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Simulation of isothermal precision extrusion of NiTi shape memory alloy pipe coupling by combining finite element method with cellular automaton

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Abstract

In order to present the microstructures of dynamic recrystallization (DRX) in different deformation zones of hot extruded NiTi shape memory alloy (SMA) pipe coupling, a simulation approach combining finite element method (FEM) with cellular automaton (CA) was developed and the relationship between the macroscopic field variables and the microscopic internal variables was established. The results show that there exists a great distinction among the microstructures in different zones of pipe coupling because deformation histories of these regions are diverse. Large plastic deformation may result in fine recrystallized grains, whereas the recrystallized grains may grow very substantially if there is a rigid translation during the deformation, even if the final plastic strain is very large. As a consequence, the deformation history has a significant influence on the evolution path of the DRX as well as the final microstructures of the DRX, including the morphology, the mean grain size and the recrystallization fraction.

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References

  1. OTSUKA K, REN X. Physical metallurgy of Ti–Ni-based shape memory alloys [J]. Progress in Materials Science, 2005, 50(5): 511–678.

    Article  Google Scholar 

  2. JANI J M, LEARY M, SUBIC A, GIBSON M A. A review of shape memory alloy: Research, applications and opportunities [J]. Materials Design, 2014, 56: 1078–1113.

    Article  Google Scholar 

  3. JEE K K, HAN J H, JANG W Y. A method of pipe joining using shape memory alloys [J]. Materials Science and Engineering A, 2006, 438-440: 1110–1112.

    Article  Google Scholar 

  4. WANG L, RONG L J, YAN D S, JING Z M, LI Y Y. DSC study of the reverse martensitic transformation behavior in a SMA pipe-joint [J]. Intermetallics, 2005, 13(3, 4): 403–407.

    Article  Google Scholar 

  5. KHAMEI A A, DEHGHANI K. A study on the mechanical behavior and microstructural evolution of Ni60wt%-Ti40wt% (60Nitinol) intermetallic compound during hot deformation [J]. Materials Chemistry and Physics, 2010, 123(1): 269–277.

    Article  Google Scholar 

  6. MORAKABATI M, KHEIRANDISH S, ABOUTALEBI M, KARIMI T A, ABBASI S M. A study on the hot workability of wrought NiTi shape memory alloy [J]. Materials Science and Engineering A, 2011, 528(18): 5656–5663.

    Article  Google Scholar 

  7. HUANG Xu, LIU Yong. Effect of annealing on the transformation behavior and superelasticity of NiTi shape memory alloy [J]. Scripta Materialia, 2001, 45(2): 153–160.

    Article  Google Scholar 

  8. JIANG Shu-yong, ZHANG Yan-qiu, ZHAO Ya-nan. Dynamic recovery and dynamic recrystallization of NiTi shape memory alloy under hot compression deformation [J]. Transactions of Nonferrous Metals Society of China, 2013, 23(1): 140–147.

    Article  Google Scholar 

  9. JANSSENS K G F. An introductory review of cellular a modeling of moving grain boundaries in polycrystalline materials [J]. Mathematics and Computers in Simulation, 2010, 80(7): 1361–1381.

    Article  MathSciNet  MATH  Google Scholar 

  10. YAZDIPOUR N, DAVIES C H J, HODGSON P D. Microstructural modeling of dynamic recrystallization using irregular cellular automata [J]. Computational Materials Science, 2008, 44(2): 566–576.

    Article  Google Scholar 

  11. SEYED S M, SERAJZADEH S. Simulation of static recrystallization in non-isothermal annealing using a coupled cellular automata and finite element model [J]. Computational Materials Science, 2012, 53(1): 145–152.

    Article  Google Scholar 

  12. SVYETLICHNYY D S, MUSZKA K, MAJTA J. Three-dimensional frontal cellular automata modeling of the grain refinement during severe plastic deformation of microalloyed steel [J]. Computational Materials Science, 2015, 102: 159–166.

