Analysis and improvement of the VTT mold growth model: application to bamboo fiberboard

Abstract : The reliability of a model is its accuracy in predicting the physical phenomena using the known input parameters. It also depends on the model's ability to estimate relevant parameters using observations of the physical phenomena. In this paper, the reliability of the VTT model is investigated under these two criteria for various given temperature and relative humidity constant in time. First of all, experiments are conducted on bamboo fiberboard. Using these data, five parameters of the VTT model, defining the mold vulnerability class of a material, are identified. The results highlight that the determined parameters are not within the range of the classes defined in the VTT model. In addition, the quality of the parameter estimation is not satisfactory. Then the sensitivity of the numerical results of the VTT model is analyzed by varying an input parameter. These investigations show that the VTT mathematical formulation of the physical model of mold growth is not reliable. An improved model is proposed with a new mathematical formulation. It is inspired by the logistic equation whose parameters are estimated using the experimental data obtained. The parameter estimation is very satisfactory. In the last parts of the paper, the numerical predictions of the improved model are compared to experimental data from the literature to prove its reliability.
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Soumis le : dimanche 8 avril 2018 - 19:12:40
Dernière modification le : jeudi 28 juin 2018 - 12:38:02

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Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale - Partage selon les Conditions Initiales 4.0 International License

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  • HAL Id : hal-01759837, version 2
  • ARXIV : 1804.02992

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Julien Berger, Hervé Le Meur, Denys Dutykh, Dang Mao Nguyen, A.-C. Grillet. Analysis and improvement of the VTT mold growth model: application to bamboo fiberboard. 33 pages, 10 figures, 9 tables, 29 references. Other author's papers can be downloaded at http://.. 2018. 〈hal-01759837v2〉

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