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Pulse-wave propagation velocity and resonance frequency measured in civil engineering structures are both related to structural design. Monitoring their variation following seismic strong shaking provides information about the immediate building capacity. Joint-interpretation of frequency and velocity variation requires a better understanding of the processes controlling seismic structural health. In this study, we analysed 8 years of earthquake data recorded by the vertical array installed in the Te Puni building in Wellington, New Zealand, as part of the GeoNet building instrumentation programme. Co-seismic variations of pulse wave velocity and fundamental frequency are analysed and interpreted through a Timoshenko beam-like building model. This study shows that even though no structural damage was visually reported over the considered time of monitoring, co- and post-seismic variation of both parameters’ values are observed for almost all earthquakes, including a permanent shift following strong ground shaking. Variations of pulse-wave velocity and resonance frequency are cross-interpreted in terms of the building model. They reflect a time variant building response, correlated with the seismic loading. In addition, time delay of the pulse-wave velocity as a function of the building height provides relevant information on the location of the changes and confirms the efficient cross-interpretation of both methods for seismic Structural Health monitoring.

We performed large-scale earthquake economic loss estimations for France and cost–benefit analyses for several French cities by developing a semiempirical, intensity-based approach. The proposed methodology is inexpensive and easily applicable in case of a paucity of detailed information regarding the specific regional seismic hazard and the structural characteristics of the building stock, which is of particular importance in moderate-to-low seismic hazard regions. The exposure model is derived from census datasets, and the seismic vulnerability distribution of buildings is calculated using data mining techniques. Several hypothetical, large-scale retrofit scenarios are proposed, with increasing levels of investment. These cities, in their respective reinforced states, are then subjected to a series of hazard scenarios. Seismic hazard data for different return periods are calculated from regulatory accelerations from French seismic zoning. Loss estimations for the original (non-reinforced) configuration show high levels of expected building repair and replacement costs for all time spans. Finally, the benefits in terms of damage avoidance are compared with the costs of each retrofit measure. Relatively limited strengthening investments reduce the probability of building collapse, which is the main cause of human casualties. However, the results of this study suggest that retrofitting is, on average, only cost-effective in the parts of France with the highest seismicity and over the longest time horizons.

We performed a seismic vulnerability assessment of the city of Constantine (Algeria) using the Risk-UE and datamining-based methods [association rule learning (ARL)]. The ARL method consists in establishing relationships between building attributes (number of stories or building age) and the vulnerability classes of the European Macro-seismic Scale, EMS98. This approach avoids the costly process of drawing up an inventory of building characteristics in the field, which often discourages the assessment of seismic risk initiatives in weak to moderate seismic-prone regions. We showed that the accuracy of the assessment is independent of the subset used for the learning phase leading to development of the Constantine vulnerability proxy. Considering only two attributes, the vulnerability assignment is equal to about 75%, reaching 99% if material is added to the attributes considered. Comparison of Risk-UE and ARL results revealed a reliable assessment of vulnerability, the differences having only a slight impact on the probability of exceeding the damage level computed by EMS98 or Risk-UE in Constantine. The results of this study suggest that the ARL-based vulnerability proxy is efficient and could be applied to the rest of Algeria.

In this paper, a simple analysis is done to explain the observed increase of resonance frequency of City-Hall building in Grenoble (France), a 12-story reinforced concrete building. This period corresponds also to the observed variation of the resonance frequency of the Grenoble’s sedimentary basin. The postulated hypothesis is that the frequency increase reflects the stiffness increase of the soil–structure system related to the cold period that hit Western Europe in 2012. To explore this hypothesis we have processed continuous recording during the early 2012 recorded at the roof level and at a close free-field accelerometric station. The variation of site effect is monitored by the horizontal-to-vertical spectral ratio of seismic noise, and the variation of apparent and system frequencies of the building by the random decrement technique. Apparent frequency is computed by deconvolution method between roof and basement. The maximum freezing penetration is 0.75 m and the horizontal relative motion stiffness of the foundation is strongly sensitive to the modification of the upper soil layer. The results suggest a variation (

