Download Aircraft Aerodynamic. Design Geometry and Optimization by Andras Sobester, Alexander I J Forrester PDF

By Andras Sobester, Alexander I J Forrester

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Extra resources for Aircraft Aerodynamic. Design Geometry and Optimization

Example text

R) is, in engineering terms, a parametric geometry, and it would still be referred to as one if u was dropped through some rearranging leading to, say, the form ????(r) : x2 + y2 = r2 . 13) To be completely precise, the latter is an implicit parametric geometry, as the ordinate y values can only be obtained by solving an equation. These can sometimes be converted into explicit parametric geometries – in √ this particular case this is doable by breaking it down into two semicircles, yielding y = ± r2 − x2 .

2001). While the mathematical formalism of the problem is simple – a compound objective function is usually generated as a linear combination of sub-objectives corresponding to the various design points – the solution is not. The difficult part is selecting the appropriate weight for each term of the linear combination. g. a method involving weights that adapt to the problem as the optimization progresses, developed by Buckley et al. (2010)). 3 Optimization Method Selection A modern design process relies on a parametric geometry and a means of simulating some aspect of the operation of the aircraft it models in order to obtain a measure of merit (objective function).

18, our most flexible cross-section geometry. The number of shape variables doubles here, as we have now introduced a new set for a separate cargo lobe. We also have the R variables here, which determine the relative positions of the two lobes. 10, twofold. First, the cost of the optimization process (now conducted via a genetic algorithm, followed up by a Nelder and Mead pattern search to fine tune the best solution found by the genetic algorithm) has gone up by two orders of magnitude – we are into the tens of thousands of evaluations of the objective function.

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