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Motivated by the crucial implications of Ground Motion Models in terms of seismic hazard analysis and civil protection planning, this work extends a scalar Ground Motion Model for Italy to the framework of Functional Data Analysis. The inherent characteristic of seismic data to be incomplete over the observation domain of oscillation periods entails embedding the analysis in the context of partially observed functional data and performing data reconstruction. This work proposes a novel methodology that accounts for the fact that parts of the curves are directly observed and other parts are reconstructed, thus, characterized by greater uncertainty. The method defines observation-specific functional weights, which enter the estimation process to reduce the impact that the less reliable portions of the curves have on the final estimates. The classical methods of smoothing and concurrent functional regression are extended to include weights. The advantages of the proposed methodology are assessed on synthetic data. Eventually, the weighted functional analysis performed on seismological data is shown to provide a natural smoothing and stabilization of the spectral estimates of the Ground Motion Model considered. for this article are available online. [ABSTRACT FROM AUTHOR]

We propose a new fully nonergodic ground motion model for Central Italy, which is one of the most sampled areas in the world after the occurrence of the last seismic sequences of 2009 and 2016–2017. The model predicts 69 ordinates of the Fourier Amplitude Spectrum in the magnitude range 3.2–6.5 and is constrained on a dense set of seismological and geophysical parameters (i.e. stress-drop Δ σ , shear-wave velocity in the uppermost 30 m, VS,30 and high-frequency attenuation parameter at source κ source and site κ 0 ) made available from a non-parametric generalized inversion technique (GIT). The aim of this work is to capture the underlying physics of ground motion related to different source energy levels, as well as to the crustal and geological structure of the region, thus providing less uncertain predictions. Calibration is performed using a stepwise regression approach which has the advantage of taking a more complex functional form (advanced model) when all physical parameters are known while returning a simpler form (base model) when physical data are missing. As a result, the advanced model reproduces the reference rock motion of the region in case the site additional proxies are set to their average values (VS,30 = 1100 m/s, κ 0 =15 ms). We show that the inclusion of the set of physically-based explanatory variables in the regression has a beneficial effect in constraining the uncertainty, leading to a reduction of the high-frequency variability of about 70% on the between-event and 35% on the site-to-site. This reduction can be viewed as the result of the combination of a more effective physical description through the incorporation of the additional proxies and a calibration embedded in a completely nonergodic framework. [ABSTRACT FROM AUTHOR]

This study develops a new spatial correlation model for Italy using the most up-to-date and densest dataset of accelerometer and velocimeter records available. The objective is to estimate the average correlation length and assess its impact on the prediction accuracy of the Italian Shakemap compared to the global model (Loth and Baker, 2013–LB13) adopted in the default configuration of the program. We compute the spatial covariance structure using a geostatistical approach based on traditional variography applied to standardized residuals within the events of a reference ground motion model (ITA10). We observe spatial clusters of the correlation lengths and a wide variability over the Italian territory linked to the profound heterogeneity of the geological and geomorphological context. The obtained estimates are then implemented within the LB13 co-regionalization model in place of the default values while assuming the same cross-correlation coefficients among spectral parameters. Although our results are quite consistent with previous models calibrated for Italy, we find that the inclusion of the new correlation lengths in the Shakemap predictions, assessed through a leave-one-out cross-validation technique, results in a non-appreciable improvement over the global model, thus indicating that the adopted approach is not able to resolve the regional features and the corresponding spatial correlation with reference to individual scenarios. These findings may suggest the need to move towards nonergodic models in the Shakemap computing to better capture the spatial variability or to determine different co-regionalisation matrices more suitable for the regional applications. [ABSTRACT FROM AUTHOR]

