This paper presents a numerical study of natural convection in an annular cavity filled with a hybrid nanofluid under the influence of a magnetic field. This study is significant for applications requiring enhanced thermal management, such as in heat exchangers, electronics cooling, and energy systems. The inner cylinder, equipped with fins and subjected to uniform volumetric heat generation, contrasts with the adiabatic outer cylinder. This study aims to investigate how different nanoparticle combinations (Fe₃O₄ with Cu, Ag, and Al₂O₃) and varying Hartmann and Rayleigh numbers impact heat transfer efficiency. The finite volume method is employed to solve the governing equations, with simulations conducted using Fluent 6.3.26. Parameters such as volume fraction (ϕ₂ = 0.001, 0.004, 0.006), Hartmann number (0 ≤ Ha ≤ 100), Rayleigh number (3 × 10³ ≤ Ra ≤ 2.4 × 10⁴), and fin number (N = 0, 2, 4, 6, 8) are analyzed. Streamlines, isotherms, and induced magnetic field contours are utilized to assess flow structure and heat transfer. The results reveal that increasing the Rayleigh number and magnetic field enhances heat transfer, while the presence of fins, especially at N = 2, may inhibit convection currents and reduce heat transfer efficiency. These findings provide valuable insights into optimizing nanofluid-based cooling systems and highlight the trade-offs in incorporating fins in thermal management designs.

In this article, we present an investigative study on the often-overlooked partial wake phenomenon in previous studies concerning wind farm configurations. A partial wake occurs when a portion of the actuator disk of a downstream wind turbine is affected by the wake of another upstream turbine. This phenomenon occurs in addition to the full wake, where the entire upstream turbine is affected by the wake of the frontal turbine, also leading to a decrease in wind speed and consequently a reduction in power production. The proposed study is based on measuring the power generated by the area swept by the wake of an array of turbines in a wind farm. To accomplish this, we integrate the linear wake model of Jensen, the specifications of the ENERCON E2 wind turbine, and the wind farm data into Matlab-developed software (version 18) to perform the calculations. In a concrete application, this proposed method is validated by reproducing the previous works that neglected the partial wake in wind farm configurations. The simulation results obtained are analyzed, compared, and discussed under similar operational conditions.