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The goal of MATISSE is to develop and implement technologies needed for successfully detecting and quantifying hazards connected with geo-energy operations in the sub-surface, in particular induced seismicity. Anthropogenic earthquakes constitute one of the major environmental impacts associated with geo-resources exploitation. Injection induced events are an undesired dynamic rockmass response to technological processes. Water injection operations taking place during industrial activities such as oil, gas and geothermal exploitation often induce microseismic activity and, under specific circumstances, reactivate existing faults, causing events of considerable size. These industrial activities can also determine air pollution and ground water contamination.Induced seismic hazard is evaluated through the computation and update of ground motion prediction equations, the time-lapse of velocity, attenuation and seismic noise tomography and the computation of pore pressure time variations. All these parameters are correlated with operational activities. A multi-hazard approach aimed at evaluating the adverse effects on environment caused by the sub-surface exploitation of geo-resources is developed.This work has been supported by PRIN-2017 MATISSE project, No 20177EPPN2, funded by Italian Ministry of Education and Research., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Tsunamis constitute a significant hazard for European coastal populations, and the impact of tsunami events worldwide can extend well beyond the coastal regions directly affected. Understanding the complex mechanisms of tsunami generation, propagation, and inundation, as well as managing the tsunami risk, requires multidisciplinary research and infrastructures that cross national boundaries. Recent decades have seen both great advances in tsunami science and consolidation of the European tsunami research community. A recurring theme has been the need for a sustainable platform for coordinated tsunami community activities and a hub for tsunami services. Following about three years of preparation, in July 2021, the European tsunami community attained the status of Candidate Thematic Core Service (cTCS) within the European Plate Observing System (EPOS) Research Infrastructure. Within a transition period of three years, the Tsunami candidate TCS is anticipated to develop into a fully operational EPOS TCS. We here outline the path taken to reach this point, and the envisaged form of the future EPOS TCS Tsunami. Our cTCS is planned to be organised within four thematic pillars: (1) Support to Tsunami Service Providers, (2) Tsunami Data, (3) Numerical Models, and (4) Hazard and Risk Products. We outline how identified needs in tsunami science and tsunami risk mitigation will be addressed within this structure and how participation within EPOS will become an integration point for community development.

Tsunamis are unpredictable and infrequent but potentially large impact natural disasters. To prepare, mitigate and prevent losses from tsunamis, probabilistic hazard and risk analysis methods have been developed and have proved useful. However, large gaps and uncertainties still exist and many steps in the assessment methods lack information, theoretical foundation, or commonly accepted methods. Moreover, applied methods have very different levels of maturity, from already advanced probabilistic tsunami hazard analysis for earthquake sources, to less mature probabilistic risk analysis. In this review we give an overview of the current state of probabilistic tsunami hazard and risk analysis. Identifying research gaps, we offer suggestions for future research directions. An extensive literature list allows for branching into diverse aspects of this scientific approach. © Copyright © 2021 Behrens, Løvholt, Jalayer, Lorito, Salgado-Gálvez, Sørensen, Abadie, Aguirre-Ayerbe, Aniel-Quiroga, Babeyko, Baiguera, Basili, Belliazzi, Grezio, Johnson, Murphy, Paris, Rafliana, De Risi, Rossetto, Selva, Taroni, Del Zoppo, Armigliato, Bureš, Cech, Cecioni, Christodoulides, Davies, Dias, Bayraktar, González, Gritsevich, Guillas, Harbitz, Kânoǧlu, Macías, Papadopoulos, Polet, Romano, Salamon, Scala, Stepinac, Tappin, Thio, Tonini, Triantafyllou, Ulrich, Varini, Volpe and Vyhmeister.

Cloud Analysis is based on simple regression in the logarithmic space of structural response versus seismic intensity for a set of registered records. This method is particularly efficient since it involves non-linear analysis of the structure subjected to a set of un-scaled ground motion time-histories. The simplicity of its underlying formulation makes it a quick and efficient analysis procedure for fragility assessment and/or performance-based safety-checking. Nevertheless, the Cloud Analysis has some limitations; such as, the assumption of a constant conditional standard deviation for probability distribution of the structural response given intensity. Arguably, with the increasing levels of intensity, the conditional dispersion in displacement-based response parameters given intensity may increase. Another complication arises when the structure becomes dynamically unstable (or when the analysis software encounters non-convergence problems, or the Collapse of the building due to large demands takes place) by subjecting to some of the ground motion records used for Cloud Analysis. In such cases, the assumption that structural response given intensity is described by a Log Normal probability distribution with constant standard deviation (one of the underlying assumptions of the Cloud Analysis) no longer holds. However, the method can still be applied to the portion of Cloud response that does not include cases of dynamic instability. Thus, the probability of exceeding a specific structural response value given ground motion intensity can be expressed, using the Total Probability Theorem, as the sum of two probability terms. These terms correspond to the two mutually exclusive and collectively exhaustive portions of the Cloud response; namely, without cases of dynamic instability and with cases of dynamic instability. In such formulation, the probability of dynamic instability given seismic intensity can be calculated by using a generalized regression model (e.g., logistic regression). The transverse frame of a seven-story existing building in Van Nuys, CA, which is modeled in OpenSees considering the flexural-shear-axial interactions, is employed in order to demonstrate this procedure. The critical demand to capacity ratio, corresponding to the component or mechanism that leads the structure closest to the onset of limit state (e.g., near collapse), is adopted as the structural response parameter. This structural response parameter, that is equal to unity at the onset of limit state, can encompass both ductile and fragile failure mechanisms. Moreover, it can register a possible shift in the governing failure mechanism with increasing intensity. The results for probabilistic demand assessment based on the Cloud Analysis considering the cases of dynamic instability are compared with those obtained based on non-linear dynamic analysis methods such as Incremental Dynamic Analysis and Multiple Stripe Analysis. It is demonstrated that, with a careful selection of ground motion records, this method leads to reasonably accurate results with considerably reduced analysis effort.

In different high seismic regions around the world, many nonductile existing reinforced concrete frame buildings, built without adequate seismic detailing requirements, have been damaged or collapsed after past earthquakes. These concrete frame buildings are much more susceptible to collapse than modern code-conforming frames. Therefore, for this type of structures, it is necessary to accurately model materials and members to capture the flexure, shear and flexure-shear failure modes in members and the potential collapse of the structure. In this paper, alternative retrofit methods are evaluated for these older frame buildings using a nonlinear structural performance assessment methodology. As a case study, the transverse frame of an existing building is modeled, including the effect of flexural-shear-axial load interaction and the bar slip deformation component to be able to capture also column shear and axial failures. A framework for probability-based demand and capacity factor design (DCFD) seismic safety evaluation is implemented in order to evaluate the structural performance at each chosen performance level. This study shows that it is a critical issue to choose the most effective retrofit strategy based on the assessed performance of the bare frame. Moreover, the estimates of expected life cycle cost are compared for the retrofit methods considered in this research.

The age distribution for jacket-type offshore platforms in the Persian Gulf shows that relatively large numbers of installations have already passed their design life, which is around 25 years in that area. Despite the fact that reconstruction and repair of an existing installation are more economical than construction of a new one, assessment of existing jacket-type offshore platforms beyond their design life has been an issue for consideration. If a structure is intended to be used beyond its design life, a thorough control of the structural safety must be executed. Strictly speaking, desired extension of service life may create a need for requalification of a structure. Being events with extreme consequences, small frequency, and large uncertainty associated with their occurrence, extreme waves are among the most significant input to a jacket-type offshore platform. Hence, probabilistic methods are required for taking into account the safety compliance with regard to life extension of existing jacket structure.

Subset Simulation is an advanced simulation procedure which is efficient for calculating the small failure probabilities corresponding to structural limit states. Moreover, it is robust with respect to the number of uncertain parameters in the problem and it is applicable to any type of structural model and any loading. Reinforced concrete structures are a particular case in which the effect of structural modelling uncertainties could be considerable. This study presents an application of the Subset Simulation technique to the seismic assessment of an ”olddesign” RC frame structure taking into account both ground motion and structural modelling uncertainties. The structure selected for the application is an 8-storeys RC plane frame designed for conventional seismic actions without modern-code detailing and ductility provisions. The uncertainty in members’ shear strength, yield and ultimate chord rotation capacities is accounted for. The uncertainty in the material modelling parameters such as concrete strength and steel yield and ultimate stress is also included. The probabilistic representation for the ground motion time-history is constructed based on a stochastic ground motion model and on the joint distribution of magnitude and distance for the site, as obtained from the de-aggregation of seismic hazard. The performance of the structure is measured in terms of a system-level scalar damage measure that accounts for a set of possible failure modes of the structure. The effect of the uncertain structural modelling parameters on the first-passage probabilities associated with the structural performance variable is studied. Finally, the results of Subset simulation are post-processed in order to generate fragility curves which are bench-marked against the fragility curves obtained directly based on structural response to a small set of scaled recorded motions.

Palm Springs (CA), USA

Modeling parameter uncertainty can affect significantly the structural seismic reliability assessment. However, this type of uncertainty may not be described by a Poisson process as it lacks renewal properties with the occurrence of each earthquake event. Furthermore, considering uncertainties related to ground motion representation by employing as-recorded ground motions together with modeling parameter uncertainties can prove quite challenging. Robust fragility assessment, proposed previously by the authors, employs the structural response to recorded ground motion as data in order to update prescribed seismic fragility models. Robust fragility can be extremely efficient for considering also the structural modelling uncertainties by creating a dataset of one-to-one assignments of structural model realizations and as-recorded ground motions. This can reduce the computational effort by about two orders of magnitude. However, it should be kept in mind that the fragility concept is based on the underlying assumption of Poisson-type renewal. Using the concept of updated robust reliability, considering both uncertainty in ground motion representation based on as-recorded ground motion and non-ergodic uncertainties, the conservative error introduced by adopting Poissonian structural reliability assessment based on the robust fragility concept can be quantified.

