributions of velocity, temperature, solutal concentration, and nanoparticles volume fraction inside the fluid were studied in addition to, a study of the pressure gradients using the 2D and 3D graphs that were made by the MATLAB program in addition to, studying the impact of some parameters on the behavior of the streamlines graphically within the channel with a mention of their physical meaning. Finally, some of the results of this study showed that the effect of Darcy number 𝐷𝑎 and the magnetic field parameter 𝑀 is opposite to the effect of the rotation parameter 𝛺 on the velocity distribution whereas, the two parameters non-linear thermal radiation𝑅and the ratio temperature 𝜃𝑤works on a decrease in the temperature distribution and an increase in both the solutal concentration distribution and the nanoparticle's volume fraction. On the other hand, the effect of the rotation parameter 𝛺 on the distribution of pressure gradients was positive, and the effect of both Darcy number 𝐷𝑎 and the magnetic field parameter 𝑀on the same distribution was negative.
The research community has shown great interest for investigation in the nanofluids models involving Aluminum Alloys AA7072 and AA7072 +AA7075 due to their advantageous impact on heat transfer, physical and mechanical characteristic exploiting in broad engineering applications such as manufacturing of spacecraft, aircraft parts and building testing. The hybrid nanomaterial AA7072-AA7075 based fluidic system is investigated in this paper using an artificial neural network with Bayesian regularization scheme (ANNs-BRS). The derived partial differential equations (PDEs) are transformed into ordinary differential equations system ODEs and obtained the reference datasets for the estimated solution dynamics of hybrid nanofluidic system. For prominent parameters, the influence of flow on the temperature distribution and velocity plot are investigated. The performance on 80% training samples, 5% testing and 15% validation dataset for ANNs-BRS is well-established in terms of error histogram plots, regression analysis, and MSE based statistics. The results for entropy generation, Eckert number Ec, magnetic interaction parameter M, suction parameter S, and heat generation parameter 𝑄 are also discussed. The results show that the Eckert number Ec has the effect of slowing down the rate of heat transfer while increasing the temperature and increases in suction parameter causes decrease in temperature while increase in temperature profile due to enhancement of suction parameter.
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