Aerodynamic and aeroacoustic comparison of optimized high-speed propeller blades
Paper in proceeding, 2018

The Boxprop is a high-speed propeller concept intended for aircraft engines, which features blade pairs connected at the tip in order to decrease tip vortex strength, possibly reducing noise and improving aerodynamic performance relative to conventional high-speed propellers. This paper investigates the aerodynamic and aeroacoustic performance of three aerodynamically optimized high speed propellers; a 6-bladed conventional propeller, a 12-bladed conventional propeller, and a 6-bladed Boxprop. Performance results will be be compared for the three designs, with a focus on sectional performance and wake flow characteristics, and will show that the 6-bladed Boxprop performance lies somewhat in-between its 6 and 12-bladed conventional counterparts. The noise level at various observer positions is presented, and shows that the noise roughly follows the values of efficiency for the three propellers, with the Boxprop noise level being higher than the 12-bladed conventional propeller, but lower than the 6-bladed one. The lower blade loading and higher efficiency of the Boxprop relative to the 6-bladed conventional propeller results in slightly lower levels of noise at cruise.

Author

Alexandre Capitao Patrao

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Daniel Lindblad

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Anders Lundbladh

Chalmers, Mechanics and Maritime Sciences (M2)

Tomas Grönstedt

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

2018 Joint Propulsion Conference

AIAA 2018-4658
978-162410570-8 (ISBN)

54th AIAA/SAE/ASEE Joint Propulsion Conference, 2018
Cincinnati, OH, USA,

Innovativ Framdrivning och Motorinstallation

VINNOVA (2013-01189), 2013-07-01 -- 2017-06-30.

Driving Forces

Sustainable development

Areas of Advance

Transport

Subject Categories

Aerospace Engineering

Vehicle Engineering

Signal Processing

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.2514/6.2018-4658

More information

Latest update

7/9/2019 7