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  • 04.06. Seismology  (4)
  • Springer  (4)
  • American Institute of Physics (AIP)
  • 2020-2024  (4)
  • 2015-2019
  • 1950-1954
  • 1945-1949
  • 2023  (4)
  • 1
    Publication Date: 2023-02-21
    Description: We develop a new inversion approach to construct a 3-D structural and shear-wave velocity model of the crust based on teleseismic P-to-S converted waves. The proposed approach does not require local earthquakes such as body wave tomography, nor a large aperture seismic network such as ambient noise tomography, but a three-component station network with spacing similar to the expected crustal thickness. The main features of the new method are: (1) a novel model parametrization with 3-D mesh nodes that are fixed in the horizontal directions but can flexibly vary vertically; (2) the implementation of both sharp velocity changes across discontinuities and smooth gradients; (3) an accurate ray propagator that respects Snell’s law in 3-D at any interface geometry. Model parameters are inverted using a stochastic method composed of simulated annealing followed by a pattern search algorithm. The first application is carried out over the Central Alps, where long-standing permanent and the temporary AlpArray Seismic Network stations provide an ideal coverage. For this study we invert 4 independent parameters, which are the Moho discontinuity depth, the Conrad discontinuity depth, the P-velocity change at the Conrad and the average Vp/Vs of the crust. The 3-D inversion results clearly image the roots of the Alpine orogen, including the Ivrea Geophysical Body. The lower crust's thickness appears fairly constant. Average crustal Vp/Vs ratios are relatively higher beneath the orogen, and a low-Vp/Vs area in the northern foreland seems to correlate with lower crustal earthquakes, which can be related to mechanical differences in rock properties, probably inherited. Our results are in agreement with those found by 3-D ambient noise tomography, though our method inherently performs better at localizing discontinuities. Future developments of this technique can incorporate joint inversions, as well as more efficient parameter space exploration.
    Description: Published
    Description: 529 - 562
    Description: 1T. Struttura della Terra
    Description: JCR Journal
    Keywords: Computational seismology ; Receiver functions  ; Inverse theory ; Crustal imaging ; Central Alps ; 05.01. Computational geophysics ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2023-08-29
    Description: Machine learning, with its advances in deep learning has shown great potential in analyzing time series. In many scenarios, however, additional information that can potentially improve the predictions is available. This is crucial for data that arise from e. g., sensor networks that contain information about sensor locations. Then, such spatial information can be exploited by modeling it via graph structures, along with the sequential (time series) information. Recent advances in adapting deep learning to graphs have shown potential in various tasks. However, these methods have not been adapted for time series tasks to a great extent. Most attempts have essentially consolidated around time series forecasting with small sequence lengths. Generally, these architectures are not well suited for regression or classification tasks where the value to be predicted is not strictly depending on the most recent values, but rather on the whole length of the time series. We propose TISER-GCN, a novel graph neural network architecture for processing, in particular, these long time series in a multivariate regression task. Our proposed model is tested on two seismic datasets containing earthquake waveforms, where the goal is to predict maximum intensity measurements of ground shaking at each seismic station. Our findings demonstrate promising results of our approach—with an average MSE reduction of 16.3%—compared to the best performing baselines. In addition, our approach matches the baseline scores by needing only half the input size. The results are discussed in depth with an additional ablation study.
    Description: Interreg North-West Europe program (Interreg NWE), project Di-Plast - Digital Circular Economy for the Plastics Industry (NWE729). INGV Pianeta Dinamico 2021 Tema 8 SOME (CUP D53J1900017001) funded by Italian Ministry of University and Research “Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese, legge 145/2018.
