Assigning actual measured elastic modulus to each lamella in FEA models better predicts dynamic response of hybrid CLT panels than using mean values or random moduli.
This study evaluates different statistical approaches for modeling the elastic moduli of heterogeneous cross-laminated timber panels by comparing finite element analysis results with experimental modal tests.
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Cross-laminated timber (CLT) has become one of the most popular mass timber products. Its overall behaviour is strongly influenced by the CLT layup and the properties of the layers. Existing calculation approaches reflect this through simple calculations using mean stiffness values. This study evaluates the validity of these simplifications for CLT panels made with a heterogeneous layup including partially reclaimed timber. Five-layer CLT panels were produced from Dutch-grown Ash and Douglas in the longitudinal, and reclaimed Spruce in the cross layers. Ultrasonic non-destructive testing was performed on each individual lamellae before panel assembly, yielding a detailed dataset of the longitudinal elastic moduli. Laminate locations within the CLT were recorded during assembly. Parametric finite element analysis (FEA) models were generated using Python scripting in DIANA FEA, and modal analyses were carried out. Three statistical and probabilistic approaches were investigated for assigning the elastic moduli to lamellae to the respective layers within the model: (i) assigning the actual measured modulus to each lamella, (ii) assigning a random modulus from the dataset to each lamella, (iii) using the global mean value per layer. The results from the FEA analyses were compared with results from experimental modal tests. The impact of each modulus assignment strategy on the dynamic response of the panels was evaluated by comparing natural frequencies, mode shapes, statistical indicators, and relative errors.
Borghese et al. (Thu,) reported a other. Assigning actual measured elastic modulus to each lamella in FEA models better predicts dynamic response of hybrid CLT panels than using mean values or random moduli.