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Dynamic water vapor sorption in wood-based fibrous materials and material parameter estimation

Autor(en): ORCID

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Journal of Building Physics, , n. 4, v. 46
Seite(n): 399-424
DOI: 10.1177/17442591221142496
Abstrakt:

Building physical simulation software rely on assumptions regarding the local equilibria in materials’ pore systems, which may be unjustified for certain materials. While local hygrothermal non-equilibrium has still been in focus in some previous studies, it has been unclear how significant factor it may be when modeling real structures. In case of wood, the non-equilibrium is related to the slowness of intrusion of water molecules into the hygroscopic cell walls. Including local non-equilibrium in macroscopic model requires separate variables for pore air vapor and adsorbed moisture, and modeling the local mass transfer between pore air and adsorbed moisture requires effective material parameters, whose experimental determination is not straightforward. Commercially available sorption balances can be used to record data, which can be used in the parameter estimation. In this type of problem of parameter estimation from time-dependent data the mathematical challenge is to find global optimum from different solutions, which yield similar values for objective function. This difficulty can be overcome by using statistical inversion approach, which we applied in studying low-density woodfibre material (LDF). Dynamic sorption parameters were finally applied in numerical analysis of a laboratory test assembly. Based on the results, our conclusion is that the slowness of sorption is obvious in small LDF sample, which is exposed to changing humidity, but with the studied material the sorption seem to happen fast enough so that local non-equilibrium may have only slight effects in modeling of real structures.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1177/17442591221142496.
  • Über diese
    Datenseite
  • Reference-ID
    10714240
  • Veröffentlicht am:
    21.03.2023
  • Geändert am:
    21.03.2023
 
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