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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

An aerodynamic optimization computational framework using genetic algorithms

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Author(s):
Antunes, Alexandre P. [1, 2] ; Azevedo, Joao Luiz F. [3]
Total Authors: 2
Affiliation:
[1] Inst Tecnol Aeronaut, Dept Comp Sci, BR-12228900 Sao Jose Dos Campos, SP - Brazil
[2] Embraer SA, Av Brig Faria Lima 2170, BR-12228901 Sao Jose Dos Campos, SP - Brazil
[3] Inst Aeronaut & Espaco, Aerodynam Div, BR-12228904 Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: Journal of the Brazilian Society of Mechanical Sciences and Engineering; v. 38, n. 4, p. 1037-1058, APR 2016.
Web of Science Citations: 1
Abstract

The present paper describes the efforts on the construction of a computational framework for 2-D and 3-D aerodynamic optimizations. The creation of the framework is an attempt to generate a design environment capable of coupling various tools from different levels of complexity and with diverse functionalities. The conceptual framework is developed to be inserted into daily activities of an aerodynamic computational fluid dynamics group. The framework is implemented for both Windows and Linux-running platforms, and it is augmented by a user-friendly graphical interface. Usage of the framework is illustrated in the paper by 2-D and 3-D aerodynamic optimization of cruise configurations for different flight conditions. The test cases addressed mainly have the objective of demonstrating that the proposed framework is a useful tool for aerodynamic optimization applications. The aspects investigated include the influence on the aerodynamic coefficients of the methodology used for configuration parameterization and the benefits of the solver fidelity level as compared to the computational cost. Moreover, the use of a neural network is evaluated to analyze the benefits that this methodology can bring to the implemented framework in terms of computational cost. (AU)

FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC