PSI - Issue 84

Vincenzo Mario Di Mucci et al. / Procedia Structural Integrity 84 (2026) 521–528

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Table 1. MAFE ( λ ) values for future time (years) scenarios. Time horizon (years from today) MAFE ( λ ) DS1 (Slight) DS2 (Moderate)

DS3 (Extensive)

DS4 (Near Collapse)

0 (Present)

2.32E-03 2.39E-03 2.45E-03 2.46E-03 2.55E-03 2.61E-03 2.61E-03

8.02E-04 8.32E-04 9.01E-04 9.81E-04 1.03E-03 1.09E-03 1.09E-03

5.84E-04 6.22E-04 6.57E-04 6.99E-04 7.68E-04 9.02E-04 9.13E-04

3.24E-04 3.52E-04 3.88E-04 4.33E-04 4.73E-04 5.14E-04 5.53E-04

5

10 15 20 25 30

Fig. 4. MAFE values over future time scenarios.

5. Conclusions This study introduced a framework for time-dependent seismic risk assessment of corroded RC bridge piers, integrating computer vision-based corrosion quantification with probabilistic structural modeling. Fragility functions were computed for four damage states (DS1–DS4), over a 30-year life span. Near-Collapse damage state governs the residual life span, with the critical threshold exceeded around year 23, while DS2 and DS3 remain below target exceedance probabilities. The framework leverages BriCANet to extract corrosion severity from inspection images and map it to probabilistic mass-loss parameters, linking automated visual assessments to structural performance models for rapid, scalable, low-cost estimation of seismic fragility. By integrating state-based corrosion forecasting, it predicts residual life and identifies intervention time windows before reliability falls below regulatory thresholds. Framed within a life-cycle perspective, the approach supports proactive maintenance by combining current condition, predicted deterioration, and intervention timing for optimized long-term bridge management. Acknowledgments This study was supported by FABRE – “Research consortium for the evaluation and monitoring of bridges, viaducts and other structures” (www.consorziofabre.it/en). Any opinion expressed in the paper does not necessarily reflect the view of the funder.