Affiliation:
1. California Institute of Technology, Pasadena, CA, USA
Abstract
As small Uninhabited Aerial Vehicles (sUAS) increase in popularity, computational analysis is increasingly being used to model and improve their performance. However, although propeller performance is one of the primary elements in modelling an aircraft, most manufacturers of propellers for this size of vehicle do not publish geometric information for the propeller. The lack of available geometric data makes simulation of propeller aerodynamics challenging. While techniques exist to accurately extract the 3D geometry of a propeller, these methods are often very expensive, time-consuming, or labor intensive. Additionally, typical 3D scanning techniques produce a 3D mesh that is not useful for techniques such as Blade Element Theory (BET), which rely on knowledge of the 2D cross sections along the propeller span. This paper describes a novel workflow to produce point clouds using readily available photo equipment and software and subsequently extract airfoil and propeller blade parameters at specified stations along the propeller span. The described process can be done with little theoretical knowledge of photogrammetry and with minimal human input. The propeller geometry generated is compared against results of established methods of geometry extraction and good agreement is shown.
Funder
NDSEG Fellowship, Air Force Office of Scientific Research
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