Visualization methodologies in aircraft design optimization
Visualization methodologies in aircraft design optimization
This thesis reviews aspects of current low dimensional visualisation methods which are useful in design and how these can be extended to higher dimensions. The deficiencies in these methods are described and new visualisation methods are introduced, which simplify complex ideas into a small number of plots, that the designer can understand and to use to gain insight into design. Much of this is made possible only because the large amounts of data required for high dimensional design space appreciation are provided by response surface method technology. A modus operandi is proposed and the possibilities for visualisation as an aid to understanding design are studies in aircraft aerodynamic design. Sample problems include analytical functions, such as a two dimensional bump problem and a military aircraft optimisation problem in 5, 8 and 14 dimensions.
The new visualisation methodologies introduced are utilised to support design decisions for the sample design problems, such as the relative scaling of the design variables and constraints and choice of penalty function, which are important in optimisation. Also extended is the potential to recognise problems such as numerical noise and boundaries of evaluation failure. Initial design of experiments are shown to be improved in a systematic way by calculation of additional points dictated by maps of statistical and other error criteria.
Although this technology is developed with reference to aircraft conceptual and aerodynamic design in particular, the design space visualisation and curve-fitting technology developed is general. It should therefore be equally applicable to other disciplines such as cost analysis, structures and computational electromagnetics, in which expensive analysis tools are used to find optima for complicated design problems. It is expected to be particularly useful in multi-disciplinary design.
University of Southampton
Holden, Carren M.E
411ab81a-6161-4eef-9d23-8ffc8972b572
2004
Holden, Carren M.E
411ab81a-6161-4eef-9d23-8ffc8972b572
Holden, Carren M.E
(2004)
Visualization methodologies in aircraft design optimization.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
This thesis reviews aspects of current low dimensional visualisation methods which are useful in design and how these can be extended to higher dimensions. The deficiencies in these methods are described and new visualisation methods are introduced, which simplify complex ideas into a small number of plots, that the designer can understand and to use to gain insight into design. Much of this is made possible only because the large amounts of data required for high dimensional design space appreciation are provided by response surface method technology. A modus operandi is proposed and the possibilities for visualisation as an aid to understanding design are studies in aircraft aerodynamic design. Sample problems include analytical functions, such as a two dimensional bump problem and a military aircraft optimisation problem in 5, 8 and 14 dimensions.
The new visualisation methodologies introduced are utilised to support design decisions for the sample design problems, such as the relative scaling of the design variables and constraints and choice of penalty function, which are important in optimisation. Also extended is the potential to recognise problems such as numerical noise and boundaries of evaluation failure. Initial design of experiments are shown to be improved in a systematic way by calculation of additional points dictated by maps of statistical and other error criteria.
Although this technology is developed with reference to aircraft conceptual and aerodynamic design in particular, the design space visualisation and curve-fitting technology developed is general. It should therefore be equally applicable to other disciplines such as cost analysis, structures and computational electromagnetics, in which expensive analysis tools are used to find optima for complicated design problems. It is expected to be particularly useful in multi-disciplinary design.
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Published date: 2004
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Local EPrints ID: 465422
URI: http://eprints.soton.ac.uk/id/eprint/465422
PURE UUID: f1d4a56a-ca20-49e7-b7a3-4335ef4c0791
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Date deposited: 05 Jul 2022 00:54
Last modified: 16 Mar 2024 20:10
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Author:
Carren M.E Holden
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