In this study, we analyze the efficiency of the ratio between particle velocity and shear wave velocity as a strain proxy for evaluating the nonlinear seismic response of sediments. The in situ stress–strain relationships are derived from accelerometric vertical array recordings at the TST site in Volvi (Thessaloniki, Greece). First, the shear wave velocity between two successive sensors was computed by seismic interferometry and strain was computed as the velocity ratio or the relative displacement between sensors. The shear-wave velocity profile and in situ shear modulus degradation curve with strain were compared with previous studies performed at the TST site. Finally, the stress–strain relationships were derived from data recorded at the surface by extending the strain proxy and stress values to the ratio between peak ground velocity and the Vs30 parameter used for site classification, i.e. without requiring the accelerometric vertical array. Our model captures the in situ nonlinear response of the site, without consideration of azimuth or distance of the earthquakes. In conclusion, the acceleration (stress) values, based on the accelerometric response spectra instead of peak ground acceleration compared with the deformation (strain) proxy, provide an effective model of the in situ nonlinear response, providing information that can be integrated into ground motion prediction equations.

An application of the naive 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 engineering demand parameter are: the discrete description of the engineering demand parameter; the use of an array of intensity measures; the combination of the information issued from the training phase via a Bayesian formulation. Six non-linear structural systems with initial fundamental frequency of 1, 2 and 5 Hz and with different strength reduction factors are modelled. Their behaviour is described using the Takeda hysteretic model and the engineering demand parameter is expressed as the relative drift. A database of 6,373 strong motion records is built from worldwide catalogues and is described by a set of “classical” intensity measures; it constitutes the “training dataset” used to feed the Bayesian classifier. The structural system response is reduced to a description of three possible classes: elastic, if the induced drift is lower than the yield displacement; plastic, if the drift ranges between the yield and the ultimate drift values; fragile if the drift reaches the ultimate drift. The goal is to evaluate the conditional probability of observing a given status of the system as a function of the intensity measure array. To validate the presented methodology and evaluate its prediction capability, a blind test on a second dataset, completely disjointed from the training one, composed of 7,000 waveforms recorded in Japan, is performed. The Japanese data are classed using the probability distribution functions derived on the first data set. It is shown that, by combining several intensity measures through the likelihood product, a stable result is obtained whereby most of the data ( $$>$$ 75 %) are well classed. The degree of correlation between the intensity measure and the engineering demand parameter controls the reliability of the probability curves associated to each intensity measure.

In recent years, many studies have been focused on the use and effectiveness of passive islotaing devices for reducing the effect of seismic ground motion on buildings. Among the available methods, one consists in isolating the structure using rubber bearings, the solution certainly the most accomplished and having the most feedback. In this study, we focused on the case of Martinique earthquake (Mw=7.4) of 29 November 2007, recorded by accelerometric stations installed at the Centre de Decouverte des Sciences de la Terre (Martinique), a base-isolation building with rubber bearings. Several earthquakes are used in this paper, from moderate to strong ground motion. Ambient vibration modal analysis is first described in order to understand the elastic response of the building. The earthquake data are then interpreted, in particular to understand the mechanism of vibration of the structure and its comparison with the experimental modes previously estimated using ambient vibrations.

International audience; Over recent years there has been a growing interest in the building frequency analysis for earthquake and structural engineering fields using ambient vibrations. Simultaneously, velocity measurements with LASER remote sensing techniques have gained more interest for several applications. This paper details the comparison of the frequency analysis obtained using sensitive velocimeter sensor and coherent LIDAR (Light Detection and Ranging) sensor, and applied to one RC existing building. Ambient vibrations recordings were processed using the Frequency Domain Decomposition method for defining the frequencies and mode shapes of the building target, while LASER remote sensing approach used coherent LIDAR method for velocity and frequency measurement. The results of the two systems are discussed. A good agreement is observed, which let us conclude on the ability of the coherent LIDAR to assess the frequency of existing buildings for structural and earthquake engineering fields at long range and without any retroreflector on the structure.

We study the nature of energy bursts that appeared in the frequency range 3–5 Hz in ambient seismic noise recorded in the Grenoble basin (French Alps) during a seismological array experiment. A close agreement is found between the identified azimuths of such noise bursts with the location of an industrial chimney. In-situ measurements of the chimney dynamic characteristics show a coincidence between the frequency of the first harmonic mode of the chimney and the fundamental frequency of a thin surficial layer that overlay the deep sediment fill. The interaction between the chimney and the surficial layer is then numerically simulated using simple impedance models and two soil profiles. Simulations exhibit a satisfactory agreement with observations and suggest that energy bursts result of inertial structure-soil interaction favored by resonance effects between the first harmonic mode of the structure and the fundamental frequency of the topmost layer.