... is to examine the combined influences of porous effects, nanoparticle transport, bioconvection and stratification on flow behavior, heat transfer and mass transport while assessing the predictive capability of an artificial neural network ( ANN ) framework. Design/methodology/approach The two-phase...

...%, while phase-shifted oscillations improve thermal transport by approximately 65% and concurrently reduce fluid friction, indicating superior thermo-hydrodynamic performance. Mass transfer remains insensitive to wall kinematics. The ANN predictions achieve high accuracy with absolute errors in the range...

... a computational basis for future three-dimensional, locally nonequilibrium and experimentally validated extensions. Practical implications The proposed ISPH–ANN (artificial neural network) framework enables rapid estimation of global transport indicators for complex porous enclosures without repeated high...

... trihybrid nanofluid Quadratic thermal radiation Velocity slip Stretching surface ANN Efficient management of heat and momentum transport in complex fluids remains a central challenge in modern thermal and fluid engineering, given their wide-ranging applications in energy systems, biomedical...

...Tahar Tayebi; Amjad Ali Pasha; M.K. Nayak; Mohammed K. Al Mesfer; Mohd Danish; Sana Qaiyum; Nehad Ali Shah Purpose This paper aims to evaluate how artificial neural network ( ANN )-based multilayer perception ( MLP ) predicts the behavior of the system under different conditions, optimizes thermal...

...Hillal M. Elshehabey Purpose The purpose of this paper is to present numerical simulations for magnetohydrodynamics natural convection of a nanofluid flow inside a cavity with an H-shaped obstacle based on combining artificial neural network (ANN) with the finite element method (FEM), and predict...

... tool and numerical simulation. Development of a surrogate forward model with artificial neural networks (ANNs) with a view to explore the full parametric space. To quantitatively ascertain if protrusions hurt or help heat transfer for an impinging jet on a concave surface. Determination of the location...

.... Afterward, the influences of effective parameters on the temperature distribution and burning time are investigated. Artificial neural network (ANN) is applied to approximate the particle temperature as a function of time, diameter and porosity factor. To obtain the best arrangement of the ANN structure...