TY - JOUR
T1 - A New Tilt-Arm Transitioning Unmanned Aerial Vehicle: Introduction and Conceptual Design
AU - Zeng, C
AU - Abnous, Rosa
AU - Chowdhury, Souma
AU - Maldonado, Victor
PY - 2020/2/12
Y1 - 2020/2/12
N2 - In this paper, a novel hybrid unmanned aerial vehicle (UAV) concept is developed. ThisUAV is capable of transitioning between VTOL, hover, and efficient (fixed-wing type) forwardflight. The overall configuration comprises a blended-wing-body, with two rotor arms mountedat the two wing tips using span-wise shafts; the arms can rotate about the span-wise axis, andeach contains two propellers at its two ends. A conceptual design automation framework isdeveloped, comprising mass and balance analysis, aerodynamic analysis and optimization. VortexLattice Method (VLM) is used to perform the aerodynamic analysis. Furthermore, usingwind distribution models, redundancy modeling, and probabilistic UAV airspeed constraintsderived thereof, a robust design optimization formulation is presented to explore the missionenvelop flexibility of this new hybrid UAV. Mixed-discrete Particle Swarm Optimization is usedto identify optimum geometry and component choices.
AB - In this paper, a novel hybrid unmanned aerial vehicle (UAV) concept is developed. ThisUAV is capable of transitioning between VTOL, hover, and efficient (fixed-wing type) forwardflight. The overall configuration comprises a blended-wing-body, with two rotor arms mountedat the two wing tips using span-wise shafts; the arms can rotate about the span-wise axis, andeach contains two propellers at its two ends. A conceptual design automation framework isdeveloped, comprising mass and balance analysis, aerodynamic analysis and optimization. VortexLattice Method (VLM) is used to perform the aerodynamic analysis. Furthermore, usingwind distribution models, redundancy modeling, and probabilistic UAV airspeed constraintsderived thereof, a robust design optimization formulation is presented to explore the missionenvelop flexibility of this new hybrid UAV. Mixed-discrete Particle Swarm Optimization is usedto identify optimum geometry and component choices.
M3 - Article
JO - Aerospace Science and Technology
JF - Aerospace Science and Technology
SN - 1270-9638
ER -