Abstract Summary
The Applied Element Method (AEM) has been used extensively through the past decade for doing non-linear analysis of structures subjected to extreme loading conditions like blast, progressive collapse, seismic assessment for new and existing buildings, wind analysis, impact analysis and fire analysis. With the recent advancement in structural health monitoring (SHM) and digital twin (TD) industry, it became essential that SHM and TD need a structural analysis tool that can predict the behavior of different structural components under extreme loads. AEM is a high fidelity numerical dynamic structural analysis method that tracks the structural behavior starting from the elastic stage passing through cracking, crushing, reinforcement yielding, buckling and post buckling up to element separation, debris, and collision. Having an AEM model connected to SHM and TD allows engineers to track in real time the effects of either man-made hazard or natural hazards on the structural behavior. It also allows decision makers to take the appropriate action to repair, strength or demolish the structure before an accident happens that leads to loss of life or assets. In this paper, the authors will present a discussion about the integration of AEM as a tool for digital twinning within an SHM strategy, taking profit of some illustrative numerical case studies. It is concluded that the use of AEM modelling is particularly profitable in association to a static monitoring system in the case of bridges undergoing slow deformation phenomena, for instance resulting from a movement of a foundation due to an active slow landslide, in order to build a digital twin of the deforming bridge useful to predict the remaining useful like of the bridge based on the measurements obtained from either contact or remote sensors. It is also concluded that AEM can be especially useful to setup alert thresholds for static response measurements, such as tilt rotations, and to aid the process of structural strengthening to avoid major accidents.
