Predicting Quadcopter Noise With The Lattice-Boltzmann Method

From small delivery Unmanned Aircraft Systems (UAS) to short-haul building-to-building aircraft, urban air mobility is gaining traction as a new approach to tackle the problem of transportation in densely populated areas. NASA’s vision for vertical lift vehicles is to capitalize on and improve unique capabilities to greatly benefit the United States’ growing civil flight requirements. This vision is embodied in the Revolutionary Vertical Lift Technology (RVLT)project [1]. Beyond safety, one of the chief concerns of communities where drones are becoming more popular is the noise they generate. Noise will undoubtedly be one of the major obstacles to public acceptance of any new urban air mobility technology. The ability to predict the acoustics of new conceptual aircraft with multiple rotors and complex fuselages is critical to enable the creation of quieter designs. The objective of this research is to build up a better physical understanding of the noise generated by a typical quadcopter drone and what it takes to predict it from first principles using computational fluid dynamics (CFD) with the Lattice-Boltzmann method (LBM). The specific goals are to establish best practices to predict multi-rotor and vehicle interaction noise with LBM, validate these predictions by comparing to wind tunnel measurements, and assess the computational cost necessary to obtain accurate predictions.