1,721,146 research outputs found
Pattern recognition techniques and time dependent neodeterministic seismic hazard assessment
No full textEGU2007 General Assembly, Vienna, Austria (Aprile 15-20, 2007)
Neo-Deterministic Seismic Hazard and Pattern Recognition Techniques: Time-Dependent Scenarios for North-Eastern Italy
No full textAn integrated neo-deterministic approach to seismic hazard assessment has been developed that combines different pattern recognition techniques, designed for the space–time iden- tification of impending strong earthquakes, with algorithms for the realistic modeling of seismic ground motion. The integrated approach allows for a time-dependent definition of the seismic input, through the routine updating of earthquake predictions. The scenarios of expected ground motion, associated with the alarmed areas, are defined by means of full waveform modeling. A set of neo-deterministic scenarios of ground motion is defined at regional and local scales, thus providing a prioritization tool for timely preparedness and mitigation actions. Constraints about the space and time of occurrence of the impending strong earthquakes are provided by three formally defined and globally tested algorithms, which have been developed according to a pattern recognition scheme. Two algorithms, namely CN and M8, are routinely used for intermediate-term middle-range earthquake predictions, while a third algorithm allows for the identification of the areas prone to large events. These independent procedures have been combined to better constrain the alarmed area. The pattern recognition of earthquake-prone areas does not belong to the family of earthquake prediction algorithms since it does not provide any information about the time of occurrence of the expected earthquakes. Never- theless, it can be considered as the termless zero-approximation, which restrains the alerted areas (e.g. defined by CN or M8) to the more precise potential location of large events. Italy is the only region of moderate seismic activity where the two different pre- diction algorithms, CN and M8S (i.e. a spatially stabilized variant of M8), are applied simultaneously and a real-time test of predic- tions, for earthquakes with magnitude larger than a given threshold (namely 5.4 and 5.6 for CN algorithm, and 5.5 for M8S algorithm) has been ongoing since 2003. The application of the CN to the Adriatic region, which is relevant for seismic hazard assessment in the northeastern part of the Italian territory, is also discussed. Examples of neo-deterministic scenarios are provided, at regional and local scale and for the cities of Trieste and Nimis (Friuli Venezia Giulia region), where the knowledge of the local geological conditions permitted a detailed evaluation of the expected ground motion
Pattern recognition methodologies and deterministic evaluation of seismic hazard: a strategy to increase earthquake preparedness
No full textSeveral algorithms, structured according to a general pattern-recognition scheme, have been developed for the space-time identification of strong events. Currently, two of such algorithms are applied to the Italian territory, one for the recognition of earthquake-prone areas and the other, namely CN algorithm, for earthquake prediction purposes. These procedures can be viewed as independent experts, hence they can be combined to better constrain the alerted seismogenic area.
We examine here the possibility to integrate CN intermediate-term medium-range earthquake predictions, pattern recognition of earthquake-prone areas and deterministic hazard maps, in order to associate CN Times of Increased Probability (TIPs) to a set of appropriate scenarios of ground motion. The advantage of this procedure mainly consists in the time information provided by predictions, useful to increase preparedness of safety measures and to indicate a priority for detailed seismic risk studies to be performed at a local scale
Identification of seismogenic nodes in the Alps and Dinarides
No full textSeismogenic nodes - specific structures formed at the intersections of fault zones - have been identified in the Alps and Dinarides. The nodes have been delineated by the morphostructural zoning (MZ) method and their seismic potential has been evaluated by the pattern-recognition method. With MZ we have compiled a morphostructural map (scale 1:1,000,000) for the study region, using the GIS technology. The map shows the hierarchical block-structure of the region, the network of boundary zones bounding blocks, and the loci of the nodes. A three-level hierarchy has been established for the blocks and their boundaries. The recorded M ≥ 6.0 earthquakes nucleate at the nodes delineated by MZ, i.e. ignoring the seismic record. Among all delineated nodes we recognized the seismogenic ones (D), prone to M ≥ 6.0 earthquakes, with the pattern recognition algorithm CORA-3. The majority of these nodes is associated with the first and second rank boundaries, i.e. larger earthquakes originate at the boundaries of larger blocks. We have identified a number of D nodes, where strong earthquakes have not yet been recorded. In the Alps, these nodes form spatial clusters in the French-Italian Alps, in the Northern Calcareous Alps, in the Dolomites, and in the Karawanken. In the Dinarides, such nodes occur on the Adriatic coast and form two small clusters in the south and in the east of Serbia. The nodes capable of M ≥ 6.5 earthquakes are identified with the criteria of high seismicity nodes, previously derived from pattern recognition in the Pamirs-Tien Shan region. With these criteria we obtained satisfactory classification of the nodes for the Dinarides, while for the Alps the defined number of high seismic potential nodes is open to discussion
Neo-deterministic seismic hazard scenarios for the Adria region and its surroundings
No full textIASPEI General Assembly 2009– (Cape Town, South Africa. 11-16 January 2009)
The contribution of pattern recognition of seismic and morphostructural data to seismic hazard assessment.
No full textExperience from the destructive earthquakes worldwide, which occurred over the last decade, motivated an active debate discussing the practical and theoretical limits of the seismic hazard maps based on a classical probabilistic seismic hazard approach (PSHA). Systematic comparison of the observed ground shaking with the expected one, in fact, shows that such events keep occurring where PSHA predicted seismic hazard to be low. Amongst the most debated issues is the reliable statistical characterization of the spatial and temporal properties of large earthquakes occurrence, due to the unavoidably limited observations from past events. We show that pattern recognition techniques allow addressing these issues in a formal and testable way and thus, when combined with physically sound methods for ground shaking computation, like the neo-deterministic approach (NDSHA), may produce effectively preventive seismic hazard maps. Pattern recognition analysis of morphostructural data provide quantitative and systematic criteria for identifying the areas prone to the largest events, taking into account a wide set of possible geophysical and geological data, whilst the formal identification of precursory seismicity patterns (by means of CN and M8S algorithms), duly validated by prospective testing, provides useful constraints about impending strong earthquakes at the intermediate space-time scale. According to a multi-scale approach, the information about the areas where a strong earthquake is likely to occur can be effectively integrated with different observations (e.g., geodetic and satellite data), including regional scale modelling of the stress field variations and of the seismic ground shaking, so as to identify a set of priority areas for detailed investigations of short-term precursors at local scale and for microzonation studies. Results from the pattern recognition of earthquake prone areas (M>=5.0) in the PO Plain (northern Italy), as well as from prospective testing and validation of the time-dependent NDSHA scenarios are presented, including the case of the May 20, 2012 Emilia earthquake
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Morfostructural zonation and block model dynamics in the Alps and surrounding regions
No full textThe two methodologies applied in this study develop the widely accepted concept that the lithosphere is built-up by different-scale blocks, separated by mobile boundaries. The aim of this work is to provide new insights about active deformations and to improve seismic hazard assessment in the Alps and surrounding areas. The Morphostructural Zonation method, MSZ (Alekseevskaya et al., 1977), allows for the identification of the sites capable of the strong events, while the block model of the lithosphere dynamics (Gabrielov et al., 1990) permits to generate a synthetic catalogue of earthquakes to be used for the analysis of some long-term features of seismic energy release in the modeled region.TRANSALP Conference (2003), Triest
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