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Structural and Multidisciplinary Optimization

, Volume 57, Issue 5, pp 2045–2059 | Cite as

Topology optimization applied to the development of small scale pump

  • L. F. N. Sá
  • J. S. Romero
  • O. Horikawa
  • E. C. N. Silva
Industrial Application
  • 308 Downloads

Abstract

Flow machines are very important to industry, being widely used on various processes. Performance improvements are relevant factors and can be achieved by using optimization methods, such as topology optimization. Thus, this work aims to perform the complete development cycle of a small scale pump designed by using topology optimization method. For the pump modelling the finite element method is applied to solve the Navier-Stokes equations on a rotating reference frame. In the optimization phase, it is defined a multi-objective function that aims to minimize the viscous energy dissipation and vorticity. The optimized results obtained by using topology optimization are post-processed and manufactured by using a 3D printer, and prototypes with an electric motor are built. An experimental characterization is performed by measuring fluid flow and pressure head given by the pumps. Experimental and computational results are compared and the improvement is verified.

Keywords

Flow machine rotor design Topology optimization Navier-Stokes Prototype manufacturing Experimental characterization 

Notes

Acknowledgements

This research was partly supported by CNPq (Brazilian Research Council) and FAPESP (Sao Paulo Research Foundation). The authors thank the supporting institutions. The first author thanks the financial support of FAPESP under grants 2016/19261-7, 2013/24434-0, and 2014/50279-4. The fourth author thanks the financial support of CNPq (National Council for Research and Development) under grant 304121/2013-4. Authors thank the NDF laboratory at Mechanical Engineering Department for sharing the ANSYS license.

