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An experimental and numerical coupled method to predict grain refinement and mechanical properties of gradient microstructure material by shot peening

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Abstract

In this paper, an innovative method is proposed to predict the microstructure evolution of the material during shot peening, in which a coupled model uses the finite element method (FEM) and cellular automaton (CA) in DEFORM software. The model can obtain the macroscopic (stress–strain response) and microscopic (texture) properties of the material during shot peening. A coupled experimental and numerical method is proposed to establish the relationship between shot peening process parameters and grain size by equivalent plastic strain. The model takes into account the number of shot in the actual process on a large scale. This new coupling method enables rapid prediction of the grain size distribution of the surface layer and improvement of the constitutive model of grade materials. Then, taking aluminum alloy as the object, the grain refinement, grain size distribution, and plastic behavior induced by shot peening were investigated using this method. The results show that the stresses induced by shot peening have a significant influence on the mechanical behavior and grain size evolution of gradient materials.

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References

  1. Miao HY et al (2010) Experimental study of shot peening and stress peen forming. J Mater Process Technol 210(15):2089–2102

    Article  Google Scholar 

  2. Hassani-Gangaraj SM et al (2015) Experimental assessment and simulation of surface nanocrystallization by severe shot peening. Acta Mater 97:105–115

    Article  Google Scholar 

  3. Shen N, Samanta A, Ding H (2017) Microstructure simulations for orthogonal cutting via a cellular automaton model. Procedia CIRP 58:543–548

    Article  Google Scholar 

  4. Zhao J et al (2019) Deformation mechanisms based constitutive modelling and strength-ductility mapping of gradient nano-grained materials. Mater Sci Eng, A 742:400–408

    Article  Google Scholar 

  5. Gariépy A et al (2012) Potential applications of peen forming finite element modelling. Adv Eng Softw 52:60–71

    Article  Google Scholar 

  6. Xie L et al (2011) Investigation on the residual stress and microstructure of (TiB+TiC)/Ti–6Al–4V composite after shot peening. Mater Sci Eng, A 528(9):3423–3427

    Article  Google Scholar 

  7. Liu YG, Li HM, Li MQ (2020) Roles for shot dimension, air pressure and duration in the fabrication of nanocrystalline surface layer in TC17 alloy via high energy shot peening. J Manuf Process 56:562–570

    Article  Google Scholar 

  8. Liu H et al (2019) Investigation on microstructure and properties of Al18B4O33 whisker reinforced Al Mg Si matrix composite after shot peening. Vacuum 160:303–310

    Article  Google Scholar 

  9. Chen M et al (2018) Evaluation of the residual stress and microstructure character in SAF 2507 duplex stainless steel after multiple shot peening process. Surf Coat Technol 344:132–140

    Article  Google Scholar 

  10. Chen M et al (2018) Residual stress and microstructure evolutions of SAF 2507 duplex stainless steel after shot peening. Appl Surf Sci 459:155–163

    Article  Google Scholar 

  11. Wang Z et al (2011) XRD investigation of microstructure strengthening mechanism of shot peening on laser hardened 17–4PH. Mater Sci Eng, A 528(21):6417–6425

    Article  Google Scholar 

  12. Wang C et al (2020) Dislocation-based study on the influences of shot peening on fatigue resistance. Surf Coat Technol 383:125247

    Article  Google Scholar 

  13. Estrin Y, Kim HS (2007) Modelling microstructure evolution toward ultrafine crystallinity produced by severe plastic deformation. J Mater Sci 42(5):1512–1516

    Article  Google Scholar 

  14. Zhao J et al (2020) Multiple mechanism based constitutive modeling of gradient nanograined material. Int J Plast 125:314–330

    Article  Google Scholar 

  15. Huang H et al (2019) The study of universality of a method for predicting surface nanocrystallization after high energy shot peening based on finite element analysis. Surf Coat Technol 358:617–627

    Article  Google Scholar 

  16. Wang C et al (2018) Numerical study of grain refinement induced by severe shot peening. Int J Mech Sci 146–147:280–294

