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Seismic monitoring of structures : characterization of building response by analyzing nonlinear elasticity and slow dynamics

Abstract : Monitoring structural response is fundamental for evaluating the performance of buildings and reducing losses during future earthquakes. One practical way to detect changes in structural behavior is analyzing variations of elastic properties during dynamic excitations. Here we show that variations in the fundamental frequency of buildings during (weak -to- strong) earthquakes might be explained by nonlinear elastic processes carried out within the structural material, which affect the global macroscopic structural behavior. These nonlinear elastic processes are responsible for both transitory and permanent structural softening, and might explain the intriguing recovery effects observed in the fundamental frequency of buildings following seismic events. This study bridges the gap between microscale laboratory experiments and macroscale seismological observations, where nonlinear elasticity is also observed. In the first part of this study, a new seismic database of building responses is presented: thousands strong motion recordings and several buildings from Japan and US were processed, providing useful tools for the earthquake engineering community, notably for the empirical prediction of structural response as a function of several ground motion intensity measures. Examples of uncertainties associated to damage prediction are presented, as well as the vulnerability assessment of a building throughout fragility curves. Next, the seismic database is used to analyze nonlinear elastic signatures in buildings, particularly the slow dynamics or relaxation effects. Variations of resonant frequencies are monitored at both short and long-term, estimating the contribution of soil in the response of the system soil-structure. Different levels of damage are inferred according to loading amplitudes and structural states. Some laboratory-based models of relaxation are adapted to the building data in order to infer crack-density and heterogeneities over time, making comparisons between structural states before and after large excitations such as the Mw 9 Tohoku earthquake. Conditioning effects are observed during the backbone recovery of aftershocks sequences. The results are extended to different building typologies, analyzing the influence of structural material and loading features, notably strain-rates. Finally, some general conclusions are presented, together with a perspective work using machine learning to predict building response based on nonlinear elastic signatures.
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https://tel.archives-ouvertes.fr/tel-02443212
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Submitted on : Friday, January 17, 2020 - 8:09:16 AM
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Ariana Astorga Nino. Seismic monitoring of structures : characterization of building response by analyzing nonlinear elasticity and slow dynamics. Earth Sciences. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAU021⟩. ⟨tel-02443212⟩

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