Abstract
Given the focus on incremental change in existing empirical aerodynamic design methods, radical, unintuitive, new optimal solutions in previously unexplored regions of design space are very unlikely to be found using them. We present a framework based on an implicit shape representation and a multiobjective evolutionary algorithm that aims to produce a variety of optimal flow topologies for a given requirement, providing designers with insights into possibly radical solutions. A revolutionary integrated flow simulation system developed specifically for design work is used to evaluate candidate designs.
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Hutabarat, W., Parks, G.T., Jarrett, J.P., Dawes, W.N., Clarkson, P.J. (2008). Aerodynamic Topology Optimisation Using an Implicit Representation and a Multiobjective Genetic Algorithm. In: Monmarché, N., Talbi, EG., Collet, P., Schoenauer, M., Lutton, E. (eds) Artificial Evolution. EA 2007. Lecture Notes in Computer Science, vol 4926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79305-2_13
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DOI: https://doi.org/10.1007/978-3-540-79305-2_13
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