Robust multidisciplinary UAS design optimisation |
| |
Authors: | Email author" target="_blank">Dong?Seop?LeeEmail author J?Periaux L?F?Gonzalez K?Srinivas E?Onate |
| |
Affiliation: | (1) International Center for Numerical Methods in Engineering (CIMNE), Barcelona, Spain;(2) Australian Research Centre Aerospace Automation (ARCAA) School of Engineering System, Queensland University of Technology, Brisbane, QLD, Australia;(3) Aerospace Mechanical & Mechatronic Engineering (AMME), University of Sydney, Sydney, Australia |
| |
Abstract: | 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 first 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. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|