Long-term continuous dynamic monitoring of an eight-story CLT building

This paper presents the continuous monitoring of an eight-story cross-laminated timber (CLT) building. The monitoring process includes daily acceleration measurements at the rooftop, along with external temperature, humidity, and wind velocity data. Additionally, moisture content (MC) of timber at various locations in the internal and perimeter walls is measured. The extraction of modal parameters is automated and is based on the Stochastic Subspace Identification method. This research primarily evaluates how environmental factors, particularly temperature, wood MC, snow height, and wind velocity, affect the building's modal parameters and vibrational response. The data has been found to significantly correlate with temperature, wood MC, and snow level. Subsequently, the authors performed a Bayesian model updating of the building to estimate the relationship between the shear modulus of CLT and the MC. This analysis has led to an empirical formula for predicting the stiffness properties of CLT walls based on wood MC derived from long-term monitoring of a timber building. To the authors' knowledge, it is the first empirical expression relating a mechanical property of timber and MC, indirectly estimated from ambient vibration data.