GNGTS 2019 - Atti del 38° Convegno Nazionale

360 GNGTS 2019 S essione 2.2 to the target conditional probability of failure p * f = 0.05 notably increases by increasing the capacity dispersion. Finally the trend in time of the capacity required for the target failure probability is discussed and the value of obtained in the range [250 yr , 1400 yr ] are reported in Fig. 3 for 4 values of β. The curves of Fig. 3 show that the required capacity increases as the time elapsed form the last event grows and the rate of this increment decreases with time. The required capacity increases sharply up to approximately 600 yr . Then, it increases slightly up to 1200 yr and finally it remains almost the same for larger values. It is noteworthy that before the critical time t – = 219 yr no structural capacity is required because the occurrence rate is lower than the target failure rate. Furthermore, it can be observed that the larger β is, the greater the slope will be. Fig. 3 - The change of required capacity by elapsing time for constant r = 5 km and variable β . Conclusions. The Impact of Time-Dependent Seismic Hazard on design capacity was assessed in this study by evaluating the strength required by the structure for varying time intervals elapsing from the last event, in order to ensure a target value of the failure rate is not exceeded. Apoint-source is considered and results concerning different and capacity dispersions β are discussed. The case study presented concerns the Paganica fault, located in central Italy. Based on the results, the following conclusions can be drawn. - High variations in hazard rates do not translate into similar variations in the capacity required to ensure the target failure rate, and capacity variations observed in the case study are moderate. - For the case considered (point-source, BPT model, T R = 750 yr ) required capacity drops to 0 at a critical instant, t = 219 yr and variations in time become negligible for t > 600 yr . - The response parameter β notably influences the required capacity and different trends are observed in time. Acknowledgments. This study was partially supported by INGV (National Institute of Geophysics and Volcanology). References Anagnos, T., Kiremidjian, A.S., 1988, “A Review of Earthquake Occurrence Models for Seismic Hazard Analysis”, Probabilistic Engineering Mech. , 3 (1), 3–11. Cornell CA, Jalayer F, Hamburger RO, Foutch DA (2002) Probabilistic basis for 2000 SAC Federal Emergency Management Agency steel moment frame guidelines. J Struct Eng 128 (4):526–533 Matthews, M V., Ellsworth, W. L., Reasenberg, P. A. (2002), A brownian model for recurrent earthquakes, Bulletin of the Seismological Society of America , 92 (6), 2233–2250. Pace, B., Peruzza, L., Lavecchia and G., Boncio P., 2006, Layered seismogenic source model and probabilistic seismic-hazard analyses in central Italy, Bulletin of the Seismological Society of America , 96 (1), 107-132.