A Loss Model System for Two-Dimensional Compressor Cascades of Modern Controlled Diffusion Airfoils
The early design stage of modern compressors urgently requires high-accuracy, low-cost two-dimensional (2D) cascade loss prediction models. However, existing traditional loss models, predominantly based on early profile data, struggle to accurately predict the performance of modern Controlled Diffusion Airfoils (CDA). This study develops a comprehensive loss model system specifically for 2D cascades with modern CDA profiles. A numerical simulation database, encompassing the entire operating range of various subsonic, transonic, and supersonic profile designs, was first constructed to provide the data foundation for the model system development. Eight critical sub-models essential for the system were then identified based on an analysis of loss sources (including blade surface boundary layers and shock waves). A methodology combining physical mechanism analysis and data-driven techniques was applied to determine the final modeling scheme for each sub-model. Validation results demonstrate that within the parameter space covered by the database, the new model system achieves over 70% higher prediction accuracy compared to the traditional model system, with approximately 95% of prediction errors falling within ±0.02. It also accurately captures the variation trend of loss with incidence angle. The entire model system, consisting of a series of explicit formulas with clear physical meanings, can be easily integrated into compressor design processes and effectively support the design and analysis of airfoils during the preliminary stages of compressor development.
Authors
- Baojie Liu (ORCID: https://orcid.org/0009-0005-1672-4622)
- Xianjun Yu (ORCID: https://orcid.org/0000-0001-6244-7244)
- Guangfeng An (ORCID: https://orcid.org/0000-0002-4978-0066)
- Xiang Yan (ORCID: https://orcid.org/0000-0002-3683-474X)
- Ruoyu Wang (ORCID: https://orcid.org/0000-0002-7091-0291)
Institutions
- Beihang University (CN)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-11-04
- DOI
- https://doi.org/10.3390/app152111759
- Primary Topic
- Turbomachinery Performance and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00