Enhancement of Heat Transfer in the Copper Square Duct with Ribs in the Application of Gas Turbine Blade Cooling Systems: A Hybrid Approach

This paper presents a hybrid approach to enhance heat transfer (HT) within a copper square duct for gas turbine (GT) blade cooling systems. The proposed method combines the gannet optimization algorithm (GOA) with the Spiking Deep Residual Network (SDRN), referred to as the GOA-SDRN technique. Since GTs operate at temperatures exceeding metal melting points, internal cooling is crucial to safeguard the blades and extend their lifespan. This study's main goal is to apply rib tubular or turbulence promoters in internal cooling turbine blades, with a focus on managing temperature and maximizing HT to enhance GT blade-cooling systems. To achieve this, the proposed method analyzes the effectiveness of ribs by employing internal rib configurations, subsequently coated with composite nanomaterials such as thermal polymer and titanium carbide powder. The study investigates turbulent flow through the square passage at various Reynolds Numbers (Re), maintains constant ambient hot air temperature, and evaluates the performance of ribs. Specifically, the flow and HT within a square channel, resembling the air-cooled turbine blade cross-section, will be examined. The effectiveness of the GOA-SDRN method will then be assessed using MATLAB and compared against existing methodologies. The proposed method outperforms existing optimization methods significantly, achieving the highest efficiency of 94%, compared to 62% for SSA, 70% for CSA, and 84% for HBO. Additionally, the proposed method exhibits the lowest cost of $35, compared to $67 for SSA, $55 for CSA, and $48 for HBO. In summary, the proposed method offers superior efficiency and cost-effectiveness, making it the preferred choice for the application.