For earthquake-resistant design purposes, ground-motion intensity is usually characterized using response spectra. The amplitude of response spectral ordinates of horizontal components varies significantly with changes in orientation. This change in intensity with orientation is commonly known as ground-motion directionality. Although this directionality has been attributed to several factors, such as topographic irregularities, near-fault effects, and local geologic heterogeneities, the mechanism behind this phenomenon is still not well understood. This work studies the directionality characteristics of earthquake ground-motion intensity using synthetic ground motions and compares their directionality to that of recorded ground motions. The two principal components of horizontal acceleration are sampled independently using a stochastic model based on finite-duration time-modulated filtered Gaussian white-noise processes. By using the same stochastic process to sample both horizontal components of motion, the variance of horizontal ground acceleration has negligible orientation dependence. However, these simulations’ response spectral ordinates present directionality levels comparable to those found in real ground motions. It is shown that the directionality of the simulated ground motions changes for each realization of the stochastic process and is a consequence of the duration being finite. Simulated ground motions also present similar directionality trends to recorded earthquake ground motions, such as the increase of average directionality with increasing period of vibration and decrease with increasing significant duration. These results suggest that most of the orientation dependence of horizontal response spectra is primarily explained by the finite significant duration of earthquake ground motion causing inherent randomness in response spectra, rather than by some physical mechanism causing polarization of shaking.
After an earthquake, hospital emergency departments need to provide continuous health care services to respond to the eventual sudden increase in injured people. The service performance of an emergency department is influenced by internal factors, such as physical damage and staff availability, and external factors, such as an increased patient arrival rate and disruptions in its supply chain. This research presents a quantification methodology for the performance of the emergency department. The novelty of the proposed approach lies in the explicit integration of the inelastic structural and nonstructural response of the building and damage with its loss of functionality, downtime, and emergency patient treatment rate. A discrete event simulation model is used to model the flow of patients within the different units of the emergency department. The seismic risk is expressed as return periods of exceeding different levels of patient waiting times. Results show that 1,000 and 30,000 accumulated waiting hours correspond to return periods of 100 and 1,000 years, respectively. It is concluded that this model may contribute to improving the risk management of critical emergency department infrastructure.
Natural hazards may cause significant disruptions to road infrastructure, subsequently affecting road agencies, users, and productive activities. Despite the existence of infrastructure fragilities to seismic hazard and some operational consequences on network mobility, previous research has not modeled risk in terms of traffic disruptions and consequent travel time delays in subduction environments, analyzing the sensitivity to model parameters and quantified model uncertainty. This study proposes a risk framework to evaluate operational consequences in interurban road networks exposed to seismic hazard using travel time delays and propagate uncertainty in the model. Risk values are evaluated using Monte Carlo simulations, and uncertainty is propagated using a polynomial chaos expansion meta‐model. The framework was applied to a very critical interurban network in central Chile. Results demonstrate that the parameters that most significantly influence risk are fragility, loss of road capacity, and traffic volume.
Correlations between response spectral ordinates at different periods are used in several seismic hazard computations, such as for the construction of conditional mean spectra and conditional spectra. Conventionally, these correlations have been computed and reported only for a damping ratio of 5%; however, structures may have damping ratios substantially lower or higher than 5%. Therefore, in those cases, one requires correlations of spectral ordinates at different periods but having the same damping ratios that are different than 5%, correlations of spectral ordinates at the same period but having different damping ratios, or the general case of correlation between spectral ordinates of two oscillators having different damping ratios and different periods. This work computes such damping-dependent correlations by using the NGA-West2 ground motion database. In general, it is found that correlations increase as the damping ratio of any of the two spectral ordinates increases and as the ratio of periods of vibration of the two oscillators departs from one. A nonlinear regression model is fitted to the resulting damping-dependent correlations to simplify future computations. Finally, the use of the new damping-dependent correlations is illustrated by computing example conditional spectra for damping ratios differing from 5%. The results show that using 5%-damped correlations for the construction of condition mean spectra, overestimates spectral ordinates for damping ratios lower than 5% and underestimates spectral ordinates for damping ratios higher than 5%.
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