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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This report presents the observations and findings following the 2017 Puebla earthquake that occurred inMexico on September 19th, 2017. The reconnaissance mission was a collaboration between the New ZealandSociety of Earthquake Engineering (NZSEE), the Universidad Autónoma Metropolitana (UAM) Azcapotzalco,the American Concrete Institute (ACI) Disaster Reconnaissance team, and the Colegio de Ingenieros Civilesde Mexico (CICM). During the earthquake, 77 buildings suffered partial or total collapse and more than8,000 buildings experienced damage ranging from slight damage to significant structural damage necessitatingdemolition. As observed in previous earthquakes, the unique soil conditions of Mexico City resulted inextensive damage to the city’s infrastructure, primarily due to local site effects. The earthquake causedrelatively more damage to buildings built on transition and soft soil zones (i.e. between hard and deep softsoils) than those on hard soils.The NZSEE and UAM team focussed on areas with widespread and extensive damage. They also assessedthe performance of repaired and retrofitted buildings after the 1985 Michoacán earthquake. It was found thatthe lessons learnt from the 1985 Michoacán earthquake led to some risk mitigation measures which benefitedseveral buildings in the 2017 earthquake. Retrofitted buildings were found to have performed very well withlittle or no damage when compared to other buildings.

This paper discusses the experimental results of a prototype slab-wall that is subjected to vertical and horizontal cyclic loading. The key aspects under discussion are: (a) the differences between the capacity resistance of a wall supported on a slab vs. a wall supported on a fixed base, (b) the implications when shear walls are placed directly on transfer concrete slabs, and (c) the effects that these walls cause on the slabs. The most important results presented herein are the change on lateral stiffness and resistance capacity of the load-bearing wall supported on a slab versus the wall supported on a fixed base. Analytical finite element slab-wall models were built using ANSYS. During the experimental test process of horizontal loading, we detected that the stiffness of the slab-wall system decreased by a third compared to the one on the fixed base wall; a result that supported by the numerical models.

This article presents a seismic vulnerability and risk assessment of buildings in Mexico City. A probabilistic seismic hazard analysis (PSHA) was carried out, which allowed the definition of seismic hazard curves as well as uniform hazard spectra (UHS) for several seismic zones. The seismic hazard includes the effects of all seismic sources located in an influence area with a radius of 500 km. Attenuation relationships were selected with basis in attenuation models of events affecting the areas of Central Mexico and were complemented by our own functions that include local soil effects. Already established the sources and attenuation functions, the seismic hazard is quantified throughout UHS, which calculated using a return period Tr = 100 years. For the vulnerability assessment, fragility curves were defined. Two groups of fragility curves were studied, the first for the first for buildings built before 1985, and the second for buildings built after 1985. In the first case, static nonlinear analyzes of selected buildings were performed to define the capacity spectra. In the second case, the capacity spectra were defined from design spectra of the Mexico City Building Code. The results showed a very good correlation with the seismic demands of the 2017 earthquake.