Eugenio Chioccarelli

The Central Italy Seismic Sequence between August and December 2016: Analysis of Strong‐Motion Observations

ABSTRACT Since August 2016, central Italy has been struck by one of the most important seismic sequences ever recorded in the country. In this study, a strong‐motion data set, consisting of nearly 10,000 waveforms, has been analyzed to gather insights about the main features of ground motion, in terms of regional variability, shaking intensity, and near‐source effects. In particular, the shake maps from the three main events in the sequence have been calculated to evaluate the distribution of shaking at a regional scale, and a residual analysis has been performed, aimed at interpreting the strong‐motion parameters as functions of source distance, azimuth, and local site conditions. Particular attention has been dedicated to near‐source effects (i.e., hanging wall/footwall, forward‐directivity, or fling‐step effects). Finally, ground‐motion intensities in the near‐source area have been discussed with respect to the values used for structural design. In general, the areas of maximum shaking appear to reflect, primarily, rupture complexity on the finite faults. Large ground‐motion variability is observed along the Apennine direction (northwest–southeast) that can be attributed to source‐directivity effects, especially evident in the case of small‐magnitude aftershocks. Amplifications are observed in correspondence to intramountain basins, fluvial valleys, and the loose deposits along the Adriatic coast. Near‐source ground motions exhibit hanging‐wall effects, forward‐directivity pulses, and permanent displacement.

Operational (Short-Term) Earthquake Loss Forecasting in Italy

Abstract The seismological community is currently developing operational earthquake forecasting (OEF) systems that aim to estimate the seismicity in an area of interest, based on continuous ground‐motion recording by seismic networks; the seismicity may be expressed, for example, in terms of rates of events exceeding a certain magnitude threshold in a short period of time (days to weeks). OEF possibly may be used for short‐term seismic risk management in regions affected by seismic swarms only if its results may be the input to compute, in a probabilistically sound manner, consequence‐based risk metrics. The present article reports on the feasibility of short‐term risk assessment, or operational earthquake loss forecasting (OELF), in Italy. The approach is that of performance‐based earthquake engineering, in which the loss rates are computed by means of hazard, vulnerability, and exposure. The risk is expressed in terms of individual and regional measures, which are based on short‐term macroseismic intensity (or ground‐motion intensity) hazard. The vulnerability of the built environment relies on damage probability matrices empirically calibrated for Italian structural classes; the exposure is represented in terms of buildings per vulnerability class and occupants per building typology. All vulnerability and exposure data are at the municipality scale. The developed procedure, which is virtually independent of the seismological model used, is implemented in an experimental OELF system that continuously processes OEF information to produce nationwide risk maps applying to the week after the OEF data release. This is illustrated by a retrospective application to the 2012 Pollino (southern Italy) seismic sequence, which provides insights on the capabilities of the system and on the impact of the methodology currently used for OEF in Italy on short‐term risk assessment.

REASSESS V1.0: A COMPUTATIONALLY-EFFICIENT SOFTWARE FOR PROBABILISTIC SEISMIC HAZARD ANALYSIS

Abstract. A stand-alone software for the probabilistic assessment of seismic hazard is developing. In its final version, it shall be structured in three modules for: (i) site-specific, (ii) scenario-based and (iii) multi-site (regional) analyses. This paper focuses on (i), which is devoted to single-site probabilistic seismic hazard analysis (PSHA). Seismic sources can be either zones or individual faults. The algorithm to compute PSHA is implemented assuming, classically, that the process of occurrence of earthquakes on each seismic source follows a homogeneous Poisson process; the processes for different sources are independent. The required input data are: (1) the source(s) geometry and the annual rate(s) of occurrence of earthquakes in the magnitude interval of interest; (2) the distribution of magnitude given the occurrence of one earthquake; (3) the ground motion propagation model (GMPM); (4) the soil classification at the site for which hazard is evaluated. Regarding (1-3), the user is aided by some library implemented in the software. REASSESS also is able to account for model uncertainty, in fact, logic trees can be built based on alternatives for the source’s annual rate of earthquake occurrence, magnitude distribution and GMPM. The strength of REASSESS, beyond the user-friendly interface, stays in the PSHA computation algorithms. These have been coded in MATLAB®, targeting accuracy and reduced computing time. Its potential for earthquake engineering and engineering seismology applications is illustrated by a few applications discussed in the paper.

ACCOUNTING FOR NEAR-SOURCE EFFECTS IN THE DISPLACEMENT COEFFICIENT METHOD FOR SEISMIC STRUCTURAL ASSESSMENT

Non-linear static procedures are well-established analytical tools for performance- based seismic design and assessment. On the other hand, near-source (NS) ground motions are emerging as relevant to structural engineering because they may be characterized by seismic demand larger and systematically different than that typically induced by so-called ordinary records. This is the result of phenomena such as rupture forward directivity (FD), which may lead to the appearance of distinct velocity pulses in the ground motion velocity time-history. Lately, effort was put towards the framework necessary for taking FD into ac- count in probabilistic seismic hazard analysis (PSHA). The objective of the present study is to discuss the extension of non-linear static procedures, such as the displacement coefficient method (DCM), with respect to the inelastic demand associated with FD. In this context, the DCM is implemented to estimate NS seismic demand by making use of the results of NS-PSHA, developed for single-fault-case scenarios. A predictive model for NS-FD inelastic displace- ment ratios, previously developed by the authors, is employed. An illustrative application of the DCM, with explicit inclusion of NS-pulse-like effects, is given for a plane R/C frame de- signed under modern code provisions.

