Model updating incorporating measured response uncertainties and confidence levels of tuning parameters

Automated model updating of real civil engineering structures is often very challenging due to the presence of different degrees of uncertainty in measured responses and confidence levels of the tuning parameters used. To address this issue, this paper presents a hybrid model updating procedure for large-scale civil engineering structures which incorporate these variations by means of data scatter for both measured responses and tuning parameters as a logical extension to the conventional automated model updating procedures. Scatters in the measured responses are derived through statistically analysing ambient vibration test data, while confidence levels of tuning parameters are derived based on the engineering judgement. The results of applying this hybrid model automated model updating procedure to a ten story building show a significant improvement in obtaining more realistic updated models, against its conventional counterpart that was done previously on the same structure.