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<p>The conversion of solar radiation into thermal energy has gained significant interest due to the rising demand for renewable energy. Tri-hybrid nanofluid (THNF) flow across curved Riga surfaces can enhance solar-thermal system efficiency in solar aircraft by improving heat transfer capabilities. In light of this importance, this study examines the THNF flow over a curved Riga surface with the impact of heat source and thermal radiation, focusing on enhancing thermal conductivity and thermal transfer efficiency. The enhancement is achieved by incorporating cobalt ferrite, cadmium telluride, and tantalum nanoparticles into a water-based fluid. The governing equations are transformed using appropriate similarity transformation procedures, and the 4th-order Runge–Kutta approach is introduced along with the shooting method to determine the unknown initial condition for solving the system of equations. A novel aspect of this research is the enhancement of rate coefficients, which is achieved through neural network-driven regression modeling, utilizing the Levenberg–Marquardt optimization technique. The findings reveal that the revised Hartmann number significantly increases the velocity distribution, while curvature parameters have an opposing effect on the temperature profile. For the tri-hybrid nanofluid case, the heat transfer rate is enhanced by approximately 33% with increasing thermal radiation and about 39% with rising curvature parameter, indicating a significant improvement in thermal performance. These results offer valuable insights for optimizing heat management techniques in solar aircraft systems, contributing to improved energy efficiency and system performance.</p>

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Neural network modeling of magnetized tri-hybrid nanofluid flow over a curved surface for solar aircraft thermal management

  • 期刊论文

  • 发表日期：

    2026年5月15日

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  • Abhishek Sharma,
  • Ram Prakash Sharma,
  • Thirupathi Thumma

摘要

The conversion of solar radiation into thermal energy has gained significant interest due to the rising demand for renewable energy. Tri-hybrid nanofluid (THNF) flow across curved Riga surfaces can enhance solar-thermal system efficiency in solar aircraft by improving heat transfer capabilities. In light of this importance, this study examines the THNF flow over a curved Riga surface with the impact of heat source and thermal radiation, focusing on enhancing thermal conductivity and thermal transfer efficiency. The enhancement is achieved by incorporating cobalt ferrite, cadmium telluride, and tantalum nanoparticles into a water-based fluid. The governing equations are transformed using appropriate similarity transformation procedures, and the 4th-order Runge–Kutta approach is introduced along with the shooting method to determine the unknown initial condition for solving the system of equations. A novel aspect of this research is the enhancement of rate coefficients, which is achieved through neural network-driven regression modeling, utilizing the Levenberg–Marquardt optimization technique. The findings reveal that the revised Hartmann number significantly increases the velocity distribution, while curvature parameters have an opposing effect on the temperature profile. For the tri-hybrid nanofluid case, the heat transfer rate is enhanced by approximately 33% with increasing thermal radiation and about 39% with rising curvature parameter, indicating a significant improvement in thermal performance. These results offer valuable insights for optimizing heat management techniques in solar aircraft systems, contributing to improved energy efficiency and system performance.