An inverse modelling approach to estimate the hygric parameters of clay-based masonry during a Moisture Buffer Value test
| Autor: | Frédéric Lebeau, Andrew Heath, Arnaud Evrard, Samuel Dubois, Fionn McGregor |
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| Rok vydání: | 2014 |
| Předmět: |
moisture buffer value
Engineering Environmental Engineering MCMC Moisture Estimation theory business.industry Multiphysics Geography Planning and Development DREAM Soil science clay Building and Construction Masonry HAM modelling Probability distribution Geotechnical engineering Sensitivity (control systems) Diffusion (business) parameter estimation business Porosity Civil and Structural Engineering |
| Zdroj: | Dubois, S, McGregor, F, Evrard, A, Heath, A & Lebeau, F 2014, ' An inverse modelling approach to estimate the hygric parameters of clay-based masonry during a Moisture Buffer Value test ', Building and Environment, vol. 81, pp. 192-203 . https://doi.org/10.1016/j.buildenv.2014.06.018 |
| ISSN: | 0360-1323 |
| DOI: | 10.1016/j.buildenv.2014.06.018 |
| Popis: | This paper presents an inverse modelling approach for parameter estimation of a model dedicated to the description of moisture mass transfer in porous hygroscopic building materials. The hygric behaviour of unfired clay-based masonry samples is specifically studied here and the Moisture Buffer Value (MBV) protocol is proposed as a data source from which it is possible to estimate several parameters at once. Those include materials properties and experimental parameters. For this purpose, the mass of two clay samples with different compositions is continuously monitored during several consecutive humidity cycles in isothermal conditions. Independently of these dynamic experimental tests, their moisture storage and transport parameters are measured with standard steady-state methods.A simple moisture transfer model developed in COMSOL Multiphysics is used to predict the moisture uptake/release behaviour during the MBV tests. The set of model parameters values that minimizes the difference between simulated and experimental results is then automatically estimated using an inverse modelling algorithm based on Bayesian techniques. For materials properties, the optimized parameters values are compared to values that were experimentally measured in steady state. And because a precise understanding of parameters is needed to assess the confidence in the inverse modelling results, a sensitivity analysis of the model is also provided. |
| Databáze: | OpenAIRE |
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