TY - GEN
T1 - Slender flight vehicle multidisciplinary design optimization considering aeroelasticity
AU - Wei, Zhao
AU - Liu, Li
AU - Long, Teng
AU - Li, Xin
N1 - Publisher Copyright:
© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Slender flight vehicle shows different characteristics under the consideration of aeroelasticity, such as in structural modeling, control system and flight dynamics, etc. Therefore, design optimization task of the slender flight vehicle is a more complex multidisciplinary design optimization (MDO) problem compared with the rigid one. In this paper, the MDO problem of the slender flight vehicle involving structure, aeroelasticity, control, and trajectory disciplines is formulated to minimize the flight vehicle total mass with a number of practical constraints. Since the structural finite element analysis model and trajectory simulation model are computationally expensive, the Kriging metamodel is applied to assist the MDO process with moderate computational cost by approximating the objective function and constraints separately. Then, genetic algorithm is adopted to solve the MDO problem. The optimization results illustrate that the flight vehicle total mass is decreased by 20kg, which demonstrates the effectiveness and practicability of Kriging surrogate model-based design optimization method in solving engineering design optimization problems.
AB - Slender flight vehicle shows different characteristics under the consideration of aeroelasticity, such as in structural modeling, control system and flight dynamics, etc. Therefore, design optimization task of the slender flight vehicle is a more complex multidisciplinary design optimization (MDO) problem compared with the rigid one. In this paper, the MDO problem of the slender flight vehicle involving structure, aeroelasticity, control, and trajectory disciplines is formulated to minimize the flight vehicle total mass with a number of practical constraints. Since the structural finite element analysis model and trajectory simulation model are computationally expensive, the Kriging metamodel is applied to assist the MDO process with moderate computational cost by approximating the objective function and constraints separately. Then, genetic algorithm is adopted to solve the MDO problem. The optimization results illustrate that the flight vehicle total mass is decreased by 20kg, which demonstrates the effectiveness and practicability of Kriging surrogate model-based design optimization method in solving engineering design optimization problems.
UR - http://www.scopus.com/inward/record.url?scp=85051647080&partnerID=8YFLogxK
U2 - 10.2514/6.2018-3418
DO - 10.2514/6.2018-3418
M3 - Conference contribution
AN - SCOPUS:85051647080
SN - 9781624105500
T3 - 2018 Multidisciplinary Analysis and Optimization Conference
BT - 2018 Multidisciplinary Analysis and Optimization Conference
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - 19th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2018
Y2 - 25 June 2018 through 29 June 2018
ER -