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An application of the naïve Bayesian classifier for selecting strong motion data in terms of the deformation probably induced on a given structural system is presented. The main differences between the proposed method and the “standard” procedure based on the inference of a polynomial relationship between a single intensity measure and the engineer...
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... We made these analyses on the maximum of the three components. Lancieri et al. (2015) showed that these are the most influential parameters on seismic structural analysis. ...
The eastern offshore of Martinique is one of the active areas of the Lesser Antilles Subduction Zone (LASZ). Although its seismicity is moderate compared to other subduction zones, LASZ is capable of generating a M 7+ interplate earthquake and recent studies and historical events, such as the M8 1839 and M 7-7.5 1946 earthquakes, confirm this possibility. Given the high risk that Martinique can face in case of unpreparedness for such a M 7+ earthquake, and the lack of a regional seismic hazard study, we investigated through numerical modelling how ground motion can vary for a hypothetical Mw 7.5 interplate earthquake. Our main objective is to highlight the major factors related to earthquake source that can cause the highest variation in ground motion at four broadband seismic stations across Martinique. For this purpose, we generated 320 rupture scenarios through a fractal kinematic source model, by varying rupture directivity, source dimension, slip distribution. We computed the broadband ground motion (0.5-25 Hz) by convolution of source-time functions with Empirical Green’s Functions (EGFs), that we selected from the analysis of moderate events (M 4-4.5) recorded in the area of interest since 2016 by the West Indies network. We found that the fault geometry and the spatial extension of the largest slip patch are the most influential factors on ground motion. The significance of the variation of the predicted ground motion with respect to ground motion prediction equations (GMPEs) depends on the evaluated frequency of ground motion and on the station. Moreover, we concluded that the EGF selection can be another significant factor controlling the modelled ground motion depending on station. Our results provide a new insight for the seismic source impact on ground motion across Martinique and can guide future blind seismic hazard assessment studies in different regions.
... In our particular case, having considered only one feature at a time, it coincides with the full Bayes theorem. We hereby give a synthetic overview of the procedure; for more details on the procedure itself and on the underlying statistics, we refer the reader to Lancieri et al. (2015) and references therein. ...
Macroseismic intensity provides a qualitative description of seismic damage. It can be associated with Ground Motion Parameters (GMPs), which are extracted in near real-time from instrumental recordings during an earthquake. Several formulations of this empirical association exist in literature for Italy, mainly focusing on the relationship between intensity expressed on the Mercalli-Cancani-Sieberg (MCS) scale and peak ground acceleration or velocity. They are usually in the form of Ground Motion to Intensity Conversion Equations (GMICEs), which treat intensity as a continuous quantity. We propose an alternative approach, the Gaussian Naïve Bayes (GNB) classifiers, which allows to correctly treat intensity according to its ordinal definition. As a comparison, we also implement a modified version of the standard GMICE approach. We expand the existing database of GMP/MCS-intensity points with new, high-quality accelerometric data recorded in Italy in the period from 2002 to 2016 and resample the database by treating the intermediate intensities with half integer values (which are not meaningful in the MCS description) as both belong to the above and below full integer classes with an assigned weight. As a result, we estimate a new set of regression relations and GNB probability distributions between integer MCS intensity classes and eight GMPs (peak acceleration, velocity, displacement, Arias and Housner intensities, spectral acceleration at 0.3, 1.0 and 3.0 s). Results based on PGA and PGV are the most stable on the whole intensity scale. GNB models score better than GMICEs in terms of performance on unseen data and classification scores.
... ground acceleration (PGA), spectral acceleration (SA) values at 1, 2 and 5 Hz, and Arias inten-309 sity. We made these analyses on the maximum of the three components.Lancieri et al. (2015) 310 ...
... Shinozuka et al., 2000) approach, which only requires a separation between the intact and damaged states (i.e., respectively blue and red points in Figure 3). To this end, a large number of ground-motion parameters is evaluated as potential IMs: The adequacy of IMs for the derivation of fragility curves has been addressed by many studies, using efficiency and sufficiency indicators (Luco & Cornell, 2007), statistical classifiers (Lancieri et al., 2015) or the concept of hazard compatibility (Hariri-Ardebili & Saouma, 2016). Based on these previous works, it is proposed to use three performance metrics in order to estimate the adequacy of the considered IMs: ...
