Multiobjective optimization of transpiration cooling in hypersonic laminar flow using a genetic algorithm approach

• Published in: Aerospace science and technology Vol. 153; p. 109414
• Main Authors: Hoseinzade, Davood, Kim, Ikhyun
• Format: Journal Article
• Language: English
• Published: Elsevier Masson SAS 01.10.2024
• Subjects: Blowing ratio; Hypersonic laminar flow; Multiobjective optimization genetic algorithm; Transpiration cooling; Blowing ratio; Multiobjective optimization genetic algorithm; Transpiration cooling; Hypersonic laminar flow
• ISSN: 1270-9638
• DOI: 10.1016/j.ast.2024.109414

•This research elaborates on the application of multiobjective genetic algorithms to optimize the transpiration cooling blowing ratio for hypersonic vehicles.•A multiobjective genetic algorithm is employed to determine the optimal blowing ratio based on an experimental correlation.•Average thermal effectiveness, coolant reservoir volume, and length of cooling were considered as objectives for the optimization process.•This approach can be applied to the entire trajectory of hypersonic vehicles, where the variables are constantly changing. The efficient utilization of transpiration cooling is crucial for addressing coolant consumption challenges in hypersonic vehicle design. This study focuses on optimizing the blowing ratio, a key parameter in transpiration cooling. A multiobjective genetic algorithm is employed to determine the optimal blowing ratio using an experimental correlation. The optimization objectives include average thermal effectiveness, length of cooling with thermal effectiveness greater than 0.5, and coolant reservoir volume over a 60 s duration cooling process. The results reveal that a blowing ratio of 0.108 % is the optimal point, with corresponding values for average thermal effectiveness, coolant reservoir volume, and length of cooling being 0.493, 7.093 m³, and 0.14 m, respectively. A comparison with the maximum experimental blowing ratio indicates a 56.61 % reduction in average thermal effectiveness, accompanied by a 56.68 % decrease in coolant reservoir volume. This study highlights the application of multiobjective genetic algorithms in optimizing the transpiration cooling blowing ratio for hypersonic vehicles.