References

  1. Aaronson KD, Slaughter MS, Miller LW, McGee EC, Cotts WG, Acker MA, Jessup ML, Gregoric ID, Loyalka P, Frazier OH, Jeevanandam V, Anderson AS, Kormos RL, Teuteberg JJ, Levy WC, Naftel DC, Bittman RM, Pagani FD, Hathaway DR, Boyce SW (2012) Use of an intrapericardial, continuous-flow, centrifugal pump in patients awaiting heart transplantation. Circulation 125 (25):3191–3200CrossRefGoogle Scholar
  2. Abraham F, Behr M, Heinkenschloss M (2004) The effect of stabilization in finite element methods for the optimal boundary control of the Oseen equations. Finite Elem Anal Des 41(3):229–251MathSciNetCrossRefGoogle Scholar
  3. Amestoy PR, Duff IS, L’Excellent J-Y, Koster J (2001) A fully asynchronous multifrontal solver using distributed dynamic scheduling. SIAM J Matrix Anal Appl 23(1):15–41MathSciNetCrossRefzbMATHGoogle Scholar
  4. Amigo R, Giusti SM, Novotny AA, Silva ECN, Sokołowski J (2016) Optimum design of flextensional piezoelectric actuators into two spatial dimensions. SIAM J Control Optim 54(2):760–789MathSciNetCrossRefzbMATHGoogle Scholar
  5. Baloni BD, Pathak Y, Channiwala S (2015) Centrifugal blower volute optimization based on Taguchi method. Comput Fluids 112:72–78CrossRefGoogle Scholar
  6. Barenboim AB, Vasil’tsov A (1965) Effect of the Reynolds number on the pump characteristics. Chem Pet Eng 1(2):118–122CrossRefGoogle Scholar
  7. Berggren M (1998) Numerical solution of a flow-control problem: vorticity reduction by dynamic boundary action. SIAM J Sci Comput 19(3):829–860MathSciNetCrossRefzbMATHGoogle Scholar
  8. Borrvall T, Petersson J (2003) Topology optimization of fluids in Stokes flow. Int J Numer Methods Fluids 41(1):77–107MathSciNetCrossRefzbMATHGoogle Scholar
  9. Casas V, Pena F, Duro R (2006) Automatic design and optimization of wind turbine blades. In: 2006 International conference on computational inteligence for modelling control and automation and international conference on intelligent agents web technologies and international commerce (CIMCA’06). IEEE, pp 205–205Google Scholar
  10. Day SW, Lemire PP, Flack RD, McDaniel JC (2003) Effect of Reynolds number on performance of a small centrifugal pump. In: Volume 1: Fora, Parts A, B, C, and D. ASME, pp 1893–1899Google Scholar
  11. Deng Y, Liu Z, Wu J, Wu Y (2013) Topology optimization of steady Navier–Stokes flow with body force. Comput Methods Appl Mech Eng 255:306–321MathSciNetCrossRefzbMATHGoogle Scholar
  12. Derakhshan S, Pourmahdavi M, Abdolahnejad E, Reihani A, Ojaghi A (2013) Numerical shape optimization of a centrifugal pump impeller using artificial bee colony algorithm. Comput Fluids 81:145–151CrossRefGoogle Scholar
  13. Evgrafov A (2004) Topology optimization of slightly compressible fluids. Doktorsavhandlingar vid Chalmers Tekniska Hogskola 62(1):55–81Google Scholar
  14. Evgrafov A (2005) The limits of porous materials in the topology optimization of stokes flows. Appl Math Optim 52(3):263–277MathSciNetCrossRefzbMATHGoogle Scholar
  15. Fraser WH (1981) Flow recirculation in centrifugal pumps. In: Proceedings of the tenth turbomachinery symposium, pp 95–100Google Scholar
  16. Funke SW, Farrell PE (2013) A framework for automated PDE-constrained optimisation. arXiv:1302.3894
  17. Gȯlcu̇ M, Pancar Y, Sekmen Y (2006) Energy saving in a deep well pump with splitter blade. Energy Convers Manag 47(5):638–651CrossRefGoogle Scholar
  18. Lee Y-T, Ahuja V, Hosangadi A, Slipper ME, Mulvihill LP, Birkbeck R, Coleman RM (2011) Impeller design of a centrifugal fan with blade optimization. Int J Rotat Mach 2011:1–16CrossRefGoogle Scholar
  19. Logg A, Wells GN, Book TF (2012) Automated solution of differential equations by the finite element method, volume 84 of lecture notes in computational science and engineering. Springer, BerlinCrossRefGoogle Scholar
  20. Nishiwaki S, Frecker MI, Min S, Kikuchi N (1998) Topology optimization of compliant mechanisms using the homogenization method. Int J Numer Methods Eng 42(3):535–559MathSciNetCrossRefzbMATHGoogle Scholar
  21. Olesen LH, Okkels F, Bruus H (2006) A high-level programming-language implementation of topology optimization applied to steady-state navier–stokes flow. Int J Numer Methods Eng 65(7):975–1001MathSciNetCrossRefzbMATHGoogle Scholar
  22. Quarteroni A, Rozza G (2003) Optimal control and shape optimization of aorto-coronaric bypass anastomoses. Math Models Methods Appl Sci 13(12):1801–1823MathSciNetCrossRefzbMATHGoogle Scholar
  23. Romero JS, Silva ECN (2014) A topology optimization approach applied to laminar flow machine rotor design. Comput Methods Appl Mech Engrg 279:268–300MathSciNetCrossRefGoogle Scholar
  24. Sá LFN, Novotny AA, Romero JS, Silva ECN (2017) Design optimization of laminar flow machine rotors based on the topological derivative concept. Struct Multidiscip Optim 56:1013Google Scholar
  25. Sigmund O (1997) On the design of compliant mechanisms using topology optimization*. Mech Struct Mach 25(4):493–524CrossRefGoogle Scholar
  26. Wächter A (2009) Short tutorial: getting started with Ipopt in 90 minutes. In: Toledo UN, Schenk O, Simon HD, Sivan (eds) Combinatorial scientific computing, Dagstuhl, Germany. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, GermanyGoogle Scholar
  27. Wȧchter A, Biegler LT (2006) On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Math Program 106(1):25–57MathSciNetCrossRefzbMATHGoogle Scholar
  28. Wen-Guang L (2011) Inverse design of impeller blade of centrifugal pump with a singularity method. Jordan J Mech Indus 5(2):119–128Google Scholar
  29. Yu S, Ng B, Chan W, Chua L (2000) The flow patterns within the impeller passages of a centrifugal blood pump model. Med Eng Phys 22(6):381–393CrossRefGoogle Scholar
  30. Zhu B, Zhang X, Fatikow S (2014) A multi-objective method of hinge-free compliant mechanism optimization. Struct Multidiscip Optim 49(3):431–440MathSciNetCrossRefGoogle Scholar
  31. Zhu B, Zhang X, Fatikow S (2015) Structural topology and shape optimization using a level set method with distance-suppression scheme. Comput Methods Appl Mech Eng 283(Supplement C):1214–1239MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechatronics and Mechanical Systems Engineering of Escola PolitecnicaUniversity of Sao PauloSao PauloBrazil
  2. 2.Department of Mechanical EngineeringFederal University of Espirito SantoEspirito SantoBrazil

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