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Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance

Author: 
Athanasios Papageorgiou, Johan Ölvander, Kristian Amadori
Year: 
2017

CHALLENGE - In the past few years, the technological advancements in the field of aeronautics have created new opportunities for the development of more capable Unmanned Aerial Vehicles (UAVs) which are now being deployed to an increasing number of missions that were traditionally covered by manned aircraft. This work considers a traditional MDO framework for the development of UAVs and emphasizes on its expansion in order to demonstrate that the new enhancements can offer additional support to the decision making process. 

SOLUTION -  Firstly, as a vertical expansion, the proposed work focuses on the development and integration of a radar signature and a sensor performance model which have been typically overlooked in MDO frameworks but are nonetheless of utmost importance in developing applications with stealth and surveillance requirements. Secondly, as a horizontal improvement, this work investigates the use of metamodels as well as the implementation of an efficient decomposition architecture which have been frequently identified as a means to increase the speed of the optimization process and in turn enable a more agile exploration of the design space. Last but not least, the framework includes models for the aerodynamics, mission simulation, and stability for ensuring that the generated design corresponds to a flyable and realistic concept, but also for allowing the concurrent consideration of the mission performance which is an undeniably representative and often conflicting design objective in the development of UAVs. The integration of the models and the realization of the proposed architectures was possible through the use of the optimization tool modeFRONTIER.

BENEFITS - Overall, the results that have been presented in this case-study show that the proposed multidisciplinary optimization and analysis framework has the potential to significantly enhance the performance of the design when mission, stealth, and surveillance requirements must be considered.  More specifically, in the first and second case it was possible to reduce the weight and the radar cross section by 16.4% and 91.1% respectively, while in the third case, the achieved sensor range was around 212 km which is an increase of 623.5%.

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