Skip to main content

Differential Evolution on the Minimization of Thermal Residual Stresses in Functionally Graded Structures

  • Conference paper
  • First Online:
Computational Intelligence and Decision Making

Abstract

Global optimization techniques present considerable advantages when applied to non-linear and/or non-convex design spaces, where local search techniques can easily be trapped in local minima. In the present work, it is considered the application of Differential Evolution to the optimization of thermal residual stresses distribution in a sandwich panel, which is composed by an aluminium core and functionally graded outer layers. With this aim, numerical examples were carried out in order to evaluate the influence of different design parameters on the thermal residual stresses distribution. From those results, it is possible to conclude from the adequacy of the Differential Evolution strategy to minimize thermal residual stresses values, under different scenarios. It is worth to note the obtained increasing smoothness of residual stresses distribution, specially on the material transition interface.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Surendranath H, Bruck HA, Gowrisankaran S (2003) Enhancing the optimization of material distributions in composite structures using gradient architectures. Int J Solids Struct 40(12):2999–3020

    Article  MATH  Google Scholar 

  2. Yamanoushi M, Koizumi M, Hiraii T, Shiota I (eds) (1990) In: Proceedings of the first international symposium on functionally gradient materials, Sendai

    Google Scholar 

  3. Koizumi M (1993) The concept of FGM. Ceram Trans 34:3–10

    Google Scholar 

  4. Uemura S (2003) The activities of FGM on new applications. Mater Sci Forum 423–425:1–10

    Article  Google Scholar 

  5. Birman V, Byrd L (2007) Modeling and analysis of functionally graded materials and structures. Appl Mech Rev 60:195–216

    Article  Google Scholar 

  6. Reddy J (2000) Analysis of functionally graded plates. Int J Numer Method Eng 47:663–684

    Article  MATH  Google Scholar 

  7. Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning, 1st edn. Addison-Wesley Longman Publishing Co, Reading

    MATH  Google Scholar 

  8. Kennedy J, Eberhart RC (1999) The particle swarm: The social adaptation in information-processing systems. In: Corne D, Dorigo M, Glover F (eds) New ideas in optimization. McGraw-Hill, London, pp 379–388

    Google Scholar 

  9. Storn R, Price K (1997) Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341–359

    Article  MathSciNet  MATH  Google Scholar 

  10. Deneubourg J, Aron S, Goss S, Pasteels J (1990) The self-organizing exploratory pattern of the argentine ant. J Insect Behav 3:159–168

    Article  Google Scholar 

  11. Kitayama S, Arakawa M, Yamazaki K (2011) Differential evolution as the global optimization technique and its application to structural optimization. Appl Soft Comput 11(4):3792–3803

    Article  Google Scholar 

  12. Wu C-Y, Tseng K-Y (2010) Topology optimization of structures using modified binary differential evolution. Struct Multidiscip Optim 42:939–953

    Article  Google Scholar 

  13. Vu A-T, Werner F (2009) Optimization of steel frame structures based on differential evolution algorithm, In: 18th International Conference on the application of computer science and mathematics in architecture and civil engineering, Weimar

    Google Scholar 

  14. Valakos I, Ntipteni M, Nikolos I (2007) Structural optimization of a centrifugal impeller using differential evolution in Catia environment. Oper Res 7:185–211

    Google Scholar 

  15. Bruck H, Gallant F, Gowrisankaran S (2002) Development of a novel continuous processing technology for functionally graded composite energetic materials using an inverse design procedure In: 2002 SEM annual conference and exposition on experimental and applied mechanics, Milwaukee, pp 296–302

    Google Scholar 

  16. Babu B, Munawar S (2007) Differential evolution strategies for optimal design of shell-and-tube heat exchangers. Chem Eng Sci 62(14):3720–3739

    Article  Google Scholar 

  17. Reddy JN, Chin CD (1998) Thermo-mechanical analysis of functionally graded cylinders and plates. J Therm Stresses 21(6):593–626

    Article  Google Scholar 

  18. Li L, Wang T (2005) A unified approach to predict overall properties of composite materials. Mater Charact 54(1):49–62

    Article  Google Scholar 

  19. Nguyen T-K, Sab K, Bonnet G (2008) First-order shear deformation plate models for functionally graded materials. Compos Struct 83(1):25–36

    Article  Google Scholar 

  20. Ravichandran K (1995) Thermal residual stresses in a functionally graded material system. Mater Sci Eng A 201:269–276

    Google Scholar 

  21. Shaw LL (1998) Thermal residual stresses in plates and coatings composed of multi-layered and functionally graded materials. Composites B 29B:199–210

    Article  Google Scholar 

  22. Becker T Jr, Cannon R, Ritchie R (2000) An approximate method for residual stress calculation in functionally graded materials. Mech Mater 32:85–97

    Article  Google Scholar 

  23. Babu B, Jehan M (2003) Differential evolution for multi-objective optimization. In: Proceedings ofthe 2003 Congress on Evolutionary Computation (CEC-2003), Canberra, Australia, pp 2696–2703

    Google Scholar 

  24. Price K, Storn RM, Lampinen JA (2005) Differential Evolution: a practical approach to global optimization, ser. Natural computing series. Springer, New York

    Google Scholar 

  25. Chakraborty UK (2008) Advances in differential evolution, 1st edn. Springer, New York

    Book  MATH  Google Scholar 

Download references

Acknowledgments

This work was partially supported by the Portuguese Foundation for Science and Technology (FCT) through the Project PTDC/EME-PME/120830/2010 and the PhD grant SFRH/BD/44696/2008.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. A. N. Silva .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Silva, T.A.N., Loja, M.A.R. (2013). Differential Evolution on the Minimization of Thermal Residual Stresses in Functionally Graded Structures. In: Madureira, A., Reis, C., Marques, V. (eds) Computational Intelligence and Decision Making. Intelligent Systems, Control and Automation: Science and Engineering, vol 61. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4722-7_27

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-4722-7_27

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-4721-0

  • Online ISBN: 978-94-007-4722-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics