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For performance-based design, nonlinear dynamic structural analysis for various types of input ground motions is required. Stochastic (simulated) ground motions are sometimes useful as input motions, because unlike recorded motions they are not limited in number and because their properties can be varied systematically to study the impact of ground motion properties on structural response. This dissertation describes an approach by which the wavelet packet transform can be used to characterize complex time-varying earthquake ground motions, and it illustrates the potential benefits of such an approach in a variety of earthquake engineering applications. The proposed model is based on Thr´ainsson and Kiremidjian (2002), which use Fourier amplitudes and phase differences to simulate ground motions and attenuation models to their model parameters. We extend their model using wavelet packet transform since it can control the time and frequency characteristic of time series. The time- and frequency-varying properties of real ground motions can be captured using wavelet packets, so a model is developed that requires only 13 parameters to describe a given ground motion. These 13 parameters are then related to seismological variables such as earthquake magnitude, distance, and site condition, through regression analysis that captures trends in mean values, standard deviations and correlations of these parameters observed in a large database of recorded strong ground motions. The resulting regression equations then form a model that can be used to predict ground motions for a future earthquake scenario; this model is analogous to widely used empirical ground motion prediction models (formerly called "attenuation models") except that this model predicts entire time series rather than only response spectra. The ground motions produced using this predictive model are explored in detail, and are shown to have elastic response spectra, inelastic response spectra, durations, mean periods, etc., that are consistent in both mean and variability to existing published predictive models for those properties. That consistency allows the proposed model to be used in place of existing models for probabilistic seismic hazard analysis (PSHA) calculations. This new way to calculate PSHA is termed "simulation-based probabilistic seismic hazard analysis" and it allows a deeper understanding of ground motion hazard and hazard deaggregation than is possible with traditional PSHA because it produces a suite of potential ground motion time histories rather than simply a distribution of response spectra. The potential benefits of this approach are demonstrated and explored in detail. Taking this analysis even further, this suite of time histories can be used as input for nonlinear dynamic analysis of structures, to perform a risk analysis (i.e., "probabilistic seismic demand analysis") that allows computation of the probability of the structure exceeding some level of response in a future earthquake. These risk calculations are often performed today using small sets of scaled recorded ground motions, but that approach requires a variety of assumptions regarding important properties of ground motions, the impacts of ground motion scaling, etc. The approach proposed here facilitates examination of those assumptions, and provides a variety of other relevant information not obtainable by that traditional approach.
For performance-based design, nonlinear dynamic structural analysis for various types of input ground motions is required. Stochastic (simulated) ground motions are sometimes useful as input motions, because unlike recorded motions they are not limited in number and because their properties can be varied systematically to study the impact of ground motion properties on structural response. This dissertation describes an approach by which the wavelet packet transform can be used to characterize complex time-varying earthquake ground motions, and it illustrates the potential benefits of such an approach in a variety of earthquake engineering applications. The proposed model is based on Thráinsson and Kiremidjian (2002), which use Fourier amplitudes and phase differences to simulate ground motions and attenuation models to their model parameters. We extend their model using wavelet packet transform since it can control the time and frequency characteristic of time series. The time- and frequency-varying properties of real ground motions can be captured using wavelet packets, so a model is developed that requires only 13 parameters to describe a given ground motion. These 13 parameters are then related to seismological variables such as earthquake magnitude, distance, and site condition, through regression analysis that captures trends in mean values, standard deviations and correlations of these parameters observed in a large database of recorded strong ground motions. The resulting regression equations then form a model that can be used to predict ground motions for a future earthquake scenario; this model is analogous to widely used empirical ground motion prediction models (formerly called "attenuation models") except that this model predicts entire time series rather than only response spectra. The ground motions produced using this predictive model are explored in detail, and are shown to have elastic response spectra, inelastic response spectra, durations, mean periods, etc., that are consistent in both mean and variability to existing published predictive models for those properties. That consistency allows the proposed model to be used in place of existing models for probabilistic seismic hazard analysis (PSHA) calculations. This new way to calculate PSHA is termed "simulation-based probabilistic seismic hazard analysis" and it allows a deeper understanding of ground motion hazard and hazard deaggregation than is possible with traditional PSHA because it produces a suite of potential ground motion time histories rather than simply a distribution of response spectra. The potential benefits of this approach are demonstrated and explored in detail. Taking this analysis even further, this suite of time histories can be used as input for nonlinear dynamic analysis of structures, to perform a risk analysis (i.e., "probabilistic seismic demand analysis") that allows computation of the probability of the structure exceeding some level of response in a future earthquake. These risk calculations are often performed today using small sets of scaled recorded ground motions, but that approach requires a variety of assumptions regarding important properties of ground motions, the impacts of ground motion scaling, etc. The approach proposed here facilitates examination of those assumptions, and provides a variety of other relevant information not obtainable by that traditional approach.
Physics-based earthquake simulations, which predict the ground-motions generated by scenario earthquakes, have the potential to be extremely useful in dynamic analyses of structures because they can be generated for scenarios not well represented in the empirical data set such as M8 earthquakes and for site/source-specific rupture geometries. But before simulations are accepted for engineering applications, they first need be validated against recorded data and empirical models. Recent efforts have made significant progress towards validation by considering the median predictions of simulations (e.g. Goulet et al., 2015), but further work is still required in order to validate other critical ground-motion properties. This dissertation develops the framework for validation of one important parameter: the inter-period correlation of [epsilon] of ground-motions. The purpose of this research is three-fold: (1) to illustrate that the inter-period correlation of [epsilon] ([rho][subscript epsilon]) is a critical feature of ground motions that influences variability of structural response and which should be considered as a validation parameter, (2) to develop an avenue for improving the correlation in the simulations, and (3) to provide an example application which can help guide future calibrations. To achieve these goals, an empirical ground-motion model (GMM) is developed for smoothed Fourier amplitude spectra (FAS), and the residuals from this model are used to develop a model for the [rho][subscript epsilon] of the FAS. The FAS is used because it is a more direct representation of the frequency content of the ground motions than response spectra and is better understood by seismologists. Using simple ground-motion simulations based on the point-source stochastic method, the importance of the [rho][subscript epsilon] of FAS in capturing the variability of structural response is demonstrated. Results show that without the adequate [rho][subscript epsilon] of FAS in the simulations, variability in the structural response may be under-estimated. This leads to structural fragilities which are too steep (under-estimated dispersion parameter [beta]) and to non-conservative estimates of seismic risk. To commence the validation process, [rho][subscript epsilon] of the smoothed FAS of several established ground-motion simulation methods are compared with the [rho][subscript epsilon] observed in data. None of the six finite-fault simulation methods tested adequately capture the [rho][subscript epsilon] over the entire frequency range evaluated, although several of the methods show promise, especially at low frequencies. The validation is performed for the FAS because this information provides the developers of the simulation methods better feedback in terms of how they can modify their methods that is not clear when using response spectra comparisons. Finally, the calibration of [rho][subscript epsilon] for one simulation method, EXSIM (Aktinson and Assatourians, 2014) is demonstrated and tested. Recommendations are provided for future [rho][subscript epsilon] calibration efforts.
Data used to develop and confirm models suffer from several shortcomings: the total data is too limited, the data are non-stationary, and the data represent nonlinear processes. The Hilbert-Huang transform (HHT) is a relatively new method that has grown into a robust tool for data analysis and is ready for a wide variety of applications. Thi
Structural Analysis of Historical Constructions contains about 160 papers that were presented at the IV International Seminar on Structural Analysis of Historical Constructions that was held from 10 to 13 November, 2004 in Padova Italy. Following publications of previous seminars that were organized in Barcelona, Spain (1995 and 1998) and Guimarães, Portugal (2001), state-of-the-art information is presented in these two volumes on the preservation, protection, and restoration of historical constructions, both comprising monumental structures and complete city centers. These two proceedings volumes are devoted to the possibilities of numerical and experimental techniques in the maintenance of historical structures. In this respect, the papers, originating from over 30 countries, are subdivided in the following areas: Historical aspects and general methodology, Materials and laboratory testing, Non-destructive testing and inspection techniques, Dynamic behavior and structural monitoring, Analytical and numerical approaches, Consolidation and strengthening techniques, Historical timber and metal structures, Seismic analysis and vulnerability assessment, Seismic strengthening and innovative systems, Case studies. Structural Analysis of Historical Constructions is a valuable source of information for scientists and practitioners working on structure-related issues of historical constructions