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Estimation of the thermal conductivity of hemp based insulation material from 3D tomographic images

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Abstract

In this work, we are interested in the structural and thermal characterization of natural fiber insulation materials. The thermal performance of these materials depends on the arrangement of fibers, which is the consequence of the manufacturing process. In order to optimize these materials, thermal conductivity models can be used to correlate some relevant structural parameters with the effective thermal conductivity. However, only a few models are able to take into account the anisotropy of such material related to the fibers orientation, and these models still need realistic input data (fiber orientation distribution, porosity, etc.). The structural characteristics are here directly measured on a 3D tomographic image using advanced image analysis techniques. Critical structural parameters like porosity, pore and fiber size distribution as well as local fiber orientation distribution are measured. The results of the tested conductivity models are then compared with the conductivity tensor obtained by numerical simulation on the discretized 3D microstructure, as well as available experimental measurements. We show that 1D analytical models are generally not suitable for assessing the thermal conductivity of such anisotropic media. Yet, a few anisotropic models can still be of interest to relate some structural parameters, like the fiber orientation distribution, to the thermal properties. Finally, our results emphasize that numerical simulations on 3D realistic microstructure is a very interesting alternative to experimental measurements.

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Abbreviations

cp :

Specific heat (J kg−1 K−1)

l:

Length of fibers (m)

R:

Radius (m)

T:

Temperature (°C)

t:

Time (s)

V:

Volume of fibers (m3)

x, y, z:

Spatial axes

β :

Volume concentration

λ:

Thermal conductivity (W m−1 K−1)

φ:

Polar angle (°)

θ:

Volume fraction; azimuth angle (°)

ρ:

Density (kg m−3)

a:

Air

eq:

Equivalent

h:

Hemp

f:

Fiber

p:

Polymer

References

  1. Thygesen A (2006) Properties of hemp fibre polymer composites - An optimisation of fibre properties using novel defibration methods and fibre characterisation. Ph.D. thesis. Risø-PhD–11(EN)

  2. Arnaud L, Cerezo V (2002) Mechanical, thermal, and acoustical properties of concrete containing vegetable particles. ACI Spec Publ 209. doi:10.14359/12499.p151-168

    Google Scholar 

  3. Lux J, Delisée C, Thibault X (2011) 3D characterization of wood based fibrous materials: an application. Image Anal Stereol 25:25–35. doi:10.5566/ias.v25.p25-35

    Article  Google Scholar 

  4. Rolland du Roscoat S, Decain M, Thibault X et al (2007) Estimation of microstructural properties from synchrotron X-ray microtomography and determination of the REV in paper materials. Acta Mater 55:2841–2850. doi:10.1016/j.actamat.2006.11.050

    Article  Google Scholar 

  5. Dirrenberger J (2012) Propriétés effectives de matériaux architecturés. PhD Thesis, Ecole Nationale Supérieure des Mines de Paris, Paris

    Google Scholar 

  6. Delisée C, Lux J, Malvestio J (2010) 3D morphology and permeability of highly porous cellulosic fibrous material. Transp Porous Media 83:623–636. doi:10.1007/s11242-009-9464-4

    Article  Google Scholar 

  7. Bernard D, Nielsen Ø, Salvo L, Cloetens P (2005) Permeability assessment by 3D interdendritic flow simulations on microtomography mappings of Al–Cu alloys. Mater Sci Eng A 392:112–120. doi:10.1016/j.msea.2004.09.004

    Article  Google Scholar 

  8. Lux J, Ahmadi A, Gobbé C, Delisée C (2006) Macroscopic thermal properties of real fibrous materials: volume averaging method and 3D image analysis. Int J Heat Mass Transf 49:1958–1973. doi:10.1016/j.ijheatmasstransfer.2005.09.038

    Article  MATH  Google Scholar 

  9. Lux J (2013) Automatic segmentation and structural characterization of low density fibreboards. Image Anal Stereol 32:13–25. doi:10.5566/ias.v32.p13-25

    Article  MathSciNet  Google Scholar 

  10. Collet F, Bart M, Serres L, Miriel J (2008) Porous structure and water vapour sorption of hemp-based materials. Constr Build Mater 22:1271–1280. doi:10.1016/j.conbuildmat.2007.01.018

