Computational Fluid Dynamics Expert System using Artificial Neural Networks


Autoria(s): Rubio Calzado, Gonzalo; Valero Sánchez, Eusebio; Lanzan, Sven
Data(s)

2012

Resumo

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Formato

application/pdf

Identificador

http://oa.upm.es/16286/

Idioma(s)

eng

Publicador

E.T.S.I. Aeronáuticos (UPM)

Relação

http://oa.upm.es/16286/1/INVE_MEM_2012_133078.pdf

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

International Journal of Engineering and Applied Sciences, ISSN 2010-3999, 2012, Vol. 6

Palavras-Chave #Aeronáutica #Informática
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed