Identification of wood material parameters under drying conditions based on multi-objective optimisation

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Abstract

Timber drying is the first step in wood processing industries, in which excessive moisture is removed up to an acceptable level required when manufacturing wooden components or structures. Numerical simulation of such processes makes possible to define proper drying schedules and product finish able to reduce potential defects. This work addresses identification of moisture diffusion and shrinking/swelling parameters associated with a fully coupled hygro-thermo-mechanical model. The strategy to determine the wood drying parameters uses inverse problem techniques based on multi-objective optimisation in order to account for multiple data sets containing time evolution of the sample mass and size (reference data). The solution is achieved using a hybrid global–local optimisation method to circumvent existence of local minima. The results indicate that the wood drying parameters determined using a single data set present a poor approximation of the reference data. The proposed strategy shows that identification using drying wood samples of multiple sizes (multiple data sets) provides more representative material parameters that yield good approximation between reference and numerical data.

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