Nikhil S. Mane¹, Sheetal Kumar Dewangan^2,*, Sayantan Mukherjee³, Pradnyavati Mane⁴, Deepak Kumar Singh¹, Ravindra Singh Saluja⁵

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.072090 - 10 November 2025

Abstract The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids. Researchers rely on experimental investigations to explore nanofluid properties, as it is a necessary step before their practical application. As these investigations are time and resource-consuming undertakings, an effective prediction model can significantly improve the efficiency of research operations. In this work, an Artificial Neural Network (ANN) model is developed to predict the thermal conductivity of metal oxide water-based nanofluid. For this, a comprehensive set of 691 data points was collected from the literature. This dataset is split More >

Asgar Ali^1,*, Nayan Sardar², Poly Karmakar³, Sanatan Das⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3563-3626, 2025, DOI:10.32604/cmes.2025.074082 - 23 December 2025

Abstract Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics, offering immense potential in energy conversion, biomedical transport, and electromagnetic flow control systems. Understanding their dynamic behavior under coupled magnetic, rotational, and reactive effects is crucial for the development of efficient thermal management technologies. This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO₂–H₂O hybrid nanofluid flowing through a squarely elevated Riga tunnel. The governing model incorporates Hall and ion-slip effects, thermal radiation, and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces. Closed-form analytical… More >

Adnan Ashique^1,#, Khalid Masood², Usman Afzal¹, Mati Ur Rahman², Maddina Dinesh Kumar³, Sohaib Abdal³, Nehad Ali Shah^1,#,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3627-3699, 2025, DOI:10.32604/cmes.2025.072523 - 23 December 2025

Abstract This study outlines a quantitative and data-driven study of the mixed convection heat transfer processes that concern Cu-water nanofluids in a Γ-shaped enclosure with one to five rotating cylinders. The dimensionless equations of mass, momentum, and energy are solved using the finite element method as implemented in the COMSOL Multiphysics 6.3 software in different rotating Reynolds numbers and cylinder geometries. An artificial Neural Network that is trained using Bayesian Regularization on data produced by the COMSOL is utilized to estimate the average Nusselt numbers. The analysis is conducted for a wide range of rotational… More >

Arshad Riaz^1,*, Misbah Ilyas¹, Muhammad Naeem Aslam², Safia Akram³, Sami Ullah Khan⁴, Ghaliah Alhamzi⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3481-3509, 2025, DOI:10.32604/cmes.2025.072513 - 23 December 2025

Abstract Peristaltic transport of non-Newtonian nanofluids with double diffusion is essential to biological engineering, microfluidics, and manufacturing processes. The authors tackle the key problem of Sisko nanofluids under double diffusion convection with thermal radiations and electroosmotic effects. The study proposes a solution approach by using Morlet-Wavelet Neural Networks that can effectively solve this complex problem by their superior ability in the capture of nonlinear dynamics. These convergence analyses were calculated across fifty independent runs. Theil’s Inequality Coefficient and the Mean Squared Error values range from 10⁻⁷ to 10⁻⁵ and 10⁻⁷ to 10⁻¹⁰, respectively. These values showed the proposed More >

Faiza Benabdallah¹, Kaouther Ghachem¹, Walid Hassen², Haythem Baya², Hind Albalawi³, Lioua Kolsi^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1839-1861, 2025, DOI:10.32604/cmes.2025.071678 - 26 November 2025

Abstract Current developments in magnetohydrodynamic (MHD) convection and nanofluid engineering technology have have greatly enhanced heat transfer performance in process systems, particularly through the use of carbon nanotube (CNT)–based fluids that offer exceptional thermal conductivity. Despite extensive research on MHD natural convection in enclosures, the combined effects of complex obstacle geometries, magnetic fields, and CNT nanofluids in three-dimensional configurations remain insufficiently explored. This research investigates MHD natural convection of carbon nanotube (CNT)-water nanofluid within a three-dimensional cavity. The study considers an inclined cross-shaped hot obstacle, a configuration not extensively explored in previous works. The work aims… More >

