Skip to main content
Log in

Estimation of fiber orientation and fiber bundles of MDF

  • Original Article
  • Published:
Materials and Structures Aims and scope Submit manuscript

Abstract

This paper presents numerical methods for the characterization of fiber orientation and fiber bundles of medium density wood fiberboards (MDF). The strength and stiffness of MDF is significantly affected by the fiber orientation and fiber bundles. Proposed methods and results are necessary to virtually generate realistic fiber networks and optimize MDF by using computer simulations. Based on 3D \(\mu\)CT images for laboratory manufactured MDF with oriented fibers, the fiber orientation is calculated in two ways. Firstly, we use an image processing method based on Hessian matrix directly on \(\mu\)CT image. Secondly, we computed the effective heat conductivity by solving PDEs on a segmentation of the \(\mu\)CT image to estimate the fiber orientation. A fiber bundle segmentation method based on local fiber orientations is introduced. Fiber bundles, which are segmented by this method show good agreement with manually segmented ones. It was observed that fiber bundles are oriented in MDF plane with log-normal distribution of bundle length. The proposed methods are general and can be used also to calculate fiber orientation and segment fiber bundles in fiber concrete, paper, glass and carbon fiber composites.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Xavier J, Belini U, Pierron F, Morais J, Lousada J, Tomazello M (2012) Characterisation of the bending stiffness components of MDF panels from full-field slope measurements. Wood Sci. Technol 47(2):423–441

    Article  Google Scholar 

  2. Sliseris J, Andrä H, Kabel M, Dix B, Plinke B, Wirjadi O, Frolovs G (2014) Numerical prediction of the stiffness and strength of medium density fiberboards. Mech Mater 79:73–84

    Article  Google Scholar 

  3. S. Heyden. Network modelling for the evaluation of mechanical properties of cellulose fiber fluff. Ph.D. thesis, Division of Structural Mechanics, LTH, Lund University, 2000

  4. Awal A, Ghosh SB, Sain M (2009) Development and morphological characterization of wood pulp reinforced biocomposite fibers. J Mater Sci 44:2876–2881

    Article  Google Scholar 

  5. Akay M, Barkley D (1991) fibre orientation and mechanical behaviour in reinforced thermoplastic injection mouldings. J Mater Sci 26:2731–2742

    Article  Google Scholar 

  6. Laranjeira F, Grnewald S, Walraven J, Blom C, Molins C, Aguado A (2011) Characterization of the orientation profile of steel fiber reinforced concrete. Mater Struct 44(6):1093–1111

    Article  Google Scholar 

  7. Barnett Sj, Lataste J-F, Parry T, Millard SG, Soutsos MN (2010) Assessment of fibre orientation in ultra high performance fibre reinforced concrete and its effect on flexural strength. Mater Struct 43(7):1009–1023

    Article  Google Scholar 

  8. Viguié J, Latil P, Orgéas L, Dumont PJJ, Rolland du Roscoat S, Bloch J-F, Marulier C, Guiraud O (2013) Finding fibres and their contacts within 3D images of disordered fibrous media. Composit Sci Technol 89:202–210

    Article  Google Scholar 

  9. Redenbach C, Rack A, Schladitz K, Wirjadi O, Godehardt M (2012) Beyond imaging: on the quantitative analysis of tomographic volume data. Int J Mater Res (formerly Zeitschrift fuer Metallkunde) 103(02):217–227

    Article  Google Scholar 

  10. Krause M, Hausherr JM, Burgeth B, Herrmann C, Krenkel W (2009) Determination of the fibre orientation in composites using the structure tensor and local X-ray transform. J Mater Sci 45(4):888–896

    Article  Google Scholar 

  11. Robb K, Wirjadi O, Schladitz K (2007) Fiber orientation estimation from 3D image data: practical algorithms, visualization, and interpretation. In: 7th international conference on hybrid intelligent systems (HIS 2007), pp 320–325, Sept 2007

  12. Nishimura T, Ansell MP (2002) Fast Fourier transform and filtered image analyses of fiber orientation in OSB. Wood Sci Technol 36(4):287–307

    Article  Google Scholar 

  13. Bernasconi A, Cosmi F, Hine PJ (2012) Analysis of fibre orientation distribution in short fibre reinforced polymers: a comparison between optical and tomographic methods. Composi Sci Technol 72(16):2002–2008

    Article  Google Scholar 

  14. Suuronen J-P, Kallonen A, Eik M, Puttonen J, Serimaa R, Herrmann H (2013) Analysis of short fibres orientation in steel fibre-reinforced concrete (sfrc) by X-ray tomography. J Mater Sci 48:1358–1367

