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Construction of dynamic three-dimensional microstructure for the hydration of cement using 3D image registration


Microstructure is one of the most important research issues in the field of cement hydration. The absence of imaging dynamic three-dimensional microstructure influences the investigation of cement hydration. Furthermore, it is impossible to confirm computer hydration models from real data perspective due to the lack of images of dynamic 3D microstructure. The evolution of the three-dimensional microstructure cannot be observed in situ easily. This article proposes an image registration-based approach to capture dynamic three-dimensional microstructure, whose original images are collected using microtomography. This is the first time that the dynamic 3D microstructure is imaged and analyzed for the hydration of cement. It allows imaging dynamic 3D microstructure for hydrating cement without using any extra equipment. Our research results indicate that the dynamic microstructure is captured easily with low cost and good precision.

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  1. 1.

    Chen W, Brouwers HJH (2008) Mitigating the effects of system resolution on computer simulation of Portland cement hydration. Cement Concrete Compos 30(9):779–787

    Article  Google Scholar 

  2. 2.

    Thomas JJ, Biernacki JJ, Bullard JW et al (2011) Modeling and simulation of cement hydration kinetics and microstructure development. Cement Concrete Res 41(12):1257–1278

    Article  Google Scholar 

  3. 3.

    van Breugel K (1995) Numerical simulation of hydration and microstructural development in hardening cement paste (I): theory. Cement Concrete Res 25(2):319–331

    Article  Google Scholar 

  4. 4.

    Bentz DP (1997) Three-dimensional computer simulation of cement hydration and microstructure development. J Am Ceram Soc 80(1):3–21

    Article  Google Scholar 

  5. 5.

    Bullard JW (2007) A three-dimensional microstructural model of reactions and transport in aqueous mineral systems. Model Simul Mater Sci Eng 15(7):711–738

    Article  Google Scholar 

  6. 6.

    Bishnoi S, Scrivener KL (2009) μic: a new platform for modelling the hydration of cements. Cement Concrete Res 39(4):266–274

    Article  Google Scholar 

  7. 7.

    Bentz DP, Mizell S, Satterfield S et al (2002) The visible cement data set. J Res Natl Inst Stand Technol 107(2):137–148

    Article  Google Scholar 

  8. 8.

    Gallucci E, Scrivener K, Groso A et al (2007) 3D experimental investigation of the microstructure of cement pastes using synchrotron X-ray microtomography (μCT). Cement Concrete Res 37(3):360–368

    Article  Google Scholar 

  9. 9.

    Promentilla MAB, Sugiyama T, Shimura K (2008) Three-dimensional imaging of cement-based materials with X-ray tomographic microscopy: visualization and quantification. Int Conf Microstruct Relat Durab Cem Compos 61:1357–1366

    Google Scholar 

  10. 10.

    Pourchez J, Ruot B, Debayle J, Pourchez E, Grosseau P (2010) Some aspects of cellulose ethers influence on water transport and porous structure of cement-based materials. Cement Concrete Res 40(2):242–252

    Article  Google Scholar 

  11. 11.

    Skalny J, Gebauer J, Odler I (2001) Scanning electron microscopy in concrete petrography. Materials Scien Concrete Special Volume: Calcium Hydroxide in Concrete, pp 59–72

  12. 12.

    Venkiteela G, Sun Z (2010) In situ observation of cement particle growth during setting. Cement Concrete Compos 32(3):211–218

    Article  Google Scholar 

  13. 13.

    Zitova B, Flusser J (2003) Image registration methods: a survey. Image Vision Comput 21(11):977–1000

    Article  Google Scholar 

  14. 14.

    Fowlkes CC, Luengo Hendriks CL, Keranen SVE et al (2008) A quantitative spatiotemporal atlas of gene expression in the Drosophila Blastoderm. Cell (Cambridge, MA, US) 133(2):364–374

    Article  Google Scholar 

  15. 15.

    Tomer R, Denes AS, Tessmar-Raible K et al (2010) Profiling by image registration reveals common origin of annelid mushroom bodies and vertebrate pallium. Cell (Cambridge, MA, US) 142(5):800–809

    Article  Google Scholar 

  16. 16.

    Grunwald D, Singer RH (2010) In vivo imaging of labelled endogenous b-actin mRNA during nucleocytoplasmic transport. Nat Biotechnol 467(7315):604–607

    Article  Google Scholar 

  17. 17.

    Wong A, Clausi DA (2007) ARRSI: automatic registration of remote-sensing images. IEEE Trans Geosci Remote Sens 45(5):1483–1493

    Article  Google Scholar 

  18. 18.

    Ketcham RA, Carlson WD (2001) Acquisition, optimization and interpretation of X-ray computed tomographic imagery: applications to the geosciences. Comput Geosci 27(4):381–400

    Article  Google Scholar 

  19. 19.

    Herman GT (1979) Correction for beam hardening in computed tomography. Phys Med Biol 24(1):81–106

    Article  Google Scholar 

  20. 20.

    Sijbersand J, Postnov A (2004) Reduction of ring artifacts in high resolution micro-CT reconstructions. Phys Med Biol 49(14):247–253

    Article  Google Scholar 

  21. 21.

    Lehmann TM, Gonner C, Spitzer K (1999) Survey: interpolation methods in medical image processing. IEEE Trans Med Imaging 18(11):1049–1075

    Article  Google Scholar 

  22. 22.

    Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor

    Google Scholar 

  23. 23.

    Eberhart RC, Kennedy J (1995) A new optimizer using pariticle swarm theory. The 6th International Symposium on Micromachine and Human Science, pp 39–43

  24. 24.

    Powell MJD (1964) An efficient method for finding the minimum of a function of several variables without calculating derivatives. Comput J 7(2):155–162

    Article  MATH  MathSciNet  Google Scholar 

  25. 25.

    Tang M (2011) Automatic registration and fast volume reconstruction from serial histology sections. Comput Vision Image Underst 115(8):1112–1120

    Article  Google Scholar 

  26. 26.

    Wachowiak MP, Peters TM (2006) High-performance medical image registration using new optimization techniques. IEEE Trans Inf Technol Biomed 10(2):344–353

    Article  Google Scholar 

  27. 27.

    Mumcuoglu EU, Nar F, Yardimci Y et al (2006) Simultaneous surface registration of ictal and interictal SPECT and magnetic resonance images for epilepsy studies. Nuclear Med Commun 27(1):45–55

    Article  Google Scholar 

  28. 28.

    Bogue RH (1955) The chemistry of Portland cement. Reinhold Publishing Corporation, New York

    Google Scholar 

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This work was supported by National Key Technology Research and Development Program of the Ministry of Science and Technology under Grant 2012BAF12B07-3. National Natural Science Foundation of China under Grant No. 61173078, No. 61203105, No. 61173079, No. 61070130, No. 60903176. Provincial Natural Science Foundation for Outstanding Young Scholars of Shandong under Grant No. JQ200820. Shandong Provincial Natural Science Foundation, China, under Grant No. ZR2010FM047, No. ZR2012FQ016, No. ZR2012FM010. Program for New Century Excellent Talents in University under Grant No. NCET-10-0863.

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Correspondence to Bo Yang.

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Wang, L., Yang, B., Abraham, A. et al. Construction of dynamic three-dimensional microstructure for the hydration of cement using 3D image registration. Pattern Anal Applic 17, 655–665 (2014).

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  • Image registration
  • Microtomography
  • Cement hydration
  • Microstructure