The majority of bridge infrastructure in Italy has been built in the 60’s and 70’s without specific seismic provisions. Therefore, it is expected that they reveal high seismic vulnerability if subjected to a significant seismic event. Given this background, it is natural that rapid and accurate assessment of economic losses incurred to bridge infrastructure can play a crucial role in emergency management in the immediate aftermath of an earthquake. Focusing on the infrastructure system of highway bridges in the Campania region, it is shown how state of the art methodologies in portfolio loss assessment and available data can be implemented in order to assess the probability distribution of the repair costs incurred to the portfolio in question due the Irpinia 1980 earthquake. Formulating the probabilistic loss assessment for the portfolio of bridges as a standard Monte Carlo Simulation problem helps in resolving the spatial risk integral efficiently. One of the specific features of this case-study is the use of statistical methods for updating, a) ground motion prediction; b) vulnerability/fragility; and c) exposure/cost models based on available data. It has been observed that alternative hypotheses with regard to the ground motion correlation structure can significantly affect the distribution of the direct economic loss. Furthermore, updating the ground motion prediction based on available recordings may significantly reduce the dispersion in the estimation of the direct economic losses.

The present study aims to calculate the expected insurance premium for Italian building stock subjected to seismic hazard in its service lifetime based on probabilistic loss estimation. A methodology is presented that takes into account the uncertainty in the occurrence of future events due to seismic hazard. The expected insurance premium can then be evaluated based on the probabilities that the structure exceeds a set of discrete limit state thresholds. Finally, the methodology is implemented in an illustrative numerical example which considers the Italian residential building stock discretized in 5 structural typologies and in 8088 areas, corresponding to the Italian municipalities. An insurance model assuming monopoly market is built, assuming risk aversion of the property owners and risk neutrality of the insurance companies. Hence, the insurance premium is evaluated for each structural typology in each Italian municipality, also considering maximum coverage and insurance excess systems. Results are aggregated to compute the total expected loss per year of the whole Italian building stock, the total income and profit of the insurance company, assuming an insurance contract for all the property owners.

In performance-based earthquake engineering, the suitability of an intensity measure (IM) is expressed through its efficiency and sufficiency. An efficient IM leads to a small record-to-record variability in the estimation of demand given seismic intensity. A sufficient IM is one that renders the estimation of demand for all intensity levels independent of all other ground motion parameters. Given that establishing sufficiency is not a trivial task, the relative sufficiency measure (RSM) has been proposed previously based on information theory concepts. RSM can be employed for quantifying the relative sufficiency of an IM with respect to another IM by the amount of extra information that it relays on average about the ground motion for the estimation of a demand parameter of interest. RSM has been so far conditioned on a linear logarithmic regression probability model, better known as the Cloud Analysis (CA), which relies on unscaled ground-motion records. This work lays out the methodology for estimating both the efficiency and RSM in terms of the damage measure directly (instead of demand parameter) and by employing alternative nonlinear dynamic analysis procedures (NDAPs), such as, a modified version of CA that considers the collapse-cases explicitly and the incremental dynamic analysis. It is demonstrated that the RSM can be sensitive to the NDAP employed, while it does not demonstrate significant sensitivity to the limit state of interest. An alternative measure of efficiency (known in literature as proficiency), directly measured as the dispersion in the fragility curve, shows more sensitivity to the limit state.

Recent earthquakes have exposed the vulnerability of existing buildings; this is demonstrated by damage incurred after moderate-to-high magnitude earthquakes. This stresses the need to exploit available data from different sources to develop reliable seismic risk components. As far as it regards empirical fragility assessment, accurate estimation of ground-shaking at the location of buildings of interest is as crucial as the accurate evaluation of observed damage for these buildings. This implies that explicit consideration of the uncertainties in the prediction of ground shaking leads to more robust empirical fragility curves. In such context, the simulation-based methods can be employed to provide fragility estimates that integrate over the space of plausible ground-shaking fields. These ground-shaking fields are generated according to the joint probability distribution of ground-shaking at the location of the buildings of interest considering the spatial correlation structure in the ground motion prediction residuals and updated based on the registered ground shaking data and observed damage. As an alternative to the embedded coefficients in the ground motion prediction equations accounting for subsoil categories, stratigraphic coefficients can be applied directly to the ground motion fields at the engineering bedrock level. Empirical fragility curves obtained using the observed damage in the aftermath of Amatrice Earthquake for residential masonry buildings show that explicit consideration of the uncertainty in the prediction of ground-shaking significantly affects the results.