This paper presents the results of an experimental investigation on the rocking behavior of rigid blocks. Two types of test specimens have been tested, namely M and C types. Nine blocks of the M type and two blocks of the C type with different aspect ratios were tested with varying initial rotational amplitudes and with different materials at the contact interface, namely concrete, timber, steel, and rubber. The results showed that the interface material has significant influence on the free rocking performance of the blocks. Blocks tested on rubber had the fastest energy dissipation followed by concrete and timber bases, respectively. Analysis of the test results has shown that the energy dissipation in the case of tests on a rubber base is a continuous mechanism whereas in the case of tests on rigid bases, i.e. timber and concrete, energy dissipation is a discrete function. Finally, the rocking characteristics of the blocks were calculated using piecewise equations of motion and numerical analysis. It was possible to predict the correct free rocking amplitude response when a reliable value for the coefficient of restitution was used.the piecewise equations of motions [3]. Pena et al. [6] used complex coupled rocking rotations and discrete element methods to predict the rocking response of four specimens. Both methods are extremely sensitive to the rocking parameters. Finally, it was found that repeatability of the rocking tests under random vibration does not exist.Shenton and Jones [7] showed that under horizontal ground excitation a rigid block has five modes of response namely rest, rocking, sliding, rocking-sliding, and free-flight. Shenton [8] analytically derived the criteria that govern the initiation of these modes in the static frictionpeak ground acceleration parameter space. Oliveto et al. [9] derived analytical expressions for the minimum acceleration impulses for uplift and overturning. They showed that the minimum overturning impulse of a flexible system is always smaller than the corresponding impulse for the rigid system. Taniguchi [10] showed that the effect of the vertical ground acceleration component on the response criteria is extremely important and went on to derive the criteria for initiation of rocking, sliding, and rocking-sliding.The rocking problem is stiff and highly nonlinear in nature, resulting in a variety of rocking responses even for relatively simple harmonic excitation. For an undamped rocking system, Jeong et al. [11] found that quasi periodic and chaotic motions dominated the response. For a damped rocking system, Wong and Tso [12] showed that out-of-phase harmonic and sub-harmonic responses can be stable, and that all in-phase steady-state rocking responses were unstable. When in-phase periodic vertical acceleration was added to a horizontal periodic excitation, the response changed to quasi periodic and chaotic [11]. The stability regions of harmonic/sub-harmonic responses as well as possible chaotic responses were determined using a discrete mapping technique by Hogan ...
This paper presents the results of free vibration and earthquake excitation tests to investigate the dynamic behaviour of freely rocking flexible structures with different geometric and vibration characteristics. The primary objective of these tests was to identify the complex interaction of elasticity and rocking and discuss its salient effects on the rocking and vibration mode frequencies, shapes and excitation mechanisms. The variability of response is discussed, including critical investigation of the repeatability of the tests. It was found that the variability in energy dissipation and energy transfer to vibrations at impact may lead to significantly different responses to almost identical excitations.
Six buildings in the Wellington region and the upper South Island, instrumented as part of the GeoNet Building Instrumentation Programme, recorded strong motion data during the 2016 Kaikoura earthquake. The response of two of these buildings: the Bank of New Zealand (BNZ) Harbour Quays, and Ministry of Business, Innovation, and Employment (MBIE) buildings, are examined in detail. Their acceleration and displacement response was reconstructed from the recorded data, and their vibrational characteristics were examined by computing their frequency response functions. The location of the BNZ building in the CentrePort region on the Wellington waterfront, which experienced significant ground motion amplification in the 1–2 s period range due to site effects, resulted in the imposition of especially large demands on the building. The computed response of the two buildings are compared to the intensity of ground motions they experienced and the structural and nonstructural damage they suffered, in an effort to motivate the use of structural response data in the validation of performance objectives of building codes, structural modelling techniques, and fragility functions. Finally, the nature of challenges typically encountered in the interpretation of structural response data are highlighted.
The 2017 Puebla, Mexico, earthquake event led to significant damage in many buildings in Mexico City. In the months following the earthquake, civil engineering students conducted detailed building assessments throughout the city. They collected building damage information and structural characteristics for 340 buildings in the Mexico City urban area, with an emphasis on the Roma and Condesa neighborhoods where they assessed 237 buildings. These neighborhoods are of particular interest due to the availability of seismic records captured by nearby recording stations, and preexisting information from when the neighborhoods were affected by the 1985 Michoacán earthquake. This article presents a case study on developing a damage prediction model using machine learning. It details a framework suitable for working with future post-earthquake observation data. Four algorithms able to perform classification tasks were trialed. Random forest, the best performing algorithm, achieves more than 65% prediction accuracy. The study of the feature importance for the random forest shows that the building location, seismic demand, and building height are the parameters that influence the model output the most.
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