TY - GEN
T1 - Aerodynamic modeling and optimization of a blended-wing-body transitioning UAV
AU - Zeng, Chen
AU - Abnous, Rosa
AU - Chowdhury, Souma
N1 - Publisher Copyright:
© 2017 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2017
Y1 - 2017
N2 - In this paper, the aerodynamic analysis and optimization of a new transitioning unmanned aerial vehicle (UAV) is presented. This UAV is capable of VTOL, hover, efficient (fixed-wing type) forward flight, and flight states in-between. The overall configuration comprises a blended-wing-body (which facilitates desirable weight distribution and flight efficiency), with two rotor arms mounted at the two wing tips using span-wise shafts; the arms can rotate about the span-wise axis, and each contains two propellers at its two ends (4 propellers in total). A Vortex Lattice (VL) method is used to perform the aerody- namic analysis; appropriate airfoil choices and number of panels in the VL method are established. The lift and drag forces computed are used to estimate forward flight range and endurance (assuming battery-powered flight), by leveraging typical momentum theory formulations. Since, a hybrid UAV such as BITU is expected to provide the flexibility of flying in varying wind conditions, diverse wind scenarios are taken into consideration here. Uncertainties associated with wind conditions are addressed by taking a typical and worst case scenario perspective, and introducing carefully tailored redundancies during the mod- eling and optimization formulation process. Optimization studies, using a mixed-integer Particle Swarm Optimization algorithm, are performed to separately maximize forward- flight range, subject to various aerodynamic and geometric constraints. Interestingly, the optimization converges to distinct designs under calm, windy, and stormy wind scenarios, with flight ranges going from about 163 km to about 54 km.
AB - In this paper, the aerodynamic analysis and optimization of a new transitioning unmanned aerial vehicle (UAV) is presented. This UAV is capable of VTOL, hover, efficient (fixed-wing type) forward flight, and flight states in-between. The overall configuration comprises a blended-wing-body (which facilitates desirable weight distribution and flight efficiency), with two rotor arms mounted at the two wing tips using span-wise shafts; the arms can rotate about the span-wise axis, and each contains two propellers at its two ends (4 propellers in total). A Vortex Lattice (VL) method is used to perform the aerody- namic analysis; appropriate airfoil choices and number of panels in the VL method are established. The lift and drag forces computed are used to estimate forward flight range and endurance (assuming battery-powered flight), by leveraging typical momentum theory formulations. Since, a hybrid UAV such as BITU is expected to provide the flexibility of flying in varying wind conditions, diverse wind scenarios are taken into consideration here. Uncertainties associated with wind conditions are addressed by taking a typical and worst case scenario perspective, and introducing carefully tailored redundancies during the mod- eling and optimization formulation process. Optimization studies, using a mixed-integer Particle Swarm Optimization algorithm, are performed to separately maximize forward- flight range, subject to various aerodynamic and geometric constraints. Interestingly, the optimization converges to distinct designs under calm, windy, and stormy wind scenarios, with flight ranges going from about 163 km to about 54 km.
KW - Blended-wing-body
KW - Particle swarm optimization
KW - Transitioning UAV
KW - Uncer- tainty
KW - Vortex lattice method
UR - https://www.scopus.com/pages/publications/85088059034
U2 - 10.2514/6.2017-4000
DO - 10.2514/6.2017-4000
M3 - Conference contribution
AN - SCOPUS:85088059034
SN - 9781624105074
T3 - 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017
BT - 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017
Y2 - 5 June 2017 through 9 June 2017
ER -