A data-driven actuator-line methodology for the simulation of high-lift aircraft wake systems
The actuator-line method is here integrated with a data-driven approach for the investigation of aircraft-induced trailing vortices as generated by landing and take-off configurations with varying levels of high-lift device deflections. It is shown that through coupling the Actuator-Line-Method to a suitable Reduced-Order-Model built upon spanwise aerodynamic force distributions obtained from high-fidelity CFD solution data. The resulting wake from the geometry can be reproduced in a manner that no longer requires an explicit representation of the aircraft geometry within the simulation environment. The result is a method that allows for increased fidelity in the vortex farfield when studying the relevant wake dynamics and evolution during take-off, climb, approach and landing. The accuracy of the proposed method is assessed via a direct comparison to traditional high-fidelity nearfield derived results where it was observed that the induced downstream velocity profile and resulting location of vortex structures displayed a satisfactory level of agreement. With the creation of such a method, the effects of variations in aircraft high-lift deployment can be included within the simulation of downstream vortex pairs in a manner that respects the computational limitations of current hardware. • High-lift vortices may be replicated via addition of source terms. • Reduced-Order-Model allows dynamic variations of high-lift devices. • Source based wake study significantly reduces computational cost of wake simulation.
Authors
- Marco Fossati (ORCID: https://orcid.org/0000-0002-1165-5825)
- P. Nagy (ORCID: https://orcid.org/0009-0002-8867-7165)
- Scott Bennie (ORCID: https://orcid.org/0009-0009-9678-1211)
Institutions
- University of Strathclyde (GB)
Publication Details
- Journal
- Computers & Fluids
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1016/j.compfluid.2025.106578
- Primary Topic
- Model Reduction and Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00