PSI - Issue 78

1790 Marco Civera et al. / Procedia Structural Integrity 78 (2026) 1783–1790 In brief, the uncorrected RN efficiency index monotonically increases as = 0.43, 0.44, 0.55, and 0.60 for DS1, DS2, DS3, and DS4, in the same order. With respect to , =0.64 , these correspond to a reduction equal to -33%, -31%, -14%, and -7%. Instead, the corrected RN efficiency index monotonically decreases ( , = 0.429, 0.095, 0.027, and 0.005 ). 5. Conclusions The results of this study should be seen as complementary to what was described in the Authors’ previous publication on the same case study (Miano et al., 2024). In that first research work, the focus was on ensuring the road network (RN) operability in the immediate aftermath of the earthquake, i.e. in the very short term. That is to say, that first work reflected a ‘transportation engineering’ perspective on traffic resilience. Under that assumption, only the most relevant DS was considered for each of the two seismic scenarios. That led to the potentially counterintuitive outcome of a larger drop in efficiency after a moderate seismic event rather than a larger one. That outcome was due to the binary classification (road disruption yes/no) followed in the procedure. In this work, instead, the focus is not on the very short term but the short and medium term (days/weeks), considering that lower DS can be more easily and rapidly recovered. This standpoint is intended to link traffic resilience with the conventional definition of structural resilience, i.e., time to recover and restore post-event..Based on all these considerations, the results highlight how the proposed weights can be applied to consider different time horizons after the first earthquake strike on the infrastructures of the RN and the surrounding buildings. It is thus suggested to use the uncorrected resilience index of the previous work when comparing DSs of the same level, while the proposed correction should be applied when considering different DSs, to compensate for the difference in expected reopening time. Acknowledgements The project ReLUIS CSLLPP- - WP2 - Osservazioni sulle schede di Livello 1 secondo LLGG is acknowledged for providing support to this research work. The authors also acknowledge the project PE3 RETURN, Spoke: TS2 - MULTI-RISK RESILIENCE OF CRITICAL INFRASTRUCTURES. MUR project code: PE00000005 and the project CN-MOST within the European Union Next-Generation EU (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1033 17/06/2022, CN00000023). References Argyroudis, Sotirios A., Stergios A. Mitoulis, Lorenzo Hofer, Mariano Angelo Zanini, Enrico Tubaldi, and Dan M. Frangopol. 2020. “Resilience Assessment Framework for Critical Infrastructure in a Multi-Hazard Environment: Case Study on Transport Assets.” Science of the Total Environment 714. doi:10.1016/J.SCITOTENV.2020.136854,. Consiglio Superiore dei Lavori Pubblici. 2020. Linee Guida per La Classificazione e Gestione Del Rischio, La Valutazione Della Sicurezza Ed Il Monitoraggio Dei Ponti Esistenti . Grünthal, G., and J. Schwarz. 1998. “European Macroseismic Scale 1998 EMS-98 Editor.” Miano, Andrea, Marco Civera, Fabrizio Aloschi, Valerio De Biagi, Bernardino Chiaia, Fulvio Parisi, and Andrea Prota. 2024. “Efficiency Assessment of Urban Road Networks Connecting Critical Node Pairs under Seismic Hazard.” Sustainability 2024, Vol. 16, Page 7465 16(17):7465. doi:10.3390/SU16177465. Moschonas, Ioannis F., Andreas J. Kappos, Panagiotis Panetsos, Vissarion Papadopoulos, Triantafyllos Makarios, and Pavlos Thanopoulos. 2009. “Seismic Fragility Curves for Greek Bridges: Methodology and Case Studies.” Bulletin of Earthquake Engineering 7(2):439–68. doi:10.1007/S10518-008-9077-2. Opabola, Eyitayo A., and Carmine Galasso. 2024. “A Probabilistic Framework for Post-Disaster Recovery Modeling of Buildings and Electric Power Networks in Developing Countries.” Reliability Engineering & System Safety 242:109679. doi:10.1016/j.ress.2023.109679. Rosti, A., C. Del Gaudio, M. Rota, P. Ricci, M. Di Ludovico, A. Penna, and G. M. Verderame. 2021. “Empirical Fragility Curves for Italian Residential RC Buildings.” Bulletin of Earthquake Engineering 19(8):3165–83. doi:10.1007/S10518-020-00971-4. Sun, Li, Dina D’Ayala, Rosemary Fayjaloun, and Pierre Gehl. 2021. “Agent-Based Model on Resilience-Oriented Rapid Responses of Road Networks under Seismic Hazard.” Reliability Engineering & System Safety 216:108030. doi:10.1016/j.ress.2021.108030.