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Design and Optimization of an Industrial Pump: Application of Genetic Algorithms and Neural Network

[+] Author Affiliations
Alain Demeulenaere


Aji Purwanto, Alban Ligout, Charles Hirsch

NUMECA International, S.A.

Ronal Dijkers, Frank Visser


Paper No. FEDSM2005-77487, pp. 1519-1527; 9 pages
  • ASME 2005 Fluids Engineering Division Summer Meeting
  • Volume 1: Symposia, Parts A and B
  • Houston, Texas, USA, June 19–23, 2005
  • Conference Sponsors: Fluids Engineering Division
  • ISBN: 0-7918-4198-7 | eISBN: 0-7918-3760-2
  • Copyright © 2005 by ASME


This paper presents an integrated environment FINETM /Design3D developed for the optimization of turbomachinery blade shapes. The methodology relies on the interaction between a genetic algorithm, an artificial neural network, a database and user generated objective functions and constraints. The optimization is coupled to the FINETM /Turbo environment of NUMECA. The present paper focuses on the application of the multipoint optimization algorithm to the design of an industrial pump. The large range of mass flow over which the pump should operate motivates the use of multipoint optimization. The optimization exercise focuses on the efficiency, the head and the NPSH at two operating conditions characterized by largely different mass flows.

Copyright © 2005 by ASME



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