Browsing by Author "Castro, Sebastián"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    A Consistently Processed Strong-Motion Database for Chilean Earthquakes
    (Seismological Society of America, 2022) Castro, Sebastián; Benavente, Roberto; Crempien de la Carrera, Jorge; Candia, Gabriel; Llera Martin, Juan Carlos de la
    © Seismological Society of America.Since the 1985 M 8.0 central Chile earthquake, national strong-motion seismic networks have recorded ten megathrust earthquakes with magnitudes greater than M 7.5 at the convergent margin, defined by the contact between the Nazca and South American plates. The analysis of these earthquake records have led to improved hazard analyses and design codes for conventional and seismically protected structures. Although strong-motion baseline correction is required for a meaningful interpretation of these records, correction methods have not been applied consistently in time. The inconsistencies between correction methods have been neglected in the practical use of these records in practice. Consequently, this work aims to provide a new strong-motion database for researchers and engineers, which has been processed by traceable and consistent data processing techniques. The record database comes from three uncorrected strong motion Chilean databases. All the records are corrected using a four-step novel methodology, which detects the P-wave arrival and introduces a baseline correction based on the reversible-jump Markov chain Monte Carlo method. The resulting strong motion database has more than 2000 events from 1985 to the date, and it is available to download at the Simulation Based Earthquake Risk and Resilience of Interdependent Systems and Networks (SIBER-RISK) project website.
  • No Thumbnail Available
    Item
    Conjunto de datos: SIBER-RISK Strong Motion Database
    (Datos de Investigación UC, ) Castro, Sebastián; Benavente, Roberto; Crempien de la Carrera, Jorge; Candia, Gabriel; Llera Martin, Juan Carlos de la
  • Thumbnail Image
    Item
    Evaluating network reduction strategies for consistent risk assessment of critical infrastructures
    (2020) Llera Martin, Juan Carlos de la; Monsalve M., Mauricio; Ferrario, Elisa; Alberto, Yolanda; Arróspide, Felipe; Castro, Sebastián; Poulos, Alan
    Critical infrastructure networks are continuously growing, gaining complexity with each urban sprawl, conurbation, technological change, and regulatory update. Consequently, their detailed risk analysis demands large amounts of data, computational resources (required by simulations, optimization, flow equilibria, etc.), and dealing with complex interpretations of the results. This comes with several drawbacks: scarcity of adequately curated data, which instead are usually incomplete and sometimes even incorrect, algorithmic runtime that impairs the full use of Monte Carlo simulations, errors that may propagate extensively, and results that cannot be generalized and extended to other cases. Therefore, researchers have also resorted to analyzing simplified versions of these infrastructure systems. This work evaluates three algorithms for reducing the complexity of infrastructure networks while keeping reasonable accuracy for statistical interpretation. These algorithms transform a detailed graph into a more compact representation, where risk assessments can be performed more easily. The strategies used herein are based on the detection of important edges (backbone detection) and the merging or lumping similar or proximate elements (clustering, contractions). The different complexity reduction algorithms are evaluated on three infrastructure networks, namely: the electric transmission network of Chile, the electric distribution network of the Greater Valparaíso and the drinking water distribution network of the Greater Valparaíso. The experiments show that two of the three graph reduction criteria proposed in this work yield good approximations of the connectivity of the original graphs, when these are reduced to 25% of their size.
  • Thumbnail Image
    Item
    Uncertainty quantification of 2 models of cardiac electromechanics
    (2017) Hurtado Sepúlveda, Daniel; Castro, Sebastián; Madrid, Pedro