Skip to main content

Optimization of a butterfly valve disc using 3D topology and genetic algorithms


Butterfly valves are a mechanical component used to regulate flow and pressure on a variety of tanks and pipeline systems. The design of this flow-control device needs to consider its structural performance as well as the flow of the fluid. In this sense, simulation and optimization tools play an important role in a butterfly valve successful development. This paper presents a global optimization of the disc of a butterfly valve by the combination of topology and shape optimization techniques. Topology optimization is employed during concept design stage to evaluate the best material distribution from a structural performance point of view. Then, based on the topology optimization results, a shape optimization, managed by Genetic Algorithms (GAs), is conducted considering structural and fluid dynamics at the same time. The results demonstrate the suitability of the proposed approach to obtain a light butterfly valve disc which satisfies the structural safety and the flow requirements.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16


  1. Baker RC (2005) Flow measurement handbook: industrial designs, operating principles, performance, and applications. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  2. Baverey, F. (1916). U.S. Patent No. 1,167,145. Washington. Patent and trademark office

  3. BVack T (1993) Optimal mutation rates in genetic search. In Proc. of the 5th International Conference on Genetic Algorithms 2–8

  4. Caille V, Laumonier J (1998) Effect of periodic aerodynamic pulsation on flow over a confined butterfly valve. Exp Fluids 25(4):362–368

    Article  Google Scholar 

  5. Corbera S, Olazagoitia JL, Lozano JA (2016) Multi-objective global optimization of a butterfly valve using genetic algorithms. ISA Trans. doi:10.1016/j.isatra.2016.03.008

    Google Scholar 

  6. De Jong K (1980) Adaptive system design: a genetic approach. IEEE Trans Syst Man Cybernet 10(9):566–574

    MathSciNet  Article  Google Scholar 

  7. Deaton JD, Grandhi RV (2014) A survey of structural and multidisciplinary continuum topology optimization: post 2000. Struct Multidiscip Optim 49(1):1–38

    MathSciNet  Article  Google Scholar 

  8. Deb K (2001) Multi-objective optimization using evolutionary algorithms (Vol. 16). Wiley

  9. Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  10. Goldberg DE (1989) Genetic algorithm in search, optimization and machine learning, mass: Wesley

  11. Han SU, Ahn DG, Lee MG, Lee KH, Han SH (2014) Structural safety analysis based on seismic service conditions for butterfly valves in a nuclear power plant. Sci World J. doi:10.1155/2014/743470

    Google Scholar 

  12. Huang C, Kim RH (1996) Three-dimensional analysis of partially open butterfly valve flows. J Fluids Eng 118(3):562–568

    Article  Google Scholar 

  13. Huang X, Xie YM (2010) A further review of ESO type methods for topology optimization. Struct Multidiscip Optim 41(5):671–683

    Article  Google Scholar 

  14. Kim JO, Yang SM, Baek SH, Kang S (2012) Structural design strategy of double-eccentric butterfly valve using topology optimization techniques. World Acad Sci, Eng Technol, Int J Mech, Aeros, Ind, Mech Manuf Eng 6(6):1075–1080

    Google Scholar 

  15. Kimura T, Tanaka T, Fujimoto K, Ogawa K (1995) Hydrodynamic characteristics of a butterfly valve—prediction of pressure loss characteristics. ISA Trans 34(4):319–326

    Article  Google Scholar 

  16. Morris MJ, Dutton JC (1991) An experimental investigation of butterfly valve performance downstream of an elbow. J Fluids Eng 113(1):81–85

    Article  Google Scholar 

  17. Nagpurkar PP, Tajane RS (2014) Design and development of double offset butterfly valve. In International Journal of Engineering Research and Technology (Vol. 3, no. 7 (July-2014)). ESRSA publications

  18. Odu GO, Charles-Owaba OE (2013) Review of multi-criteria optimization methods–theory and applications. IOSRJEN 3:1–14

    Article  Google Scholar 

  19. Ogawa K, Kimura T (1995) Hydrodynamic characteristics of a butterfly valve—prediction of torque characteristics. ISA Trans 34(4):327–333

    Article  Google Scholar 

  20. Prager W, Rozvany GI (1977) Optimization of structural geometry. Dynam Syst, 265–293

  21. Querin OM, Steven GP, Xie YM (1998) Evolutionary structural optimisation (ESO) using a bidirectional algorithm. Eng Comput 15(8):1031–1048