Rupture directivity and its potential frequency dependence is an open issue within the seismological community, especially for small‐to‐moderate events. Here, we provide a statistical overview based on empirical evidence of seismological observations, thanks to the large amount of high‐quality seismic recordings (more than 30,000 waveforms) from Central Italy, which represents an excellent and almost unique natural laboratory of normal faulting earthquakes in the magnitude range between 3.4 and 6.5 within the time frame 2008–2018. In order to detect an anisotropic distribution of ground motion amplitudes due to the rupture directivity, we fit the smoothed Fourier Amplitude Spectra (FAS) cleared of source‐, site‐ and path‐effects. According to our criteria, about 36% of the analyzed events (162 out of 456) are directive and the distribution of rupture direction is aligned with the strikes of the major faults of the Central Apennines. We find that the directivity is a band‐limited phenomenon whose width may extend up to five times the corner frequency. The results of this research provide useful insights to parameterize directivity, to be explicitly implemented in future ground motion modeling and scenario predictions. Plain Language Summary: In seismology, directivity is one of the source phenomena that causes large spatial variability of earthquake ground motions and is related to the features of the rupture propagation along the fault. The importance of this effect is very well known for large‐magnitude events (M > 6), while it is still an open issue for small‐to‐moderate events. The aim of this paper is to recognize directive events and quantify their strength in Central Italy, using a large data set of earthquakes in the magnitude range 3.4–6.5 that occurred between 2008 and 2018. We find that about 36% of the analyzed events are directive, caused by rupture propagations oriented along the NW‐SE alignment of the Central Apennines fault systems. Furthermore, we find that directivity is a band‐limited phenomenon and that as the directivity gets stronger, the frequency band becomes wider. Our contribution provides a useful insight with the possibility to improve the parametrization of directivity within the empirical seismic hazard assessment. Key Points: Statistical procedure to detect directivity effects in small‐to‐moderate earthquakes analyzing the aleatory residuals of the ground motionThe directive events are the 36% of the data set and the distribution of rupture direction is aligned with the strikes of the faults systemThe observed directivity is a frequency‐dependent band‐limited phenomenon, which can occur up to five times the value of corner frequency [ABSTRACT FROM AUTHOR]

This paper provides a new methodological framework to generate empirical ground shaking scenarios, designed for engineering applications and civil protection planning. The methodology is useful both to reconstruct the ground motion pattern of past events and to generate future shaking scenarios, in regions where strong‐motion datasets from multiple events and multiple stations are available. The proposed methodology combines (1) an ad‐hoc nonergodic ground motion model (GMM) with (2) a spatial correlation model for the source region‐, site‐, and path‐systematic residual terms, and (3) a model of the remaining aleatory error to take into account for directivity effects. The associated variability is a function of the type of scenario generated (bedrock or site, past or future event) and it is minimal for source areas where several events have occurred and for sites where recordings are available. In order to develop the region‐specific fully nonergodic GMM and to compute robust estimation of the residual terms, the approach is calibrated on a highly dense dataset compiled for the area of central Italy. Example tests demonstrate the validity of the approach, which allows to simulate acceleration response spectra at unsampled sites, as well as to capture peculiar physical features of ground motion patterns in the region. The proposed approach could be usefully adopted for data‐driven simulations of ground shaking maps, as alternative or complementary tool to physic‐based and stochastic‐based approaches. [ABSTRACT FROM AUTHOR]

This work offers a novel methodological framework to address the problem of generating data-driven earthquake shaking fields at different vibration periods, which are key to support decision making and civil protection planning. We propose to analyse the entire profiles of spectral accelerations and project their information content to unsampled locations in the system, based on the theory of Object Oriented Spatial Statistics. The proposed methodology combines a non-ergodic ground motion model with a fully functional model for the residual term, the latter consisting of (i) the spatially-varying systematic effects due to source, site and path, and (ii) the remaining aleatory error. The proposed methodology allows to generate multiple shaking scenarios conditioned on the data, jointly and consistently for all the vibration periods, overcoming the intrinsic limitations of existing multivariate approaches to the problem. The approach is tested on a vast dataset of ground motion records collected in the study-area of the Po Plain (Northern Italy), for which a region-specific fully non-ergodic GMM was previously calibrated. Our validation tests demonstrate the potentiality of the approach, which is capable to effectively simulate spectral acceleration profiles, while keeping the ability to capture the main physical features of ground motion patterns in the region. [ABSTRACT FROM AUTHOR]

The Engineering Strong-Motion (ESM) flatfile is a parametric table which contains verified and reliable metadata and intensity measures of manually processed waveforms included in the ESM database. The flatfile has been developed within the Seismology Thematic Core Service of EPOS-IP (European Plate Observing System Implementation Phase) and it is disseminated throughout a web portal (http://esm.mi.ingv.it/flatfile-2018/flatfile.php) for research and technical purposes. The adopted criteria for flatfile compilation aim to collect strong motion data and related metadata in a uniform, updated, traceable and quality-checked way to develop Ground Motion Models (GMMs) for Probabilistic Seismic Hazard Assessment (PSHA) and engineering applications. In this paper, we present the characteristics of ESM flatfile in terms of recording, event and station distributions, and we discuss the most relevant features of the Intensity Measures (IMs) of engineering interest included in the table. The dataset for flatfile compilation includes 23,014 recordings from 2179 earthquakes and 2080 stations from Europe and Middle-East. The events are characterized by magnitudes in the range 3.5-8.0 and refer to different tectonics regimes, such as shallow active crustal and subduction zones. Intensity measures include peak and integral parameters and duration of each waveform. The spectral amplitudes of the (5% damping) acceleration and displacement response are provided for 36 periods, in the interval 0.01-10 s, as well as the 103 amplitudes of the Fourier spectrum for the frequency range 0.04-50 Hz. Several statistics are shown with reference to the most significant metadata for GMMs calibrations, such as moment magnitude, focal depth, several distance metrics, style of faulting and parameters for site characterization. Furthermore, we also compare and explain the most relevant differences between the metadata of ESM flatfile with those provided by the previous flatfile derived in RESORCE (Reference Database for Seismic Ground Motion in Europe) project. [ABSTRACT FROM AUTHOR]

Tuned mass dampers (TMD) are well known as one of the most widely adopted devices in vibration control passive strategies. In the past few decades, many methods have been developed to find the optimal parameters of a TMD installed on a structure and subjected to a random base excitation process, but most of them are usually based on an implicit assumption that all of the structural parameters are deterministic. However, in many real cases this simplification is unacceptable, so robust optimal design criteria becomes a viable alternative to better support engineers in the design process. In Robust Design Optimization (RDO) approaches, indeed the solution must be able to not only minimize the performance but also to limit its variation induced by uncertainty. Most of the currently available RDO methods are based on a probabilistic description of the model uncertainty, even if in many cases they are not able to explicitly include the influence of all the possible sources of uncertainties. Therefore, in this study, a fuzzy version of the robust TMD design optimization problem is proposed. The consistency of the fuzzy approach is studied with respect to the available non-probabilistic formulations reported in the literature and an application to an example of a robust design of a linear TMD subjected to base random vibrations in the presence of fuzzy uncertainties. The results show that the proposed fuzzy-based approach is able to give a set of optimal solutions both in terms of structural efficiency and sensitivity to mechanical and environmental uncertainties. [ABSTRACT FROM AUTHOR]

Steel bars pitting corrosion is a process that strongly jeopardises the reliability of the reinforced concrete structures exposed to chlorides. The proper treatment of uncertainties that affects geometrical, mechanical and chemical involved parameters is for some aspects still an open question because the probabilstic approach, ordinarily adopted, presents some limitations not only when few data are available to characterise involved variables but especially when some parameters are ambiguously defined, not only in terms of distribution type. In these circumstances a possibilistic approach could respresent a reasonable alternative to perform this specific reliability analysis. In the present study, the problem parameters are modelled by using a complete fuzzy criterion and a time-dependent fuzzy safety factor is defined in order to evaluate how the residual flexural resistance is greater or less than the bending moment. Moreover, the study provides a more proper mathematical analysis of the chloride penetration into concrete. [ABSTRACT FROM AUTHOR]

Near-source effects can amplify seismic ground motion, causing large demand to structures and thus their identification and characterization is fundamental for engineering applications. Among the most relevant features, forward-directivity effects may generate near-fault records characterized by a large velocity pulse and unusual response spectral shape amplified in a narrow frequency-band. In this paper, we explore the main statistical features of acceleration and displacement response spectra of a suite of 230 pulse-like signals (impulsive waveforms) contained in the NESS1 (NEar Source Strong-motion) flat-file. These collected pulse-like signals are analyzed in terms of pulse period and pulse azimuthal orientation. We highlight the most relevant differences of the pulse-like spectra compared to the ordinary (i.e., no-pulse) ones, and quantify the contribution of the pulse through a corrective factor of the spectral ordinates. Results show that the proposed empirical factors are able to capture the amplification effect induced by near-fault directivity, and thus they could be usefully included in the framework of probabilistic seismic hazard analysis to adjust ground-motion model (GMM) predictions. [ABSTRACT FROM AUTHOR]