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Multilevel optimization of the semi-open impeller in a centrifugal pump

Identyfikatory
Warianty tytułu
Konferencja
International Symposium on Compressor and Turbine Flow Systems - Theory and Application Areas "SYMKOM" (10 ; 26-28.10.2011 ; Łódź, Polska)
Języki publikacji
EN
Abstrakty
EN
Full optimization task for the case of the semi-open impeller with straight blades, requires description of its' geometry by means of, at least, eighteen design variables. In the case of constant meridional cross-section, are required at least eight design variables. Solution of the task with such great vector of design variables requires much more time. One way to manage to obtain a solutions with great variety of design variables is comprehensive approach to the task depending on the partition into minor subtasks. After decomposing the optimization task, one should choose procedure of solving it. One of these procedures is parametric optimization, which is two-stage method of minimizing (maximizing). This optimization is carried on in two levels. On a lower level, multi-optimization of decomposed parts of the tasks, depending on design variables, is being held. The solution of the lower level is used in an upper level (coordinating level) to find optimal coordination variables. It has been shown that result of multilevel optimization and full task optimization is the same in limits of accepted accuracy of the objective functions' calculus. Time of the calculation for the multilevel optimization task is over four times shorter than undecomposed task time.
Rocznik
Strony
319--332
Opis fizyczny
Bibliogr. 16 poz.
Twórcy
autor
Bibliografia
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  • [2] ANSYS, Inc., ANSYS-CFX Release 11.0 Canonsburg, PA USA, 2007.
  • [3] Arabas, J.: Wykłady z algorytmów ewolucyjnych, WNT, Warszawa, 2001.
  • [4] Choi, T., Gilmore, P., Eslinger, O. J., Kelley, C.T. and Gablonsky, J.: Iffco: Implicit filtering for constrained optimization, version 2. Technical Report CRSC-TR99-23, North Carolina State University, Center for Research in Scientific Computation, 1999.
  • [5] Carroll, D. L.: Fortran genetic algorithm (GA) driver version 1.7.1a, Url: http://cuaerospace.com/carroll/ga.html, 2001.
  • [6] Findeisen, W., Szymanowski, J. and Wierzbicki, A.: Teoria i metody obliczeniowe optymalizacji, PWN, Warszawa, 1980.
  • [7] Gulich, J. F.: Centrifugal Pumps, Springer Berlin Heidelberg New York, 2008.
  • [8] Harinck, J., Alsalihi, Z., Van Buytenen, J.P. and Van den Braembussche, R.A.: Optimization of a 3D radial turbine by means of an improved genetic algorithm, In: Proceedings of European Turbomachinery Conference, Lille, 2005.
  • [9] Kelley, C. T.: Iterative Methods for Optimization, SIAM, Philadelphia, 1999.
  • [10] Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution, Springer-Verlag, 1996. (also access in Polish)
  • [11] Ostwald, M.: Podstawy optymalizacji konstrukcji, Wydawnictwo Politechniki Poznańskiej, Poznań, 2003.
  • [12] Papierski, A. and Błaszczyk, A.: Procedury optymalizacji w metodzie projektowania półotwartych wirników pomp odśrodkowych, Pompy Pompownie, 136/2010, p. 38-43, 2010.
  • [13] Papierski, A., Błaszczyk, A. and Staniszewski, J.: Nowoczesna metoda projektowania pomp, VII Konferencja - Problemy Badawcze Energetyki Cieplnej, Politechnika Warszawska, Prace Naukowe Konferencje z. 24, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa, 2005.
  • [14] Papierski, A., Martyna, M. and Najdecki, S.: Calculations of the Flow in a Semi-Open Impeller of the Low Specific Speed Centrifugal Pump, International Symposium SYMKOM' 05.Compresor and Turbine Flow Systems. Theory and Applications Areas, Zeszyty Naukowe Politechniki Łódzkiej, CMP-Turbomachinery IMP PL, 128, 2005.
  • [15] Papierski, A.: Shape optimization of semi-open impeller for the low specific speed centrifugal pump, XVIII KKMP, Jastrzębia Góra, 2008.
  • [16] Thevenin, D. and Janiga, G.: Optimization and Computational Fluid Dynamics, Springer-Verlag, 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-LOD9-0027-0052
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