Abstract
The present paper investigates the performance of gradient-free inversion methods applied to the characterisation of hygrothermal properties of building materials. Two classes of techniques were implemented to solve the inverse problem of envelope parameter identification: the Covariance Matrix Adaptation evolution strategy, and Bayesian inference. The comparison was made on the basis of a numerical benchmark, which showed that such advanced characterisation techniques can learn from incomplete or noisy data and provide reliable material characteristics, given sufficient sensor measurements. A possible application is the improvement of traditional experimental techniques for hygrothermal characterisation in labs.
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