    Article  MATH  Google Scholar 

  22. Sigmund O (2001) A 99 line topology optimization code written in Matlab. Struct Multidiscip Optim 21(2):120–127

    MathSciNet  Article  Google Scholar 

  23. Sigmund O, Maute K (2013) Topology optimization approaches. Struct Multidiscip Optim 48(6):1031–1055

    MathSciNet  Article  Google Scholar 

  24. Song XG, Wang L, Baek SH, Park YC (2009) Multidisciplinary optimization of a butterfly valve. ISA Trans 48(3):370–377

    Article  Google Scholar 

  25. Sorkine O (2006). Laplacian mesh processing

  26. Spears WM (1991) KA De Jong. On the virtues of parameterized uniform crossover. Proceedings of the fourth International Conference on Genetic Algorithms

  27. Ştefan MT, Iosif PZ, Florin P, Marius AE, Dorica SM (2011) Stresses and displacement FEM analysis on biplane disks of the butterfly valves. In Proceedings of the 4th WSEAS international conference on Finite differences-finite elements-finite volumes-boundary elements (pp. 88–91). World scientific and engineering academy and society (WSEAS)

  28. Xie YM, Steven GP (1993) A simple evolutionary procedure for structural optimization. Comput Struct 49(5):885–896

    Article  Google Scholar 

  29. Xie, Y. M., & Steven, G. P. (1997). Basic evolutionary structural optimization. In Evolutionary Structural Optimization (pp. 12–29). Springer London

  30. Yang SM, Baek SH, Kang S (2012) Shape design for disc of a double-eccentric butterfly valve using the topology optimization technique. J Comput Fluids Eng 17(1):61–69

    Article  Google Scholar 

  31. Yi SI, Shin MK, Shin MS, Yoon JY, Park GJ (2008) Optimization of the eccentric check butterfly valve considering the flow characteristics and structural safety. Proc Inst Mech Eng, Part E: J Proc Mech Eng 222(1):63–73

    Article  Google Scholar 

  32. Young V, Querin OM, Steven GP, Xie YM (1999) 3D and multiple load case bi-directional evolutionary structural optimization (BESO). Struct Opt 18(2–3):183–192

    Article  Google Scholar 

  33. Zeheen, J. (1887). U.S. Patent No. 373,000. Washington. Patent and trademark office

  34. Zhou M, Rozvany GIN (2001) On the validity of ESO type methods in topology optimization. Struct Multidiscip Optim 21(1):80–83

    Article  Google Scholar 

  35. Zhu JH, Zhang WH, Xia L (2015) Topology optimization in aircraft and aerospace structures design. Arch Comput Methods Eng 1–28

Download references


The authors would like to acknowledge the support of the Nebrija Santander Green Surface Transport chair.

Author information



Corresponding author

Correspondence to R. Álvarez Fernández.

Additional information


• This paper proposed the global optimization of a butterfly valve taking into account the structural safety, its fluid dynamic influence and its weight.

• An approach, structured in two stages with different optimization techniques is applied for a multi-objective optimization of the butterfly valve.

• Topology optimization is employed at the first stage aim to evaluate the best material distribution from a structural performance point of view, then a shape optimization, managed by Genetic Algorithms, is conducted considering structural and fluid performance at the same time.

• The design domain of the topology optimization and the design variables of the shape optimization concern the complete back side of the disc and they are not only focused on a concrete region. This strategy allows a true global optimization of the disc.

• The optimization process is set up by means of different Python scripts that connect the FEA and CFD software with Topology and Genetic Algorithms developed by the authors.

• The optimization result shows that the combination of Topology and Genetic Algorithms provides an optimum valve design that decreases the maximum stress by 70.5%, the mass by 6% and increases the Kv by 16.7%.

• The results obtained confirm that the applied methodology in this study is adequate for addressing the optimization of these types of valves.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Corbera Caraballo, S., Olazagoitia Rodríguez, J.L., Lozano Ruiz, J.A. et al. Optimization of a butterfly valve disc using 3D topology and genetic algorithms. Struct Multidisc Optim 56, 941–957 (2017).

Download citation


  • Butterfly valve
  • Topology optimization
  • Genetic algorithms
  • Computational fluid dynamics
  • Static structural