Maddina Dinesh Kumar^1,#, S. U. Mamatha², Khalid Masood³, Nehad Ali Shah^4,#, Se-Jin Yook^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074680 - 29 January 2026

Abstract Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces. The trapezoidal cavity form is compared with its thermal and flow performance, and it is revealed that trapezoidal fins tend to be more efficient, particularly when material optimization is critical. Motivated by the increasing need for sustainable energy management, this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid. The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties; hence, optimising these properties… More >

Muhammad Hamzah¹, Muhammad Ramzan^2,*, Abdulrahman A. Almehizia³, Ibrahim Mahariq^4,5,6,7,8,*, Laila A. Al-Essa⁹, Ahmed S. Hassan¹⁰

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.070435 - 29 January 2026

Abstract The present investigation inspects the unsteady, incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO2 (silicon dioxide), ZnO (zinc oxide), and MWCNT (multi-walled carbon nanotubes) suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates. This problem is important because it helps us understand the complicated connections between magnetic fields, nanofluid dynamics, and heat transport, all of which are critical for designing thermal management systems. These findings are especially useful for improving the design of innovative cooling technologies in electronics, energy systems, and healthcare applications. No prior study has… More >

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 >