Experimental verification for a mechanics-based digital cloning method predicting structural performance and damage

This paper introduces a novel digital twin modelling framework combining accurate structural health monitoring (SHM) results delivered by hysteresis loop analysis (HLA) with the basis function modelling to predict structural damage and responses of earthquake-affected structures under future seismic events. The measured data sets of a 12-storey 1/10 scale reinforced concrete (RC) structure shaken by three damaging base excitations (Events 1, 2 and 3) using a shake table has been employed to validate the performance of the introduced predictive framework. The results show that the digital twin created under the first base excitation (Event 1) predicts the inter-storey displacement responses of the test structure due to the second and third excitations (Events 2 and 3) with an average correlation coefficient of similar to 0.88 and similar to 0.94, respectively. The inter-storey drift ratio (IDR) values predicted by the digital twin also result in the same seismic performance delivered by the measured values, making the introduced framework a promising tool for assessing structural collapse and subsequent financial risk using incremental dynamic analysis (IDA). Moreover, the maximum difference of 5% between the identified and predicted stiffness values illustrates the robust and accurate performance of the proposed framework in diagnosing structural damage in highly nonlinear and damaged structures.