On the prediction of noise generated by urban air mobility (UAM) vehicles. Part 2. Implementation of the Farassat F1A formulation into a modern surface-vorticity panel solver
Abstrak
This study focuses on the integration of established acoustic prediction techniques directly into a surface-vorticity solver. The main objective is to enhance an aircraft designer's ability to characterize the acoustic signatures generated by urban air mobility (UAM) vehicles in general, and Distributed Electric Propulsion (DEP) concepts in particular, including Unmanned Aerial Vehicles (UAVs). Our solver consists of a reliable, surface-vorticity panel code that incorporates viscous boundary-layer corrections. It thus offers a computationally efficient commercial tool for conceptual design and preliminary aerodynamic analysis. By implementing the Farassat F1A acoustics formulation directly into the solver, a new intuitive capability is achieved, which is both conversive with modern engineering tools and efficient in setup and speed of execution. Besides its application to the X-57 High-Lift Propeller and the Revolutionary Vertical Lift Technology (RVLT) Tiltwing electric Vertical Take-Off and Landing (eVTOL) vehicle by the National Aeronautics and Space Administration (NASA), this capability is systematically demonstrated using three particular case studies. These consist of both single- and six-propeller Joby S4 eVTOL as well as a small eight-propeller Kittyhawk KH-H1 DEP vehicle. Whereas the details of this tool and underlying equations are showcased in this article, the acoustic metrics that can be effectively used to characterize the noise level generated by a UAM in flight are described in a companion article. By embedding this assortment of insightful metrics into a simple and user-friendly flow solver, a much improved flow-acoustic analysis capability is thereby provided to support the design of future aircraft.
Penulis (4)
Vivek Ahuja
Daniel S. Little
J. Majdalani
R. Hartfield
Format Sitasi
Akses Cepat
- Tahun Terbit
- 2022
- Bahasa
- en
- Total Sitasi
- 14×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1063/5.0105002
- Akses
- Open Access ✓