Real-time monitoring of evolutive structural damage from advanced sensing and simulation

The integration of advanced sensing technologies and numerical simulations presents a viable pathway for the real-time structural health monitoring (SHM) of critical engineering assets. This research direction explores the methodology for tracking and predicting the progression of evolutive structural damage under dynamic operational loads. By leveraging high-fidelity in situ measurements, such as those obtained from distributed optical fiber sensors, alongside predictive computational models, the framework aims to establish a continuous feedback loop between physical structures and their digital representations. The methodology addresses the challenges of processing high-dimensional experimental strain and displacement fields to identify localized material degradation. Furthermore, it incorporates simulation-based prognostic models to forecast remaining useful life and facilitate

adaptive operational planning under degraded structural states. The research provides structuring and guidance for implementing real-time data-assimilation algorithms that bridge the gap between physical measurements and numerical damage mechanics. Ultimately, this approach supports the development of autonomous, self-monitoring mechanical systems capable of optimizing maintenance schedules and preventing catastrophic failures in sectors such as aerospace, wind energy, and civil infrastructure.

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