Heat and moisture diffusion in spruce and wood panels computed from 3-D morphologies using the Lattice Boltzmann method

Abstract

In this paper, the Lattice Boltzmann method is used to simulate heat and mass diffusion in bio-based building materials. The numerical method is presented and the methodology developed to reduce the calculation time is described. The 3-D morphologies of spruce and wood fibers are obtained using synchrotron X-ray micro-tomography. Equivalent macroscopic properties (heat conductivity and mass diffusivity) are therefore determined from the real micro-structure of the materials. The results reveal the anisotropy of the studied materials. The computed equivalent heat conductivity varies from 0.036 W m −1 K −1 to 0.52 W m −1 K −1 and the computed dimensionless mass diffusivity varies from 0.0088 to 0.78 depending on the materials and on the diffusion directions. Using these results, morphology families are identified and simple expressions are proposed to predict the equivalent properties as a function of phase properties and solid fraction.

Multiscale analysis of water vapor diffusion in low density fiberboard: Implications as a building material

“…The value 0.53 is consistent with both the asymptotic trend observed at large thicknesses (Fig. 4) and with the value computed on real 3D morphologies Louerat et al (2018). At the microscopic scale, the thermal conductivity is sufficient to ensure a uniform temperature inside the microscopic inclusion, which might, however, be different from the gaseous temperature due to coupling transfers at the interface.…”

“…To extrapolate the outcomes of this works to fiberboard panels of different densities, we assume the microscopic behavior to similar and used the expression proposed in (Louerat et al, 2018) to obtain the macroscopic diffusivity f as a function of the solid fraction:…”

Non-Fickian diffusion in biomaterials

“…This was already discussed in [8]. Using a relevant value of f = 0.5, as predicted by homogenisation from the real 3D morphology [15], the model predict a too low dynamic of RH increase at the back face. Finally, the use of a simple function, whose parameters were determined by identification, the dynamic of RH evolution can be captured with the same value of f (0.5).…”

Estimation of Thermal Properties of Straw-Based Insulating Panels

“…The values of the coefficient primary result from thermal conductivity and thickness of the applied insulating material. Credible data on the thermal properties of the materials are required for correct design of barrier envelopes, especially in the case of advanced low-energy and passive buildings [ 17 ].…”