The energy and mass transference through ternary nanofluid (TNF) over a stretching spinning sheet is estimated in the present study. The TNF has been prepared by the distribution of magnesium oxide (MgO), titanium dioxide (TiO2), and cobalt ferrite (CoFe2O4) nanoparticles (NPs) in water. The study of the TNF over a rotating stretching sheet can be directly used in optimizing the performance of solar thermal collector, high-power electronics cooling, and aerospace heat shields. Such flow has a vital role in the optimization of lubrication processes and nuclear reactor cooling in which high thermal conductivity and centrifugal flow manipulation is needed. The TNF flow has been calculated under the consequence of mixed convection, thermal radiation, constant and exponential heat source/sink, magnetic field, and porous medium. The flow scenario is mathematically stated in the form of a nonlinear system of PDEs (partial differential equations). The set of PDEs is transfigured into the non-dimensional system of ODEs (ordinary differential equations), by means of the similarity variables. The results are obtained through the bvp4c code (Matlab built-in package). The percent error between present and published study at Pr =5.0 is 0.0034541%, which ensure the accuracy of the proposed model and applied methodology. The energy transfer rate drops by up to 20.4049%, 25.5465% and 32.4766% by varying the exponential heat source/sink factor from -1.0 t0 1.0 in case of nano, hybrid and ternary nanofluid respectively. The transfer rate enhances up to 52.7911% and 51.2236% by varying heat radiation and Dufour number from 1.0 to 3.0 and 1.5 to 3.5 in case of THNF, respectively.

Buoyancy-driven viscous fluid flow across a curved surface is investigated numerically in this work using the coupled Maxwell and Navier–Stokes equations, with variable fluid characteristics represented as nonlinear functions of temperature. Realistic magneto-hydrodynamic effects are captured by including the Lorentz force and the influence of a fluctuating magnetic field in curvilinear coordinates. The governing partial differential equations are solved using the parametric continuation method (PCM) after being converted into a system of ordinary differential equations by similarity transformations. Results demonstrate excellent agreement when compared to previously published data using MATLAB's PCM solver to confirm correctness. According to the parametric study, buoyancy ((Formula presented.)) improves fluid motion by around 15%, whereas greater curvature factors (Formula presented.), Stuart numbers (Formula presented.), and Prandtl numbers (Formula presented.) result in a 12%–16% drop in radial and arc-length velocities. The temperature profile falls by more than 23% as (Formula presented.) and (Formula presented.) increase, indicating the significance of thermal diffusivity in preventing heat buildup. It increases by 25% with higher magnetic interaction ((Formula presented.), (Formula presented.)). The induced magnetic field is strengthened by 6%–7% with a little increase in the magnetic interaction parameter (Formula presented.), whereas the magnetic field intensity is reduced by about 25% with a larger (Formula presented.). Skin friction falls by almost 10% with greater (Formula presented.) at moderate (Formula presented.), but increases by 4% under larger Lorentz forces ((Formula presented.), (Formula presented.)). Overall, the results show that velocity, temperature, magnetic field distribution and surface forces are strongly influenced by buoyancy, curvature and electromagnetic parameters. The findings shed light on efficient energy optimisation, thermal control, and electromagnetic regulation of MHD flows over curved geometries.

The Riga plate is a magnetized surface that influences fluid motion and boundary layer properties. It plays an important role in heat transfer, industrial processes, and aerodynamics. This study investigates the unsteady flow of a micropolar hybrid nanofluid (MHNF) over a Riga plate. The base-fluid sodium alginate (SA) has been used in the preparation of a hybrid nanofluid (HNF) consisting of CeO2 (cerium oxide) and Al2O3 (aluminum oxide) nanoparticles (NPs). The modeled equations are transformed into a dimensionless form via similarity transformations, and the resulting equations are then numerically solved using the PCM (parametric continuation method). The influence of numerous parameters on velocity, microrotation, energy, and fluid concentration profiles is demonstrated and explained using tables and figures. Results for skin friction, energy, and mass transmission rate are also provided. Comparisons to the published data corroborate the method’s accuracy. The skin friction reduces by up to 95.1263% and 34.4699%, respectively, as the velocity slip factor and the Hartmann number are varied from 0.1 to 1.0 and 1.0 to 4.0, respectively. The energy and fluid concentration transfer rates increase by up to 21.1823% and 32.4299%, respectively, as the thermal and concentration slip parameters are varied from 0.1 to 1.4 and 0.5 to 2.0, respectively. These findings have substantial significance for a wide range of engineering applications, particularly in improving heat and mass transfer processes in industrial operations, engineering, and nanotechnology.