...-Darcy medium. This work analyzes the combined effects of electro-hydrodynamic forces, heat transfer, viscous dissipation, Joule heating and motile microorganism-induced bioconvection. A novel hybrid framework based on the homotopy perturbation method and artificial neural network is developed...

... by using similarity transformations and solved numerically by the shifted Legendre polynomial collocation method ( SLPCM ). Also, response surface methodology ( RSM ) and a Levenberg-Marquardt artificial neural network (LM-ANN) methods are employed to explore heat transfer. Findings Variable thermal...

...-integrated cooling passage and develops an artificial neural network ( ANN ) surrogate for rapid prediction of thermal-hydraulic performance. Design/methodology/approach A three-dimensional two-phase mixture model is solved using the finite-volume method with SIMPLEC pressure–velocity coupling...

... the system of equations into non-dimensional form. Furthermore, robust numerical method, i.e. the Keller box method ( KBM ) is employed to solve these transformed equations. In addition, the artificial neural network ( ANN ) model was constructed using the radiation parameter, heat source parameter and Biot...

... analysis and Levenberg–Marquardt scheme-artificial neural network (LMS-ANN) prediction, to accurately evaluate average heat and mass transfer rates in a trapezoidal cavity filled with ternary nanofluids under double-diffusive convection. By combining numerical modeling, statistical optimization and machine...

... solutions are used to train an artificial neural network model with the Levenberg–Marquardt algorithm. Findings The results show that Coriolis and Lorentz forces reduce the velocity field, while thermal relaxation suppresses energy transport. Skin friction coefficient decays as the rotation and magnetic...

...Xinwang Liu; Muhammad Ishaq; Muhammad Bilal Ashraf; Maria Altaib Badawi; Adel Thaljaoui; Umer Farooq Purpose The purpose of this study is to develop an intelligent artificial neural network-based framework for predicting the flow, heat, mass and bioconvection characteristics of Johnson–Segalman...

... micropolar ternary nanofluid flow over a surface. The calculation of flow fields and heat transfer concerning several input factors necessitates a complex method. Computational intelligence techniques, such as artificial neural networks (ANNs), can learn many models rather than relying on complex...

.... Moreover, advanced data-driven tools such as artificial neural network (ANN) have not been fully leveraged for the accurate prediction of hemodynamic quantities and efficient modeling of such complex hemodynamic systems. These gaps highlight the need to conduct a systematic study that integrates arterial...

...Subham Jangid; Kaladhar Kolla Purpose This study aims to analyze the mixed convection of Williamson fluid through a vertical channel, taking into account the effects of both the Soret phenomenon and a magnetic field along with a first-order chemical reaction. An “artificial neural network” ( ANN...

...Faisal; Aroosa Ramzan; Moeed Ahmad; Waseem Abbas Purpose This study aims to develop a neurocomputational approach using the Levenberg–Marquardt artificial neural network (LM-ANN) to analyze flow and heat transfer characteristics in mixed convection involving radiative magnetohydrodynamic hybrid...

... to solve the governing equations after converting them to dimensionless form. The authors also try the artificial neural network method to predict the innovative cavity’s heat response in future scenarios. Transition state charts, regression analysis, MSE and error histograms accelerate, smooth...

... methodology and artificial neural networks are used to develop the empirical model for pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. Findings The empirical model demonstrates an excellent fit with a coefficient of determination reaching 100...

... increases with increasing the Reynolds number and slip coefficient. Afterwards, a non-parametric function estimation is performed relying on the artificial neural network. Originality/value Finally, the Genetic Algorithm was used to establish a set of optimal decision parameters for the problem...

...@mu.edu.sa 09 11 2020 06 12 2020 10 12 2020 13 12 2020 13 12 2020 © Emerald Publishing Limited 2020 Emerald Publishing Limited Licensed re-use rights only Heat transfer Artificial neural network Carbon nanotube Silicon dioxide XRD = X-ray...

...., AIAA J., 2015). Contrary to RANS methods, such a hybrid approach makes unsteady distortions available, which are necessary information for reconstruction algorithm assessment. Findings The best reconstruction accuracy is obtained with the artificial neural network (ANN) but the improvement compared...