MHD hybrid nanofluid flow and entropy analysis in smooth and wavy channels under non-uniform magnetic field

Tue, 18 Aug 2026 00:00:00 +0000

This study presents a comprehensive numerical investigation of magneto hydrodynamic (MHD) hybrid nanofluid flow in a two-dimensional channel featuring a localized wavy section under the influence of a non-uniform magnetic field. The hybrid nanofluid, composed of Fe₃O₄–Al₂O₃ nanoparticles dispersed in water, is modeled as a single-phase fluid under laminar, steady, and incompressible conditions. The applied transverse magnetic field follows an exponential decay along the channel height, inducing a spatially varying Lorentz force and Joule heating effect. The governing equations are solved using the finite volume method implemented in ANSYS Fluent, with the SIMPLE algorithm employed for pressure–velocity coupling. A comparative analysis between smooth (SC) and wavy (WC) channel configurations is conducted to evaluate the impact of Reynolds number (200 ≤ Re ≤ 800) and magnetic field intensity (1 T ≤ B₀ ≤ 8 T) on flow structure, heat transfer, and thermodynamic irreversibility. The results reveal that the magnetic field significantly suppresses fluid velocity within the magnetized region due to Lorentz force damping, while simultaneously enhancing fluid temperature through Joule heating. Overall, the results demonstrate that the combination of localized wall waviness and a non-uniform magnetic field provides an effective strategy for enhancing heat transfer while minimizing thermodynamic irreversibility. This study offers valuable insights for the design of advanced MHD-based cooling systems and energy applications involving hybrid nanofluids.

Integration of state of health in power management algorithms for hybrid renewable energy systems

Siddharth Joshi, Akash V. Barva, Digesh D. Shah — Wed, 19 Aug 2026 00:00:00 +0000

This paper proposes a State of Health (SOH)—aware power management framework for a hybrid renewable energy system integrating solar photovoltaic, wind energy, and battery energy storage systems. Unlike conventional strategies that rely solely on State of Charge, the proposed approach embeds SOH as an active control variable within the power management algorithm to adapt battery dispatch based on degradation state. Real-world solar and wind datasets, along with experimentally obtained battery degradation data, are used for system evaluation. Simulation results demonstrate that incorporating SOH reduces battery stress, limits excessive cycling under degraded conditions, and improves long-term system reliability. The proposed framework enables lifecycle-aware energy management, enhancing the sustainability and operational resilience of hybrid renewable energy systems.

Transactions on Energy Systems and Engineering Applications

MHD hybrid nanofluid flow and entropy analysis in smooth and wavy channels under non-uniform magnetic field

Integration of state of health in power management algorithms for hybrid renewable energy systems