In nuclear applications, fragility curves are an essential element of the seismic probabilistic safety assessment that is performed at the level of the power plant. They are required to account for the aleatory randomness and the epistemic uncertainty generated by various sources of variability, such as the representation of the seismic input by intensity measures, the assumptions in the structural model (e.g., mechanical or geometrical parameters) and the confidence in the statistical estimation of the fragility parameters (i.e., related to number of data points used). Therefore, this study investigates the relative contributions of such variables to the dispersion of the resulting fragility functions, while ensuring the separation between aleatory and epistemic uncertainty sources, as advocated by the standards in effect in the nuclear industry. To this end, vector-valued fragility functions, based on two intensity measures, are also investigated: it appears that they allow for a partial transfer from the record to record variability to an epistemic uncertainty component that is related to the description of the seismic loading given the hazard at the studied site. The proposed uncertainty decomposition is applied to the fragility assessment of the main steam line of a nuclear reactor: the total dispersion of the resulting fragility models is then decomposed into different aleatory and epistemic components. Although it is found that vector valued intensity measures contribute to a significant part of the total dispersion, the uncertainty due to the variability of mechanical and geometrical parameters appears to be even larger.
... The commonly used vector IM is the combination of the PSA at the natural frequency of a structure with the number of standard deviation (i.e., epsilon). Some studies (e.g., Zhai et al., 2013;De Biasio et al., 2014;Lancieri et al., 2015;Kohrangi et al., 2016) have shown a good correlation between the certain IMs and the seismic behavior of structures, which motivate the use of IMs in the GM selection. ...
The observed variability is very large among natural earthquake records, which are not consolidated in the engineering applications due to the cost and the duration. In the current practice with the nonlinear dynamic analysis, the input variability is minimized, yet without clear indications of its consequences on the output seismic behavior of structures. The study, herein, aims at quantifying the impact of ground motion selection with large variability on the distribution of engineering demand parameters (EDPs) by investigating the following questions:What is the level of variability in natural and modified ground motions?What is the impact of input variability on the EDPs of various structural types?For a given earthquake scenario, target spectra are defined by ground motion prediction equations (GMPEs). Four ground motion modification and selection methods such as (1) the unscaled earthquake records, (2) the linearly scaled real records, (3) the loosely matched spectrum waveforms, and (4) the tightly matched waveforms are utilized. The tests on the EDPs are performed on a record basis to quantify the natural variability in unscaled earthquake records and the relative changes triggered by the ground motion modifications.Each dataset is composed by five accelerograms; the response spectrum compatible selection is then performed by considering the impact of set variability. The intraset variability relates to the spectral amplitude dispersion in a given set, and the interset variability relates to the existence of multiple sets compatible with the target.The tests on the EDPs are performed on a record basis to quantify the natural variability in unscaled earthquake records and the relative changes triggered by the ground motion modifications. The distributions of EDPs obtained by the modified ground motions are compared to the observed distribution by the unscaled earthquake records as a function of ground motion prediction equations, objective of structural analysis, and structural models.This thesis demonstrates that a single ground motion set, commonly used in the practice, is not sufficient to obtain an assuring level of the EDPs regardless of the GMSM methods, which is due to the record and set variability. The unscaled real records compatible with the scenario are discussed to be the most realistic option to use in the nonlinear dynamic analyses, and the ‘best’ ground motion modification method is demonstrated to be based on the EDP, the objective of the seismic analysis, and the structural model. It is pointed out that the choice of a GMPE can provoke significant differences in the ground motion characteristics and the EDPs, and it can overshadow the differences in the EDPs obtained by the GMSM methods.
... For example, under the seismological point of view, each IM describes a single property of the strong ground motion: a peak value occurring in time domain (i.e., PGA), or peaks in frequency domain (PSA), energy estimated in time domain (Arias Intensity or cumulative absolute velocity, CAV) or energy estimated in a given frequency band (Housner or Spectral Intensity). The point is that a single IM is not always sufficient to fully explain the structural behaviour (De Biasio, 2014) and a combination of IM can be more suitable (Perraut et Guéguen, 2014;Lancieri et al., 2015). ...
The major cause of earthquake damage to an embankment is the liquefaction of the soil foundation that induces ground-level deformations. The aim of this paper is to assess numerically the effect of the liquefaction-induced settlement of the soil foundation on a levee due to real earthquakes. The seismic vulnerability is evaluated in terms of analytical fragility curves constructed on the basis of nonlinear dynamic finite-element (FE) analysis. However, FE analysis can be expensive because of the very large number of simulations needed for an accurate assessment of the system failure behavior. This problem is addressed by building a Gaussian process (GP) emulator to represent the output of the expensive FE model. A comparison with the FE reference results suggests that the proposed GP model works well and can be successfully used as a predictive tool to compute the induced damage on the levee. Findings also illustrate clearly the importance and the advantages of an adequate definition of the input parameters to build the GP model.