    Article  Google Scholar 

  13. CHEN Fei, QI K, CUI Zhen-shan, LAI Xin-min. Modeling the dynamic recrystallization in austenitic stainless steel using cellular automaton method [J]. Computational Materials Science, 2014, 83: 331–340.

    Article  Google Scholar 

  14. TIMOSHENKOV A, WARCZOK P, ALBU M, KLARNER J, KOZESCHNIK E, BUREAU R, SOMMITSCH C. Modelling the dynamic recrystallization in C–Mn micro-alloyed steel during thermo-mechanical treatment using cellular automata [J]. Computational Materials Science, 2014, 94: 85–94.

    Article  Google Scholar 

  15. LIU Xiao, LI Luo-xing, HEI Feng-yi, ZHOU J, ZHU Bi-wu, ZHANG Li-qiang. Simulation on dynamic recrystallization behavior of AZ31 magnesium alloy using cellular automaton method coupling Laasraoui-Jonas model [J]. Transactions of Nonferrous Metals Society of China, 2013, 23(9): 2692–2699.

    Article  Google Scholar 

  16. LIU Y X, LIU Y C, LI H B, WEN D X, CHEN X M, CHEN M S. Study of dynamic recrystallization in a Ni-based superalloy by experiments and cellular automaton model [J]. Materials Science and Engineering A, 2015, 626: 432–440.

    Article  Google Scholar 

  17. ZHANG Yan-qiu, JIANG Shu-yong, LIANG Yu-long, HU Li. Simulation of dynamic recrystallization of NiTi shape memory alloy during hot compression deformation based on cellular automaton [J]. Computational Materials Science, 2013, 71: 124–134.

    Article  Google Scholar 

  18. LEE H W, IM Y T. Numerical modeling of dynamic recrystallization during nonisothermal hot compression by cellular automata and finite element analysis [J]. International Journal of Mechanical Sciences, 2010, 52(10): 1277–1289.

    Article  Google Scholar 

  19. DING R, GUO Z X. Microstructural modelling of dynamic recrystallisation using an extended cellular automaton approach [J]. Computational Materials Science, 2002, 23(1-4): 209–218.

    Article  Google Scholar 

  20. KUGLER G, TURK R. Modeling the dynamic recrystallization under multi-stage hot deformation [J]. Acta Materialia 2004, 52(15): 4659–4668.

    Article  Google Scholar 

  21. ROBERTS W, AHLBLOM B. A nucleation criterion for dynamic recrystallization during hot working [J]. Acta Metallurgica, 1978, 26(5): 801–813.

    Article  Google Scholar 

  22. DING R, GUO Z X. Microstructural evolution of a Ti–6Al–4V alloy during ß-phase processing: Experimental and simulative investigations [J]. Materials Science and Engineering A, 2004, 365(1-2): 172–17

    Article  Google Scholar 

  23. CHEN Fei, CUI Zhen-shan, LIU Juan, CHEN Wen, CHEN Shi-jia. Mesoscale simulation of the high-temperature austenitizing and dynamic recrystallization by coupling a cellular automaton with a topology deformation technique [J]. Materials Science and Engineering A, 2010, 527(21, 22): 5539–5549.

    Article  Google Scholar 

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Correspondence to Shu-yong Jiang  (江树勇).

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Foundation item: Projects(51305091, 51475101) supported by the National Natural Science Foundation of China; Project(20132304120025) supported by Specialized Research Fund for the Doctoral Program of Higher Education, China

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Zhang, Yq., Jiang, Sy., Zhao, Yn. et al. Simulation of isothermal precision extrusion of NiTi shape memory alloy pipe coupling by combining finite element method with cellular automaton. J. Cent. South Univ. 24, 506–514 (2017). https://doi.org/10.1007/s11771-017-3453-5

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  • DOI: https://doi.org/10.1007/s11771-017-3453-5

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