Robust multidisciplinary UAS design optimisation
Lee, D-S., Periaux, J., Gonzalez, L.F., Srinivas, K., & Onate, E. (2011) Robust multidisciplinary UAS design optimisation. Structural and Multidisciplinary Optimization.
There are many applications in aeronautical/aerospace engineering where some values of the design parameters states cannot be provided or determined accurately. These values can be related to the geometry(wingspan, length, angles) and or to operational flight conditions that vary due to the presence of uncertainty parameters (Mach, angle of attack, air density and temperature, etc.). These uncertainty design parameters cannot be ignored in engineering design and must be taken into the optimisation task to produce more realistic and reliable solutions. In this paper, a robust/uncertainty design method with statistical constraints is introduced to produce a set of reliable solutions which have high performance and low sensitivity. Robust design concept coupled with Multi Objective Evolutionary Algorithms (MOEAs) is defined by applying two statistical sampling formulas; mean and variance/standard deviation associated with the optimisation fitness/objective functions. The methodology is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. It is implemented for two practical Unmanned Aerial System (UAS) design problems; the flrst case considers robust multi-objective (single disciplinary: aerodynamics) design optimisation and the second considers a robust multidisciplinary (aero structures) design optimisation. Numerical results show that the solutions obtained by the robust design method with statistical constraints have a more reliable performance and sensitivity in both aerodynamics and structures when compared to the baseline design.
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|Item Type:||Journal Article|
|Additional Information:||Springer First Online Publication|
|Keywords:||Robust multidisciplinary, UAS, UAV, design optimisation|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > NUMERICAL AND COMPUTATIONAL MATHEMATICS (010300) > Optimisation (010303)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTATION THEORY AND MATHEMATICS (080200) > Numerical Computation (080205)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation|
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2011 Springer-Verlag|
|Copyright Statement:||The original publication is available at SpringerLink http://www.springerlink.com|
|Deposited On:||31 Oct 2011 08:39|
|Last Modified:||01 Nov 2011 05:44|
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