Evolving Parametric Aircraft Models for Design Exploration and Optimisation

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Jonathan Byrne and Phillip Cardiff and 
                 Anthony Brabazon and Michael O'Neill",
  title =        "Evolving Parametric Aircraft Models for Design
                 Exploration and Optimisation",
  journal =      "Neurocomputing",
  year =         "2014",
  volume =       "142",
  pages =        "39--47",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1016/j.neucom.2014.04.004",
  URL =          "http://www.sciencedirect.com/science/article/pii/S092523121400530X",
  abstract =     "Traditional CAD tools generate a static solution to a
                 design problem. Parametric systems allow the user to
                 explore many variations on that design theme. Such
                 systems make the computer a generative design tool and
                 are already used extensively as a rapid prototyping
                 technique in architecture and aeronautics. Combining a
                 design generation tool with an analysis software and an
                 evolutionary algorithm provides a methodology for
                 optimising designs. This work combines NASA's
                 parametric aircraft design tool (OpenVSP) with a fluid
                 dynamics solver (OpenFOAM) to create and analyse
                 aircraft. An evolutionary algorithm is then used to
                 generate a range of aircraft that maximise lift and
                 reduce drag while remaining within the framework of the
                 original design. Our approach allows the designer to
                 automatically optimise their chosen design and to
                 generate models with improved aerodynamic efficiency.
                 Different components on three aircraft models are
                 varied to highlight the ease and effectiveness of the
                 parametric model optimisation.",

Genetic Programming entries for Jonathan Byrne Phillip Cardiff Anthony Brabazon Michael O'Neill