Characterization of Seismic Responses in Mexico City Using Hilbert-Huang Transform

In this investigation, we present the Hilbert-Huang transform (HHT) as an alternative technique, which has advantage over other methods for extracting useful data of seismic ground response. The HHT, integrated with the empirical mode decomposition (EMD) and the Hilbert transformation (HT), enables engineers to analyze data from nonlinear and nonstationary processes. The product of the transformation is a detailed description of time-varying frequency diagrams. The recordings of accelerations of soft-soil deposits in Mexico City are studied under this technique. Results of the analysis of accelerograms indicate that this adaptive decomposition permits the extraction motion characteristics, which cannot be effectively unraveled by other conventional data processing techniques. The findings and conclusions derived from studies such as the one presented here contribute to a better understanding of seismic response patterns

Neural estimation of strong ground motion duration

AbstractThis paper presents and discusses the use of neural networks to determine strong ground motion duration. Accelerometric data recorded in the Mexican cities of Puebla and Oaxaca are used to develop a neural model that predicts this duration in terms of the magnitude, epicenter distance, focal depth, soil characterization and azimuth. According to the above the neural model considers the effect of the seismogenic zone and the contribution of soil type to the duration of strong ground motion. The final scheme permits a direct estimation of the duration since it requires easy-to-obtain variables and does not have restrictive hypothesis. The results presented in this paper indicate that the soft computing alternative, via the neural model, is a reliable recording-based approach to explore and to quantify the effect of seismic and site conditions on duration estimation. An essential and significant aspect of this new model is that, while being extremely simple, it also provides estimates of strong ground motions duration with remarkable accuracy. Additional but important side benefits arising from the model’s simplicity are the natural separation of source, path, and site effects and the accompanying computational efficiency

Subsoil classification and geotechnical zonation for Guadalajara City, México: Vs30, soil fundamental periods, 3D structure and profiles

Guadalajara, Jalisco, is the second largest city in Mexico with around 4.5 million inhabitants. A high seismic hazard exists in the city due to forces produced by the interaction between the Rivera, Cocos and North American plates and the smaller Jalisco Block. Guadalajara is one of the largest cities built over pumice soil deposits. Furthermore, the near‐surface phreatic level causes a high susceptibility to liquefaction. All these features can cause extreme earthquake site effects. Due to the fragile inner structure of pumice sands, traditional geotechnical tests are inappropriate to characterize the seismic response. Therefore, we propose the use of surface wave analysis methods (multichannel analysis of surface waves and refraction microtremor), which we applied in 33 sites to define the soil classification in terms of VS30 (the average shear wave velocity between the surface and 30 m depth), the bedrock depth and the fundamental period. From the soil classification, we construct a microzonation map consisting of four geotechnical zones, which we superimpose on the known construction systems within the city. The comparison between the construction period of the buildings and the fundamental frequencies of the soil indicates a high vulnerability to resonance in 1‐ to 4‐storied old buildings constructed of adobe and unreinforced masonry within zones II and III, followed by a medium vulnerability to seismic resonance in compact buildings of 1–4 stories within zone I and 1–12 stories within zones II and IV.TU Berlin, Open-Access-Mittel – 202