    Article  Google Scholar 

  15. Wille K, Tue NV, Parra-Montesinos GJ (2014) Fiber distribution and orientation in uhp-frc beams and their effect on backward analysis. Mater Struct 47(11):1825–1838

    Article  Google Scholar 

  16. Graupner N, Beckmann F, Wilde F, Müssig J (2014) Using synchroton radiation-based micro-computer tomography (sr l-ct) for the measurement of fibre orientations in cellulose fibre-reinforced polylactide (pla) composites. J Mater Sci 49:450–460

    Article  Google Scholar 

  17. Schulgasser K (1985) Fiber orientation in machine-made paper. J Mater Sci 20:859–866

    Article  Google Scholar 

  18. Tran H, Doumalin P, Delisee C, Dupre JC, Malvestio J, Germaneau A (2013) 3d mechanical analysis of low-density wood-based fiberboards by X-ray microcomputed tomography and digital volume correlation. J Mater Sci 48:3198–3212

    Article  Google Scholar 

  19. Behzad T, Sain M (2007) Measurement and prediction of thermal conductivity for hemp fiber reinforced composites. Polym Eng Sci 47(7):977–983

    Article  Google Scholar 

  20. Wang M, Kang Q, Pan N (2009) Thermal conductivity enhancement of carbon fiber composites. Appl Therm Eng 29(2):418–421

    Article  Google Scholar 

  21. Wirjadi O (2009) Models and algorithms for image-based analysis of microstructures. Ph.D. thesis, Technical University Kaiserslautern

  22. Altendorf H, Jeulin D (2009) 3D directional mathematical morphology for analysis of fiber orientations. Image Anal Stereol 28:143–153

    Article  MathSciNet  MATH  Google Scholar 

  23. Thoemen H, Walther T, Wiegmann A (2008) 3D simulation of macroscopic heat and mass transfer properties from the microstructure of wood fibre networks. Composit Sci Technol 68(3–4):608–616

    Article  Google Scholar 

  24. Moulinec H, Suquet P (1998) A numerical method for computing the overall response of nonlinear composites with complex microstructure. Comput Methods Appl Mech Eng 157(12):69–94

    Article  MathSciNet  MATH  Google Scholar 

  25. Eyre DJ, Milton GW (1999) A fast numerical scheme for computing the response of composites using grid refinement. Eur Phys J Appl Phys 6(01):41–47

    Article  Google Scholar 

  26. Fisher NI, Lewis T, Embleton BJJ (1987) Statistical analysis of spherical data. Cambridge University Press, Cambridge

  27. Liang H, Zhang C, Yan M (2009) A feldkamp-type approximate algorithm for helical multislice CT using extended scanning helix. Comput Med Imaging Graph 33(3):197–204

    Article  Google Scholar 

  28. MAVI 1.5.1.http://www.itwm.fraunhofer.de/abteilungen/bildverarbeitung/mikrostrukturanalyse/mavi.html . Accessed 10 Feb 2015

  29. FeelMath. http://www.itwm.fraunhofer.de/abteilungen/stroemungs-und-materialsimulation/festkoerpermechanik/feelmath.html. Accessed 10 Feb 2015

  30. Götz T, Klar A, Marheineke N, Wegener R (2007) A stochastic model and associated fokker-planck equation for the fiber lay-down process in nonwoven production processes. SIAM J Appl Math 67(6):1704–1717

    Article  MathSciNet  MATH  Google Scholar 

  31. GeoDict 2015. http://geodict.de/. Accessed 10 Feb 2015

Download references

Acknowledgments

The project IGF 17644N ”Simulation-supported development of medium density fibreboards for lightweight constructions” of the International Association for Technical Issues (iVTH) was funded through the German Federation of Industrial Research Associations (AiF) in the program for promoting the Industrial Collective Research (IGF) of the Federal ministry for economic Affairs and Energy (BMWi) on the basis of a decision of the German Bundestag. Thanks for GE Sensing & Inspection Technologies GmbH for \(\mu\)CT-images. The research leading to these results has received the funding from Latvia state research programme under grant agreement ”INNOVATIVE MATERIALS AND SMART TECHNOLOGIES FOR ENVIRONMENTAL SAFETY, IMATEH”. The research leading to these results has received the funding from Riga Technical University, Faculty of Building and Civil Engineering grant ”DOK.BIF”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Janis Sliseris.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sliseris, J., Andrä, H., Kabel, M. et al. Estimation of fiber orientation and fiber bundles of MDF. Mater Struct 49, 4003–4012 (2016). https://doi.org/10.1617/s11527-015-0769-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1617/s11527-015-0769-1

Keywords

Navigation