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 and temperature by Adams Bashforth method and these solutions are used as a reference dataset of the networks. Data is processed by segmentation into three categories i.e., training, validation and testing while Levenberg–Marquart training algorithm is adopted for optimization of networks results in terms of performance on mean square errors, train state plots, error histograms, regression analysis, time series responses, and auto-correlation, which establish the accurate and efficient recognition of trends of the system.
Highlights
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
Results of proposed study ANN-Levenberg–Marquardt Method (LMM) along with the reference solutions as per procedure provided in the last section are presented for fluidic model of peristaltic flow through a curved channel to predict the flow and heat transfer characteristics
The results provided here are based on 60 hidden neurons, while small change of number of neurons in neural network structure have no bit impact on the performance
Summary
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. E baid[3] investigated the behavior of peristaltic transport of a Newtonian fluid for influences of wall slip conditions and magnetic field in an asymmetric channel. Numerical solvers based on deterministic procedure for nonlinear systems including Chebyshev Polynomial Approximations, Variational Iteration Method, Adomian Decomposition Method, Pade Approximation Technique, Cubic B-Spline Scaling Functions, Homotopy Perturbation Method, Homotopy Analysis Method, Finite Element Method, Finite Difference Method etc. Major features of these methods are expensive computation, determinism, and a precursor analytical methodology and these procedures have their own limitations and deliver same final outcomes as classical one
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