Age- and State-Dependent Seismic Reliability of Structures

ABSTRACT: Life-cycle analysis of civil structures requires stochastic modeling of degradation. Phenomena causing structures to degrade are typically categorized as aging and point-in-time overloads. The former refers to deterioration of material characteristics and/or small yet frequent shocks, while earthquake effects are the members of the latter category this study deals with. Earthquake damage is usually modeled as dependent on the state of the structure at the time of each seismic shock only, while increments of deterioration due to aging are typically assumed to depend on the age of the structure at the most. While several studies deal with stochastic modeling of degradation they neglect, in an attempt to obtain easy-to-compute equations for the life-cycle reliability, to account at the same time for both forms of dependency. The presented study explicitly addresses this issue via a Markov-chain-based approach. Indeed, the model, which is practically in closed-form even if approximate, is able to describe a generic age- and state-dependent degradation process. The model also relies on the homogeneous Poisson process assumption for earthquake occurrence, a common case in seismic hazard analysis. An illustrative application shows the potential of the model. 1. INTRODUCTION Mainly because of the importance of sustainability-related issues, there is an increasing interest in the life-cycle analysis of civil constructions. The latter requires modeling structural performance across the service life. Indeed, structures are generally subjected to degradation, the evaluation of which may aid in design of maintenance policies. It is common to distinguish phenomena causing degradation in two main categories: aging that may reflect on structural performance, and instantaneous (with respect to the lifespan of the structure) and observable overloads, such as earthquakes. Both cause damage accumulation on structures and both are random in nature. Aging is related to an aggressive environment, which worsens the mechanical features of structural elements (e.g., corrosion of reinforcing steel due to chloride attack, carbonation in concrete, etc.) or shocks the occurrence of which may be difficult to observe (e.g., ambient vibrations, traffic loads, fatigue, etc.). Degradation due to aging is typically described assuming that it takes place gradually over time. Earthquake shocks potentially cumulate damage on the hit structure during its lifetime. In general, mainly because earthquake occurrences can be treated as instantaneous with respect to structural life, that is safety-treating point-in-time events, it is advantageous to model the cumulative seismic damage process separately from aging (i.e., gradual deterioration). A number of studies has recognized the stochastic nature of structural degradation, and approached modeling for reliability assessment; e.g., Pandey and van Noortwijk (2004). Some of the proposed models specifically address one of the two causes of deterioration, while more

Aftershocks’ Effect on Structural Design Actions in ItalyAftershocks’ Effect on Structural Design Actions in Italy

Although earthquakes generally form clusters in both space and time, only mainshocks, usually the largest magnitude events within clusters, are considered by probabilistic seismic hazard analysis (PSHA; Cornell, 1968). On the other hand, aftershock PSHA (APSHA), based on the modified Omori law, allows the quantification of the aftershock threat (Yeo and Cornell, 2009). Classical PSHA often describes event occurrence via a homogeneous Poisson process, whereas APSHA describes occurrence of aftershocks via cluster-specific nonhomogeneous Poisson processes, the rate of which is a function of the mainshock magnitude. It is easy to recognize that clusters, each of which is made of the mainshock and the following aftershocks, occur at the same rate of mainshocks. This recently allowed the generalization of the hazard integral to account for aftershocks in PSHA (i.e., Iervolino et al., 2014), which resulted in the formulation of the so-called sequence-based PSHA (SPSHA). In the present study, SPSHA is applied to Italy countrywide, using the same source model (Stucchi et al., 2011) that lies at the base of the official PSHA used for structural design, to quantitatively assess the increase in seismic design actions for structures when accounting for the aftershocks.

Erratum to: Operational earthquake loss forecasting: a retrospective analysis of some recent Italian seismic sequences

Operational earthquake forecasting (OEF) relies on real-time monitoring of seismic activity in an area of interest to provide constant (e.g., daily) updates of the expected number of events exceeding a certain magnitude threshold in a given time window (e.g., 1 week). It has been demonstrated that the rates from OEF can be used to estimate expected values of the seismic losses in the same time interval OEF refers to. This is a procedure recently defined as operational earthquake loss forecasting (OELF), which may be the basis for rational short-term seismic risk assessment and management. In Italy, an experimental OELF system, named MANTIS-K, is currently under testing. It is based on weekly rates of earthquakes exceeding magnitude (M) 4, which are updated once a day or right after the occurrence in the country of an M 3.5+ earthquake. It also relies on large-scale structural vulnerability and exposure data, which serve to the system to provide continuously the weekly expected number of: (1) collapsed buildings, (2) displaced residents, and (3) casualties. While the probabilistic basis of MANTIS-K was described in previous work, in this study OELF is critically discussed with respect to three recent Italian seismic sequences. The aim is threefold: (1) illustrating all the features of the OELF system in place; (2) providing insights to evaluate whether if it would have been a useful additional tool for short-term management; (3) recognizing common features, if any, among the losses computed for different sequences.