Intelligent Computation of Cilia‐Driven Micropolar Fluid Flow Through Porous Ductuli Efferentes With Activation Energy Effects

ABSTRACT This study investigates the cilia‐driven transport of an incompressible micropolar fluid through a porous ductuli efferentes channel under the combined effects of thermal radiation, heat generation, mixed convection, and activation energy. The mathematical model governing momentum, microrotation, energy, and concentration transport is developed using lubrication approximation theory, resulting in a coupled nonlinear system of differential equations. The reduced equations are solved numerically through a second‐order finite difference method (FDM). To accelerate the prediction process and reduce computational cost, an artificial neural network (ANN) model based on TensorFlow is developed using the numerical data set generated from the FDM solutions. The data set is divided into training, validation, and testing subsets to ensure accurate learning and prediction performance. The influence of important physical parameters, including Brinkman number, radiation parameter, Schmidt number, porous‐medium parameter, Grashof number, micropolar parameters, and activation energy, on velocity, temperature, concentration, pressure gradient, pressure rise, and trapping phenomena is examined in detail. The results reveal that thermal radiation reduces fluid temperature, whereas heat generation and viscous dissipation significantly enhance thermal transport. Increasing activation energy elevates the concentration profile due to reduced chemical reaction strength, while larger Schmidt numbers suppress mass diffusion. The ANN predictions exhibit excellent agreement with the numerical solutions with very small prediction errors, confirming the reliability and efficiency of the proposed intelligent computational framework. The present analysis provides important insights into seminal fluid transport mechanisms in the male reproductive tract and offers potential applications in biomedical engineering, reproductive biomechanics, and bio‐inspired microfluidic systems.

Authors

Institutions

Publication Details

Journal
Heat Transfer
Published
2026-06-19
DOI
https://doi.org/10.1002/htj.70301
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Computation of Cilia‐Driven Micropolar Fluid Flow Through Porous Ductuli Efferentes With Activation Energy Effects

Zaheer Abbas, Melis Arslan, Muhammad Yousuf Rafiq, Ahmed Aljunaibi
Heat Transfer
Nanofluid Flow and Heat Transfer
article

Intelligent Computation of Cilia‐Driven Micropolar Fluid Flow Through Porous Ductuli Efferentes With Activation Energy Effects

Zaheer Abbas, Melis Arslan, Muhammad Yousuf Rafiq, Ahmed Aljunaibi
article en

Abstract

ABSTRACT This study investigates the cilia‐driven transport of an incompressible micropolar fluid through a porous ductuli efferentes channel under the combined effects of thermal radiation, heat generation, mixed convection, and activation energy. The mathematical model governing momentum, microrotation, energy, and concentration transport is developed using lubrication approximation theory, resulting in a coupled nonlinear system of differential equations. The reduced equations are solved numerically through a second‐order finite difference method (FDM). To accelerate the prediction process and reduce computational cost, an artificial neural network (ANN) model based on TensorFlow is developed using the numerical data set generated from the FDM solutions. The data set is divided into training, validation, and testing subsets to ensure accurate learning and prediction performance. The influence of important physical parameters, including Brinkman number, radiation parameter, Schmidt number, porous‐medium parameter, Grashof number, micropolar parameters, and activation energy, on velocity, temperature, concentration, pressure gradient, pressure rise, and trapping phenomena is examined in detail. The results reveal that thermal radiation reduces fluid temperature, whereas heat generation and viscous dissipation significantly enhance thermal transport. Increasing activation energy elevates the concentration profile due to reduced chemical reaction strength, while larger Schmidt numbers suppress mass diffusion. The ANN predictions exhibit excellent agreement with the numerical solutions with very small prediction errors, confirming the reliability and efficiency of the proposed intelligent computational framework. The present analysis provides important insights into seminal fluid transport mechanisms in the male reproductive tract and offers potential applications in biomedical engineering, reproductive biomechanics, and bio‐inspired microfluidic systems.

Heat Transfer
Islamia University of Bahawalpur (PK), University of Nizwa (OM), College of Applied Sciences, Nizwa (OM)
Affordable and clean energy
Openalex Percentile: Top 12%
Nanofluid Flow and Heat Transfer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.