GNGTS 2013 - Atti del 32° Convegno Nazionale

Das R., Wason H. R. and Sharma M. L.; 2011: Global regression relations for conversion of surface wave and body wave magnitudes to moment magnitude, Nat Hazards, 59 , 801–810 Del Pezzo E. and Petrosino S.; 2001: A local-magnitude scale for Mt. Vesuvius from synthetic Wood-Anderson seismograms, J. Seismol., 5 , 207-215. Ferrucci F. and Patanè D.; 1993: Seismic activity accompanying the outbreak of the 1991-1993 eruption of Mt. Etna (Italy), Jour. Volc. Geoth. Res., 57 , 125-135 Gasperini P. and Ferrari G.; 2000: Deriving numerical estimates from descriptive information: The computation of earthquake parameters , Ann. Geophys., 43 , 4, 729-746. Gasperini P.; 2002: Local magnitude revaluation for recent Italian earthquakes (1981–1996), J. Seism. 6, 503–524. GiampiccoloE., D’AmicoS., PatanèD. andGrestaS.;2007: Attenuationand sourceparameters ofshallowmicroearthquakes at Mt. Etna volcano (Italy) , Bull. Seism. Soc. Am., 97, 1b, 184-197. Grünthal, G., 1998: European Macroseismic Scale 1998 (EMS-98) European Seismological Commission, subcommission on Engineering Seismology, working Group Macroseismic Scales. Conseil de l’Europe, Cahiers du Centre Européen de Géodynamique et de Séismologie, 15, Luxembourg, p. 99. http://www.ecgs.lu/cahiers-bleus/. Gruppo analisi dati sismici, 2013: Catalogo dei terremoti della Sicilia Orientale – Calabria Meridionale,(1999-2013) INGV,Catania, http://www.ct.ingv.it/ufs/analisti/catalogolist.php Lahr J. C.; 1999: Hypoellipse: a computer program for determining local earthquake hypocentral parameters, magnitude, and first motion pattern (Y2K compliant), U.S. Geol. Surv. Open File Rep. 99-23. Murru M., Console R., Falcone G., Montuori C. and Sgroi T.; 2007: Spatial mapping of the b value at Mount Etna, Italy, using earthquake data recorded from 1999 to 2005, J. Geophys. Res., 112 , B12303, DOI:10.1029/2006JB004791. Patanè D. and Giampiccolo E.; 2004: Faulting processes and earthquake source parameters at Mount Etna: state of art and perspective, in Mt. Etna: Volcano Laboratory, edited by Bonaccorso A., Calvari S., Coltelli M., Del Negro C. and Falsaperla S., Am. Geophys. Un., 143 , 167-189. Real C. R. and Teng T.; 1973: Local Richter magnitude and total signal duration in Southern California , Bull. Seism. Soc. Am. 63 , 5, 1809 – 1827. Richter C. F.; 1935: An instrumental earthquake magnitude scale, Bull. Seismol. Soc. Am. 25 , 1–31. SYNTHESIS 0.1: BETA RELEASE OF A SYNTHETIC WAVEFORMS REPOSITORY M. D’Amico 1 , F. Pacor 1 , R. Puglia 1 , L. Luzi 1 , G. Ameri 2 , F. Gallovi 3 , A. Spinelli 4 , M. Rota Stabelli 4 1 Istituto Nazionale di Geofisica e Vulcanologia, Milan, Italy 2 FUGRO-Geoter, Auriol, France 3 Faculty of Mathematics and Physics, Department of Geophysics, Charles University, Prague, Czech Republic 4 Team Quality s.r.l., Bergamo, Italy Introduction. Earthquake engineering analysis requires, as seismic input, a reliable and complete characterization of ground motion both in time and frequency domains. For time-series analysis, engineers often use a suite of observed accelerograms from past earthquakes, selected from worldwide databanks on the base of specific criteria, suitable for their particular purpose, such as strong-motion parameter, magnitude, distance, site class, tectonic environment, spectral matching, etc.. One reason of promoting the use of synthetic seismograms is the paucity of recorded strong motion data in near-source range for moderate to strong events that are of great concerns for seismic hazard evaluation, risk assessment and seismic microzonation. Synthetic waveforms, generated by broadband simulation procedures, have the potential to represent a valid alternative to observed motions. Several simulation techniques have been recently proposed to this aim (Graves and Pitarka, 2004; Pacor et al. , 2005; Liu et al. , 2006; Gallovič and Brokešová, 2007; Ameri et al. , 2008; among many others). They vary in methodological approach and complexity, but all of them model source processes, path effects, and local site response. The numerical models require the definition of a quite large number of input parameters whose values rarely can be fixed “a priori”. While reasonable hypothesis can be done on the causative fault and properties of the propagation medium, kinematic parameters describing the rupture can hardly be set. To handle this lack of knowledge, a strategy is to generate, for each fault, a large number of shaking scenarios (all equally probable), assuming the input values in a plausible range. Each scenario corresponds to a specific combination of input parameters used to simulate the ground 38 GNGTS 2013 S essione 2.1

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