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Parallelization of the Monte Carlo Static Recrystallization Model

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Book cover eScience on Distributed Computing Infrastructure

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8500))

Abstract

Implementation of parallel version of the Monte Carlo (MC) static recrystallization algorithm for application in the PL-Grid Infrastructure is presented in this work. General assumptions of the algorithm are described first. This is followed by presentation of modifications that were introduced and are required for the parallel execution. Monte Carlo space division schemes between subsequent computing nodes are particularly addressed. Implementation details are also presented. Finally, influence of size and geometry of the MC space on calculations efficiency is discussed.

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References

  1. Sieradzki, L., Madej, L.: A perceptive comparison of the cellular automata and Monte Carlo techniques in application to static recrystallization modeling in polycrystalline materials. Computational Material Science 67, 156–173 (2013)

    Article  Google Scholar 

  2. Madej, Ł., Rauch, Ł., Perzyński, K., Cybułka, P.: Digital Material Representation as an efficient tool for strain inhomogeneities analysis at the micro scale level. Archives of Civil and Mechanical Engineering 11, 661–679 (2011)

    Article  Google Scholar 

  3. Szyndler, J., Madej, L.: Effect of number of grains and boundary conditions on digital material representation deformation under plain strain. Archives of Civil and Mechanical Engineering (2013), http://dx.doi.org/10.1016/j.acme.2013.09.001

  4. Kalos, M.H., Whitlock, P.A.: Monte Carlo Methods. Wiley-VCH (2008)

    Google Scholar 

  5. Humphreys, M.J., Hatherly, M.: Recrystallization and related annealing phenomena, 2nd edn. Elsevier, Oxford (2004)

    Google Scholar 

  6. Doherty, R.D., Hughes, D.A., Humphreys, F.J., Jonas, J.J., Juul Jensen, D., Kassner, M.E., King, W.E., McNelley, T.R., McQueen, H.J., Rollett, A.D.: Current issues in recrystallization: a review. Materials Science and Engineering 238, 219–274 (1997)

    Article  Google Scholar 

  7. Chun, Y.B., Siemiatin, S.L., Hwang, S.K.: Monte Carlo modeling of microstructure evolution during the static recrystallization of cold-rolled, commercial-purity titanium. Scripta Materialia 54, 3673–3689 (2006)

    Article  Google Scholar 

  8. Ivasishin, O.M., Shevchenko, S.V., Vasiliev, N.L., Semiatin, S.L.: A 3-D Monte Carlo (Potts) model for recrystallization and grain growth in polycrystalline materials. Materials Science and Engineering A 422, 216–232 (2006)

    Article  Google Scholar 

  9. Rollett, A.D., Manohar, P.: The Monte Carlo method. In: Raabe, D., Roters, F., Chen, L.-Q. (eds.) Continuum Scales Simulation of Engineering Materials, pp. 76–113. Wiley-VCH (2004)

    Google Scholar 

  10. Walasek, T.A.: Experimental verification of Monte Carlo recrystallization model. Journal of Material Processing Technology 157- 158, 262–267 (2004)

    Article  Google Scholar 

  11. Goetz, R.L., Seetharaman, V.: Static recrystallization kinetics with homogeneous and heterogeneous nucleation using a cellular automata model. Metallurgical and Materials Transactions A 29A, 1998–2307 (1997)

    Google Scholar 

  12. Sitko, M., Dybich, D., Szyndler, J., Madej, L.: Parallelization of the Monte Carlo grain growth algorithm. Materials Science & Technology 2013, 1657–1667 (2013)

    Google Scholar 

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Madej, Ł., Sitko, M. (2014). Parallelization of the Monte Carlo Static Recrystallization Model. In: Bubak, M., Kitowski, J., Wiatr, K. (eds) eScience on Distributed Computing Infrastructure. Lecture Notes in Computer Science, vol 8500. Springer, Cham. https://doi.org/10.1007/978-3-319-10894-0_32

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  • DOI: https://doi.org/10.1007/978-3-319-10894-0_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10893-3

  • Online ISBN: 978-3-319-10894-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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