Investigation in cooling performance and structural optimization for typical fractal units in turbine blades

Abstract

Fractal structures exhibit remarkable integrated performance due to their extremely high surface-to-volume ratio and adaptability. However, the exceedingly high degree of freedom in fractal designs introduces numerous geometric control variables, thereby complicating topological optimization. This study proposes a novel construction method for fractal structures and conducts flow and heat transfer analyses on various topological configurations of fractal units. Furthermore, intelligent algorithms are employed to perform topological optimization on typical fractal units. The results indicate that the performance of fractal units is predominantly influenced by bifurcation parameters and flow channel numbers. The heat transfer efficiency and pressure drop of fractal units increase with higher bifurcation numbers and angles. Meanwhile, the convergence of multiple fluid streams within the channels leads to significant pressure losses. An increase in flow channel numbers can enhance heat transfer while reducing pressure loss. Although increasing the complexity of the fractal topology improves heat transfer performance, this enhancement is insufficient to offset the adverse effects of increased pressure loss. Optimization using genetic algorithms yielded representative optimal structures which, under identical heat transfer performance, exhibited only 58 % of the original pressure drop. This finding indicates that employing intelligent algorithms is effective for achieving efficient topological optimization of fractal structures.