    Article  Google Scholar 

  11. Whitaker S (1998) The method of volume averaging. Springer, Berlin

    Google Scholar 

  12. Serra J (1986) Introduction to mathematical morphology. Academic Press, New York

    MATH  Google Scholar 

  13. Serra J (1994) Morphological filtering: an overview. Signal Process 38:3–11. doi:10.1016/0165-1684(94)90052-3

    Article  MATH  Google Scholar 

  14. Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12:629–639. doi:10.1109/34.56205

    Article  Google Scholar 

  15. Siau JF (1984) Transport processes in wood. Springer, Berlin

    Book  Google Scholar 

  16. Altendorf H, Jeulin D (2011) 3D directional mathematical morphology for analysis of fiber orientations. Image Anal Stereol 28:143–153. doi:10.5566/ias.v28.p143-153

    Article  MathSciNet  MATH  Google Scholar 

  17. Nozad I, Carbonell RG, Whitaker S (1985) Heat conduction in multiphase systems—I: theory and experiment for two-phase systems. Chem Eng Sci 40:843–855. doi:10.1016/0009-2509(85)85037-5

    Article  Google Scholar 

  18. Quintard M, Whitaker S (1993) One- and two-equation models for transient diffusion processes in two-phase systems. In: Hartnett JP, Irvine TF (eds) Adv Heat Transf. Elsevier, pp 369–464

  19. Lux J (2005) Comportement thermique macroscopique de milieux fibreux réels anisotropes: étude basée sur l’analyse d’images tridimensionnelles. PhD Thesis, Université Sciences et Technologies-Bordeaux I

  20. Kanit T, Forest S, Galliet I et al (2003) Determination of the size of the representative volume element for random composites: statistical and numerical approach. Int J Solids Struct 40:3647–3679. doi:10.1016/S0020-7683(03)00143-4

    Article  MATH  Google Scholar 

  21. Wang M, Pan N (2008) Predictions of effective physical properties of complex multiphase materials. Mater Sci Eng R Rep 63:1–30. doi:10.1016/j.mser.2008.07.001

    Article  Google Scholar 

  22. Carson JK, Lovatt SJ, Tanner DJ, Cleland AC (2003) An analysis of the influence of material structure on the effective thermal conductivity of theoretical porous materials using finite element simulations. Int J Refrig 26:873–880. doi:10.1016/S0140-7007(03)00094-X

    Article  Google Scholar 

  23. Zhu QY, Xie MH, Yang J, Li Y (2010) Investigation of the 3D model of coupled heat and liquid moisture transfer in hygroscopic porous fibrous media. Int J Heat Mass Transf 53:3914–3927. doi:10.1016/j.ijheatmasstransfer.2010.05.010

    Article  MATH  Google Scholar 

  24. Pal R (2008) On the Lewis–Nielsen model for thermal/electrical conductivity of composites. Compos Part Appl Sci Manuf 39:718–726. doi:10.1016/j.compositesa.2008.02.008

    Article  Google Scholar 

  25. Kumlutaş D, Tavman İH, Turhan Çoban M (2003) Thermal conductivity of particle filled polyethylene composite materials. Compos Sci Technol 63:113–117. doi:10.1016/S0266-3538(02)00194-X

    Article  Google Scholar 

  26. Wyllie MRJ, Southwick PF (1954) An experimental investigation of the S.P. and resistivity phenomena in dirty sands. J Pet Technol 6:44–57. doi:10.2118/302-G

    Article  Google Scholar 

  27. Krischer O, Kast W (1978) Die wissenschaftlichen grundlagen der trocknungstechnik. Springer, Berlin

    Google Scholar 

  28. Peyrega C, Jeulin D, Delisée C, Malvestio J (2011) 3D morphological modelling of a random fibrous network. Image Anal Stereol 28:129–141. doi:10.5566/ias.v28.p129-141

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

The authors would like to thank the Poitou–Charentes Region for its financial support.

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Correspondence to J. Lux.

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El-Sawalhi, R., Lux, J. & Salagnac, P. Estimation of the thermal conductivity of hemp based insulation material from 3D tomographic images. Heat Mass Transfer 52, 1559–1569 (2016). https://doi.org/10.1007/s00231-015-1674-4

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  • DOI: https://doi.org/10.1007/s00231-015-1674-4

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