    Article  Google Scholar 

  17. Lin Q et al (2020) Effects of different shot peening parameters on residual stress, surface roughness and cell size. Surf Coat Technol 398:126054

    Article  Google Scholar 

  18. Majzoobi GH, Azadikhah K, Nemati J (2009) The effects of deep rolling and shot peening on fretting fatigue resistance of Aluminum-7075-T6. Mater Sci Eng, A 516(1–2):235–247

    Article  Google Scholar 

  19. Li X et al (2017) Simulation of dynamic recrystallization in AZ80 magnesium alloy using cellular automaton. Comput Mater Sci 140:95–104

    Article  Google Scholar 

  20. Lu J et al (2018) Thermal deformation behavior and processing maps of 7075 aluminum alloy sheet based on isothermal uniaxial tensile tests. J Alloy Compd 767:856–869

    Article  Google Scholar 

  21. Saluja RS, Ganesh Narayanan R, Das S (2012) Cellular automata finite element (CAFE) model to predict the forming of friction stir welded blanks. Computational Materials Science 58:87–100

    Article  Google Scholar 

  22. Seetharaman, R., Static recrystallization kinetics with homogeneous and heterogeneous nucleation using a cellular automata model. Metallurgical&Materials Transactions A, 1998.

  23. Xie L et al (2012) Investigation on experiments and numerical modelling of the residual stress distribution in deformed surface layer of Ti–6Al–4V after shot peening. Mater Des 41:314–318

    Article  Google Scholar 

  24. Wu J et al (2020) Effect of shot peening coverage on residual stress and surface roughness of 18CrNiMo7-6 steel. Int J Mech Sci 183:105785

    Article  Google Scholar 

  25. Bagherifard S, Ghelichi R, Guagliano M (2014) Mesh sensitivity assessment of shot peening finite element simulation aimed at surface grain refinement. Surf Coat Technol 243:58–64

    Article  Google Scholar 

  26. Valiev RZ et al (1996) Structure and deformaton behaviour of Armco iron subjected to severe plastic deformation. Acta Mater 44(12):4705–4712

    Article  Google Scholar 

  27. Umemoto, M., et al (2003) Characterization of bulk cementite produced by mechanical alloying and spark plasma sintering. J Metastable and Nanocrystalline Materials 15–16

  28. Yang C et al (2020) Microstructure characterization and tensile properties of processed TC17 via high energy shot peening. Mater Sci Eng, A 784:139298

    Article  Google Scholar 

  29. Wang C et al (2022) Experimental and simulation study of multi-region peen forming and mechanical property. J Manuf Process 84:198–215

    Article  Google Scholar 

  30. González, J., et al (2017) Influence of different shot peening treatments on surface state and fatigue behaviour of Al 6063 alloy. Engineering Fracture Mechanics

  31. Erfan, M. and U. Okan (2018) Roles of surface coverage increase and repeening on properties of AISI 1045 carbon steel in conventional and severe shot peening processes. Surfaces and Interfaces 82–96

  32. Jamalian M, Field DP (2019) Effects of shot peening parameters on gradient microstructure and mechanical properties of TRC AZ31. Mater Charact 148:9–16

    Article  Google Scholar 

  33. Bagherifard S et al (2014) Effect of severe shot peening on microstructure and fatigue strength of cast iron. Int J Fatigue 65:64–70

    Article  Google Scholar 

  34. Amanov A et al (2019) Effect of combined shot peening and ultrasonic nanocrystal surface modification processes on the fatigue performance of AISI 304. Surf Coat Technol 358:695–705

    Article  Google Scholar 

  35. Rodríguez-Baracaldo R, Benito JA, Cabrera JM (2010) Tensile and compressive test in nanocrystalline and ultrafine carbon steel. J Mater Sci 45(17):4796–4804

    Article  Google Scholar 

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Correspondence to Xuemei Chen.

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Wang, C., Wang, Y., Peng, J. et al. An experimental and numerical coupled method to predict grain refinement and mechanical properties of gradient microstructure material by shot peening. Int J Adv Manuf Technol 128, 5331–5352 (2023). https://doi.org/10.1007/s00170-023-12248-6

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