Mairaj Bibi¹, Muhammad Shoaib Arif ², Yasir Nawaz³, Nabil Kerdid^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 537-569, 2025, DOI:10.32604/cmes.2025.070362 - 30 October 2025

Abstract This study develops a high-order computational scheme for analyzing unsteady tangent hyperbolic fluid flow with variable thermal conductivity, thermal radiation, and coupled heat and mass transfer effects. A modified two-stage Exponential Time Integrator is introduced for temporal discretization, providing second-order accuracy in time. A compact finite difference method is employed for spatial discretization, yielding sixth-order accuracy at most grid points. The proposed framework ensures numerical stability and convergence when solving stiff, nonlinear parabolic systems arising in fluid flow and heat transfer problems. The novelty of the work lies in combining exponential integrator schemes with compact… More >

Shaik Mohammed Ibrahim¹, Bhavanam Naga Lakshmi², Chundru Maheswari³, Hasan Koten^4,*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1555-1574, 2025, DOI:10.32604/fhmt.2025.069392 - 31 October 2025

Abstract Magnetohydrodynamic (MHD) radiative chemically reactive mixed convection flow of a hybrid nanofluid (Al₂O₃–Cu/H₂O) across an inclined, porous, and stretched sheet is examined in this study, along with its unsteady heat and mass transport properties. The hybrid nanofluid’s enhanced heat transfer efficiency is a major benefit in high-performance engineering applications. It is composed of two separate nanoparticles suspended in a base fluid and is chosen for its improved thermal properties. Thermal radiation, chemical reactions, a transverse magnetic field, surface stretching with time, injection or suction through the porous medium, and the effect of inclination, which introduces gravity-induced… More >

Pennelli Saila Kumari¹, Shaik Mohammed Ibrahim^1,*, Prathi Vijaya Kumar², Giulio Lorenzini^3,*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1639-1660, 2025, DOI:10.32604/fhmt.2025.069063 - 31 October 2025

Abstract In this paper, the authors examine various slip effects on the magnetic field and thermal radiative impacts on the flow, mass and heat transfer of a Jeffrey nanofluid over a 2-dimensional inclined stretching sheet by a porous media. The offered work is modelled to be in the form of a combination of coupled highly nonlinear partial differential equations in dimensional contexts. Governing equations were obtained, dimensionless parameters were defined in terms of similarity parameters, and the solutions were obtained by the Homotopy Analysis Method (HAM). The analysis is significant as the effects of viscosity are… More >

Barkilean Jaismitha¹, Jagadeesan Sasikumar^2,*, Samad Noeiaghdam^3,*, Unai Fernandez-Gamiz⁴, Thirugnanasambandam Arunkumar¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1529-1554, 2025, DOI:10.32604/fhmt.2025.067869 - 31 October 2025

Abstract The present study investigates the dynamic behavior of a ternary-hybrid nanofluid within a tapered asymmetric channel, focusing on the impact of unsteady oscillatory flow under the influence of a magnetic field. This study addresses temperature-sensitive water transport mechanisms relevant to industrial applications such as thermal management and energy-efficient fluid transport. By suspending nanoparticles of diverse shapes-platelets, blades, and spheres in a hybrid base fluid comprising cobalt ferrite, magnesium oxide, and graphene oxide, the study examines the influence of both small and large volume fraction values. The governing equations are converted into a dimensionless form. With More >

Banan Najim Abdullah¹, Karam Hashim Mohammed¹, Ammar Hassan Soheel¹, Bashar Mahmood Ali², Omar Rafae Alomar^1,*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1681-1700, 2025, DOI:10.32604/fhmt.2025.066814 - 31 October 2025

Abstract The current work aims to numerically investigate the impact of using (50% ZnO and 50% Al₂O₃) hybrid nanofluid (HNf) on the performance of convective heat transfer inside a horizontal wavy micro-channel. This issue represents a novel approach that has not been extensively covered in previous research and provides more valuable insights into the performance of HNfs in complex flow geometries. The conjugate heat transfer approach is used to demonstrate the influence of adding hybrid nanoparticles (50% Al₂O₃ and 50% ZnO) to pure water on the rate of heat transfer. The governing equations are numerically solved by… More >