Revista UIS Ingenierías

Vol. 18 No. 2 (2019): Revista UIS Ingenierías
Articles

Wing profile evolution driven by computational fluid dynamics

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  • Cristian Rendon,
  • José Hernandez,
  • Oscar Ruiz – Salguero,
  • Carlos Alvarez,
  • Mauricio Toro
Cristian Rendon
U. EAFIT
José Hernandez
Universidad EAFIT
Oscar Ruiz – Salguero
Universidad EAFIT
Carlos Alvarez
Universidad EAFIT
Mauricio Toro
Universidad EAFIT
DOI: https://doi.org/10.18273/revuin.v18n2-2019013

Published 2019-02-07

Keywords

  • fluid mechanics,
  • shape evolution,
  • wing profile

How to Cite

Rendon, C., Hernandez, J., Ruiz – Salguero, O., Alvarez, C., & Toro, M. (2019). Wing profile evolution driven by computational fluid dynamics. Revista UIS Ingenierías, 18(2), 139–146. https://doi.org/10.18273/revuin.v18n2-2019013
Copyright Notice

Abstract

In the domain of fluid dynamics, the problem of shape optimization is relevant because is essential to increase lift and reduce drag forces on a body immersed in a fluid. The current state of the art in this aspect consists of two variants: (1) evolution from an initial guess, using optimization to achieve a very specific effect, (2) creation and genetic breeding of random individuals. These approaches achieve optimal shapes and evidence of response under parameter variation. Their disadvantages are the need of an approximated solution and / or the trial - and - error generation of individuals. In response to this situation, this manuscript presents a method which uses Fluid Mechanics indicators (e.g. streamline curvature, pressure difference, zero velocity neighborhoods) to directly drive the evolution of the individual (in this case a wing profile). This pragmatic strategy mimics what an artisan (knowledgeable in a specific technical domain) effects to improve the shape. Our approach is not general, and it is not fully automated. However, it shows to efficiently reach wing profiles with the desired performance. Our approach shows the advantage of application domain - specific rules to drive the optimization, in contrast with generic administration of the evolution.

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