Utilization of physics-based simulated earthquake ground motions for performance assessment of tall buildings

Databases of recorded motion are limited despite the increasing amount of data collected through strong motion instrumentation programs. Particular lack of data exists for large magnitude events and at close distances as well as on earthquakes in deep sedimentary basins. Additionally, databases of recorded motions are also limited in representation of energy at long periods due to the useable frequencies of recording instruments. This lack of data is currently partially addressed through assumption of ergodicity in development of empirical ground motion prediction equations (GMPEs). Nevertheless, challenges remain for calibration of empirical GMPEs as used in conventional approaches for probabilistic estimation of seismic hazard. At the same time, limited data on strong earthquakes and their effect on structures poses challenges for making reliable risk assessments particularly for tall buildings. For instance, while the collapse safety of tall buildings is likely controlled by large magnitude earthquakes with long du- rations and high long-period content, there are few available recorded ground motions to evaluate these issues. The influence of geologic basins on amplifying ground motion effects raises additional questions. Absent recorded motions from past large magnitude earthquakes, physics-based ground motion simulations provide a viable alternative due to the ability to consider extreme ground motions while being inherently site-specific and explicitly considering instances not well constrained by limited empirical data. This thesis focuses on utilization of physics-based simulated earthquake ground motions for performance assessment of tall buildings with three main goals: (1) developing confidence in the use of simulated ground motions through comparative assessments of recorded and simulated motions; (2) identifying important characteristics of extreme ground motions for col- lapse safety of tall buildings; (3) exploring areas where simulated ground motions provide significant advantages over recorded motions for performance-based engineering. To gain confidence in the use of simulated motions for full performance assessment of tall buildings, a 'similar intensity measure' validation study was performed. Structural responses to ground motions simulated with different methods on the Southern California Earthquake Center (SCEC) Broadband Platform (BBP) are contrasted to recorded motions from PEER NGA database with similar spectral shape and significant durations. Two tall buildings, a 20-story concrete frame and a 42-story concrete core wall building, are analyzed at increasing levels of ground motion intensity, up to structural collapse, to check for statistically significant differences between the responses to simulated and recorded motions. Considered demands include story drift ratios, floor accelerations and collapse response. These comparisons yield similar results in most cases but also reveal instances where certain simulated ground motions can result in biased responses. The source of bias is traced to differences in correlations of spectral values in some of the stochastic ground motion simulations. When the differences in correlations are removed, simulated and recorded motions yield comparable results. Moving beyond validation, the thesis also explored areas where the use of simulated motions provides advantages over approaches based on limited databases of recorded motions for performance-based engineering. One such area is seismic risk in deep sedimentary basins which is studied by examining collapse risk and drift demands of a 20-story archetype tall building utilizing ground motions at four sites in the Los Angeles basin. Seismic demands of the building are calculated form nonlinear structural analyses using large datasets (~500,000 ground motions per site) of unscaled, site-specific simulated seismograms. Seismic hazard and building performance from direct analysis of SCEC CyberShake motions are contrasted with values obtained based on 'conventional' approaches that rely on recorded motions coupled with probabilistic seismic hazard assessments. The analysis shows that, depending on the location of the site within the basin, the two approaches can yield drastically different results. For instance, at a deep basin site the CyberShake-based analysis yields around seven times larger mean annual frequency of collapse ( c) and significantly higher drift demands (e.g. drift demand of 1% is exceeded around three times more frequently) compared to the conventional approach. Both the hazard as well as the spectral shapes of the motions are shown to drive the differences in responses. Deaggregation of collapse risk is performed to identify the relative contributions of earthquake fault ruptures, linking building responses with specific seismograms and contrasting collapse risk with hazard. The effect of earthquake ground motions in deep sedimentary basins on structural collapse risk is further studied through the use of CyberShake earthquake simulations in the Los Angeles basin. Distinctive waveform characteristics of deep basin seismograms are used to classify the ground motions into several archetype groups, and the damaging influence of the basin effects are evaluated by comparing nonlinear structural responses under comparable basin and non-basin ground motions. The deep basin ground motions are observed to have larger durations and spectral intensities than non-basin motions for vibration periods longer than about 1.5 seconds, which can increase the relative structural collapse risk by up to 20 percent between ground motions with otherwise comparable spectral accelerations and significant durations. Two new metrics, termed sustained amplitude response spectra (RSx spectra) and significant duration spectra (Da spectra), are proposed to quantify period-dependent duration effects that are not otherwise captured by conventional ground motion intensity measures. The proposed sustained amplitude response spectra and significant duration spectra show promise for characterizing the damaging effects of long duration features of basin ground motions on buildings and other structures. The large database of CyberShake simulations is utilized to re-examine the relationships between engineering demand parameters and input ground motions on structural response. Focusing on collapse response, machine learning techniques are applied to results of about two million nonlinear time history analyses of an archetype 20-story tall building performed using CyberShake ground motions. The resulting feature selection (based on regularized logistic regression) generally confirms existing understanding of collapse predictors as gained from scaled recorded motions but also reveals the benefit of some novel intensity measures (IMs), in particular the RSx spectral features. In addition, the statistical interrogations of the large collection of hazard-consistent simulations demonstrate the utility of different IMs for collapse predictions in a way that is not possible with recorded motions. A small subset of robust IMs is identified and used in development of an efficient collapse classification algorithm, which is tested on benchmark results from other CyberShake sites. The classification algorithm yields promising results for application to regional risk assessment of building performance.

Advisor: Deierlein Gregory G. (Gregory Gerard)
Baker Jack W. 
Lin Ting