Mustafa Bayram
7005821294
Publications - 4
Unraveling the Bäcklund Transformation and Interaction Phenomena in Nonlinear Dispersive Media Describing Combined pKP-BKP System in (3+1) Dimensions
Publication Name: Journal of Nonlinear Mathematical Physics
Publication Date: 2026-12-01
Volume: 33
Issue: 1
Page Range: Unknown
Description:
This work studies the exact solutions of the integrable (3+1)-dimensional combined potential Kadomtsev-Petviashvili (pKP) equation with the B-type Kadomtsev-Petviashvili (BKP) equation, which is used to characterize several nonlinear oscillations occurring in hydrodynamics, plasma physics, and nonlinear optics. A bilinear representation of the pKP-BKP model is used to study the properties of different wave solutions. A variety of ansatzes are utilized to derive lump cross-kink waves, lump cross-periodic waves, rogue waves, as well as two, three, and multi-wave solutions pertinent to the model. In addition, a traveling wave transformation is applied to transform the problem into an ordinary differential equation. The new auxiliary equation methodology yields solutions including rational, exponential, hyperbolic, and trigonometric functions. Graphical visualizations using 2D plots, contour plots, and 3D plots show the dynamics of the obtained solutions. These solutions are of great importance in nonlinear fiber optics and telecommunications, which contribute to our understanding of the fundamental physical models.
Open Access: Yes
Intelligent predictive neural network analysis of stefan blowing impacts on chemical reactive flow of Boger nanofluid with thermophoresis and brownian motion
Publication Name: Discover Nano
Publication Date: 2026-12-01
Volume: 21
Issue: 1
Page Range: Unknown
Description:
This study scrutinizes the effect of thermal radiation and Stefan blowing on the chemical reactive flow of Boger nanofluid across a stretched sheet with Darcy Forchheimer medium and heat generation using an intelligent computational framework based on Artifice neural network—Bayesian regularization. Furthermore, Brownian motion and thermophoresis properties have been examined. The suggested model of how Stefan blowing affects the chemical reactive flow of a Boger nanofluid with thermophoresis effects and Brownian motion has useful applications in a number of industrial and engineering operations. In chemical reactors, nano-coating technologies, and polymer processing, this model is essential for improving heat and mass transport processes. While the Boger nanofluid model accurately depicts non-Newtonian behaviour pertinent to biofluids and complex lubricants, Stefan blowing consideration offers insights on evaporation or suction effects. For the purpose of maximizing nanoparticle dispersion in cooling systems, fuel cells, and medicinal devices like targeted drug delivery systems where exact control over particle motion and chemical reactivity is crucial, Brownian motion and thermophoresis are also critical. The velocity profile improves as the Stefan blowing parameter values rise, but the thermal and concentration profiles decrease.
Open Access: Yes
Thermal characteristics of magnetic blood-based hexa-hybrid nanofluids in stenotic arteries with heat source/sink by applying Caputo-Fabrizio fractional derivatives
Publication Name: Results in Surfaces and Interfaces
Publication Date: 2026-08-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
The current examination explores the magnetohydrodynamic flow and transport behavior of a Casson-based blood-derived hexa-hybrid nanofluid via a vertically oriented, mildly stenotic artery using a fractional-order framework. The hexa-hybrid nanofluid is formulated by dispersing Au, Cu, ZnO, Ag, MgO and TiO2 nanoparticles into blood, and the flow is considered highly pulsatile. Mathematical modelling is developed from the conservation laws of mass, momentum, and energy, followed by nondimensionalization under the mild-stenosis approximation. To extend the classical model to its fractional form, the Caputo–Fabrizio fractional derivative is incorporated, enabling closed-form analytical expressions for velocity and temperature through combined Laplace and Hankel transforms. The graphical results highlight the influence of key physical factors on velocity, temperature, and entropy production. The inclusion of hexa-hybrid nanoparticles notably enhances the thermal characteristics of blood due to the substantial rise in effective thermal conductivity. The velocity increases with higher Casson parameter values, whereas temperature decreases as the fractional-order parameter intensifies. Furthermore, entropy generation is found to rise with increasing thermodynamic parameters, while the Bejan number correspondingly decreases, reflecting dominant irreversibility effects within the system.
Open Access: Yes
Artificial intelligence-driven performance analysis of carbon nanotubes hybrid nanofluid with wastewater treatment applications: an intelligent neuro-computing model
Publication Name: South African Journal of Chemical Engineering
Publication Date: 2026-07-01
Volume: 57
Issue: Unknown
Page Range: Unknown
Description:
The current study examines the properties of heat radiation on the Darcy Forchheimer flow of carbon nanotube/water based hybrid nanofluid across a Riga plate in the occurrence of oxytactic microbes, employing a novel intelligent numerical computing paradigm based on the legacy of neural networks with the intelligent Bayesian regularization (NN-IBR) method. The AI-driven neuro-computing model for improving the thermal behavior of a carbon nanotube (CNT) hybrid nanofluid in wastewater treatment has a wide range of applications. It has the potential to dramatically improve thermal management efficiency in wastewater treatment plants, improve pollutant removal through optimal heat and mass transfer, and minimize energy consumption in treatment operations. This model can also be used in sustainable water recycling, industrial effluent treatment, and smart environmental management systems, where intelligent prediction and control of nanofluid performance is critical for accomplishing environmentally friendly and cost-effective operations. The Homotopy analysis approach is used to classify the obtained equations. The concentration profile increases as the activation energy parameter values upsurge.
Open Access: Yes
