Framework for Multifidelity Aeroelastic Vehicle Design Optimization

Author(s):  
Dean Bryson ◽  
Markus Rumpfkeil ◽  
Ryan Durscher
2017 ◽  
Vol 26 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Loïc Brevault ◽  
Mathieu Balesdent ◽  
Sébastien Defoort

The design of complex systems such as launch vehicles involves different fields of expertise that are interconnected. To perform multidisciplinary studies, concurrent engineering aims at providing a collaborative environment which often relies on data set exchange. In order to efficiently achieve system-level analyses (uncertainty propagation, sensitivity analysis, optimization, etc.), it is necessary to go beyond data set exchange which limits the capabilities of performance assessments. Multidisciplinary design optimization methodologies is a collection of engineering methodologies to optimize systems modelled as a set of coupled disciplinary analyses and is a key enabler to extend concurrent engineering capabilities. This article is focused on several examples of recent developments of multidisciplinary design optimization methodologies (e.g. multidisciplinary design optimization with transversal decomposition of the design process, multidisciplinary design optimization under uncertainty) with applications to launch vehicle design to illustrate the benefices of taking into account the coupling effects between the different physics all along the design process. These methods enable to manage the complexity of the involved physical phenomena and their interactions in order to generate innovative concepts such as reusable launch vehicles beyond existing solutions.


2000 ◽  
Author(s):  
J. Garcelon ◽  
K. Wipke ◽  
Tony Markel

Author(s):  
Hyeong-Uk Park ◽  
Joon Chung ◽  
Jae-Woo Lee ◽  
Daniel Neufeld

Manufacturers often develop new products by modifying and extending existing products in order to achieve new market demands while minimizing development time and manufacturing costs. In this research, an efficient derivative design process was developed to efficiently adapt existing aircraft designs according to new requirements. The proposed design process was evaluated using a case study that derives an unmanned aerial vehicle design from a baseline manned 2-seatlight sport aircraft. Multiple unmanned aerial vehicle operational scenarios were analysed to define the requirements of the derivative aircraft. These included patrol, environmental monitoring, and communications relay missions. Each mission has different requirements and therefore each resulting derivative unmanned aerial vehicle design has different geometry, devices, and performance. The derivative design process involved redefining the design requirements and identifying the minimum design variable set that needed to be considered in order to efficiently adapt the baseline design. Uncertainty was considered as well to enhance the reliability of the optimized result when it considered different conditions for each mission. An optimization method based on the possibility based design optimization was proposed to handle uncertainty that arises in the design requirements for the multi-role nature of unmanned aerial vehicles. In this paper, the possibility based design optimization method was implemented with multidisciplinary design optimization technique to derive the derivative unmanned designs based on originally manned aircraft. This approach prevented constraint violation via uncertainty variations in the operating altitude and payload weight for each. The unmanned aerial vehicle derivative designs satisfying the requirements of three different missions were derived from the proposed design process.


Author(s):  
Hugo Magalhães ◽  
João Pombo ◽  
Jorge Ambrósio ◽  
J. F. A. Madeira

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