    Description: Published
    Description: 317–332
    Description: 8T. Sismologia in tempo reale e Early Warning Sismico e da Tsunami
    Description: JCR Journal
    Keywords: Graph neural networks ; Time series ; Sensors ; Convolutional neural networks ; Regression ; Earthquake ground motion ; Seismic network ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 3
    Publication Date: 2023-10-03
    Description: Lifelines, such as pipelines, roads, and tunnels, are critical infrastructure and when crossing active tectonic faults, a reliable estimation of the fault displacement in case of an earthquake is required. The first and simplest approach is to use empirical fault scaling relations to compute the design fault displacement, but this may result in an unknown level of safety. Thus, the probabilistic fault displacement hazard analysis (PFDHA) is the appropriate tool to assess the fault displacement hazard within a performance-based framework. Based upon an established PFDHA model, we present a simplified approach for engineering applications focusing on the lifeline–fault crossing along with appropriate simplifications and assumptions to extend its applicability to numerous faults. The aim is to provide a structure-independent approach of PFDHA that can be used when a site-specific study is not required, not possible (e.g., absence of recent sediments for dating past events), or too cumbersome, e.g., for lifeline route selection. Additionally, an in-depth investigation is presented on the key parameters, such as maximum earthquake magnitude, fault length, recurrence rate of all earthquakes above a minimum magnitude, and lifeline-fault crossing site, and how they affect the hazard level. This approach will be the basis for deriving hazard-consistent expressions to approximate fault displacement for use within the Eurocodes. The latter is intended to serve as a compromise between hazard-agnostic fault scaling relations and a comprehensive PFDHA, which requires detailed calculations and site-specific seismological data.
    Description: Open access funding provided by HEAL-Link Greece. The current work has been undertaken as part of the Horizon 2020 Seismology and Earthquake Engineering Research Infrastructure Alliance in Europe (SERA, Grant Agreement No. 730900). The first and the third author have received partial funding from the European Union’s Horizon 2020 research and innovation programme “METIS-Seismic Risk Assessment for Nuclear Safety” under Grant Agreement No. 945121. Also, the financial support provided by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Faculty Members & Researchers”, Project "TwinCity—Climate-Aware Risk and Resilience Assessment of Urban Areas under Multiple Environmental Stressors via Multi-Tiered Digital City Twinning ", (Number: 2515) is gratefully acknowledged.
    Description: Published
    Description: 4821–4849
    Description: 2T. Deformazione crostale attiva
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Description: 6T. Studi di pericolosità sismica e da maremoto
    Description: JCR Journal
    Keywords: PFDHA ; 04.06. Seismology ; 04.04. Geology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 4
    Publication Date: 2023-10-11
    Description: Set of data and metadata that characterize a site hosting a seismic station
    Description: In this paper we describe an advanced database for the site characterization of seismic stations, named “CRISP—Caratterizzazione della RIsposta sismica dei Siti Permanenti della rete sismica” (http:// crisp. ingv. it, quoted with https:// doi. org/ 10. 13127/ crisp), designed for the Italian National Seismic Network (Rete Sismica Nazionale, RSN, operated by Istituto Nazionale di Geofisica e Vulcanologia). For each site, CRISP collects easily accessible station information, such as position, type(s) of instrumentation, instrument housing, thematic map(s) and descriptive attributes (e.g., geological characteristics, etc.), seismic analysis of recordings, and available geophysical investigations (shear-wave velocity [VS] profile, non-linear decay curve). The archive also provides key proxy indicators derived from the available data, such as the time-averaged shear-wave velocity of the upper 30 m from the surface ( VS30) and site and topographic classes according to the different seismic codes. Standardized procedures have been applied as motivated by the need for a homogenous set of information for all the stations. According to European Plate Observing System infrastructural objectives for the standardization of seismological data, CRISP is integrated into pre-existing INGV instrument infrastructures, shares content with the Italian Accelerometric Archive, and complies map information about the stations, as well as local geology, through web services managed by Istituto Superiore per la Protezione e la Ricerca Ambientale. The design of the CRISP archive allows the database to be continually updated and expanded whenever new data are available from the scientific community, such as the ones related to new seismic stations, map information, geophysical surveys, and seismological analyses.
    Description: Published
    Description: 2415 - 2439
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Description: JCR Journal
    Keywords: Site effects ; Site characterization ; Permanent seismic station ; Italian National Seismic Network ; Database ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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