This paper proposes the application of the Covariance Matrix Adaptation (CMA) evolution strategy for the identification of building envelope materials hygrothermal properties. All material properties are estimated on the basis of local temperature and relative humidity measurements, by solving the inverse heat and moisture transfer problem. The applicability of the identification procedure is demonstrated in two stages: first, a numerical benchmark is developed and used as to show the potential identification accuracy, justify the choice for a Tikhonov regularisation term in the fitness evaluation, and propose a method for its appropriate tuning. Then, the procedure is applied on the basis of experimental measurements from an instrumented test cell, and compared to the experimental characterisation of the observed material. Results show that an accurate estimation of all hygrothermal properties of a building material is feasible, if the objective function of the inverse problem is carefully defined.

The present work is the hygric characterization of wood fibre insulation boards, using dynamic measurements of relative humidity and sample weight, analyzed in the frame of Bayesian inference for parameter identification under uncertainty. It is an attempt at identifying detailed profiles of moisture-dependent properties, and thus a relatively high number of parameters. Because of this ambition, some caution should be exercised once the outcome of the inversion algorithm is available: in addition to confidence intervals of parameters provided by the Bayesian framework, a simplified form of identifiability analysis is performed by analysing a posteriori parameter correlations and likelihood-based confidence intervals.The characterization methodology does not require for the model structure to have a differentiable analytical formulation, or for material samples to reach mass equilibrium between each RH step of the experimental process. Two separate experimental designs were used for material characterization and for validation, respectively. Results show a clear relation between available information (experimental data) and inference (confidence intervals of parameters). A single relative humidity step is not informative enough for a precise inference of moisture-dependent properties such as vapour permeability and moisture capacity. A two-step experiment however holds enough information to significantly reduce parameter uncertainty.

International audienceThe present work aims at developing a methodology for the detection and monitoring of damage and fractures in building materials in the prospects of energetic renovation. Digital image correlation (DIC) and acoustic emission (AE) monitoring were simultaneously performed during tensile loading tests of fibre reinforced mortar samples. The full-field displacement mappings obtained by DIC revealed all ranges of cracks, from microscopic to macroscopic, and an image processing procedure was conducted as to quantify their evolution in the course of the degradation of the samples. The comparison of these measurements with the acoustic activity of the material showed a fair match in terms of quantification and localisation of damage. It is shown that after such a calibration procedure, AE monitoring can be autonomously used for the characterisation of damage and fractures at larger scales