Bayesian Methods for Intensity Measure and Ground Motion Selection in Performance-Based Earthquake Engineering
Dhulipala, Lakshmi Narasimha Somayajulu
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The objective of quantitative Performance-Based Earthquake Engineering (PBEE) is designing buildings that meet the specified performance objectives when subjected to an earthquake. One challenge to completely relying upon a PBEE approach in design practice is the open-ended nature of characterizing the earthquake ground motion by selecting appropriate ground motions and Intensity Measures (IM) for seismic analysis. This open-ended nature changes the quantified building performance depending upon the ground motions and IMs selected. So, improper ground motion and IM selection can lead to errors in structural performance prediction and thus to poor designs. Hence, the goal of this dissertation is to propose methods and tools that enable an informed selection of earthquake IMs and ground motions, with the broader goal of contributing toward a robust PBEE analysis. In doing so, the change of perspective and the mechanism to incorporate additional information provided by Bayesian methods will be utilized. Evaluation of the ability of IMs towards predicting the response of a building with precision and accuracy for a future, unknown earthquake is a fundamental problem in PBEE analysis. Whereas current methods for IM quality assessment are subjective and have multiple criteria (hence making IM selection challenging), a unified method is proposed that enables rating the numerous IMs. This is done by proposing the first quantitative metric for assessing IM accuracy in predicting the building response to a future earthquake, and then by investigating the relationship between precision and accuracy. This unified metric is further expected to provide a pathway toward improving PBEE analysis by allowing the consideration of multiple IMs. Similar to IM selection, ground motion selection is important for PBEE analysis. Consensus on the "right" input motions for conducting seismic response analyses is often varied and dependent on the analyst. Hence, a general and flexible tool is proposed to aid ground motion selection. General here means the tool encompasses several structural types by considering their sensitivities to different ground motion characteristics. Flexible here means the tool can consider additional information about the earthquake process when available with the analyst. Additionally, in support of this ground motion selection tool, a simplified method for seismic hazard analysis for a vector of IMs is developed. This dissertation addresses four critical issues in IM and ground motion selection for PBEE by proposing: (1) a simplified method for performing vector hazard analysis given multiple IMs; (2) a Bayesian framework to aid ground motion selection which is flexible and general to incorporate preferences of the analyst; (3) a unified metric to aid IM quality assessment for seismic fragility and demand hazard assessment; (4) Bayesian models for capturing heteroscedasticity (non-constant standard deviation) in seismic response analyses which may further influence IM selection.
General Audience Abstract
Earthquake ground shaking is a complex phenomenon since there is no unique way to assess its strength. Yet, the strength of ground motion (shaking) becomes an integral part for predicting the future earthquake performance of buildings using the Performance-Based Earthquake Engineering (PBEE) framework. The PBEE framework predicts building performance in terms of expected financial losses, possible downtime, the potential of the building to collapse under a future earthquake. Much prior research has shown that the predictions made by the PBEE framework are heavily dependent upon how the strength of a future earthquake ground motion is characterized. This dependency leads to uncertainty in the predicted building performance and hence its seismic design. The goal of this dissertation therefore is to employ Bayesian reasoning, which takes into account the alternative explanations or perspectives of a research problem, and propose robust quantitative methods that aid IM selection and ground motion selection in PBEE The fact that the local intensity of an earthquake can be characterized in multiple ways using Intensity Measures (IM; e.g., peak ground acceleration) is problematic for PBEE because it leads to different PBEE results for different choices of the IM. While formal procedures for selecting an optimal IM exist, they may be considered as being subjective and have multiple criteria making their use difficult and inconclusive. Bayes rule provides a mechanism called change of perspective using which a problem that is difficult to solve from one perspective could be tackled from a different perspective. This change of perspective mechanism is used to propose a quantitative, unified metric for rating alternative IMs. The immediate application of this metric is aiding the selection of the best IM that would predict the building earthquake performance with least bias. Structural analysis for performance assessment in PBEE is conducted by selecting ground motions which match a target response spectrum (a representation of future ground motions). The definition of a target response spectrum lacks general consensus and is dependent on the analysts’ preferences. To encompass all these preferences and requirements of analysts, a Bayesian target response spectrum which is general and flexible is proposed. While the generality of this Bayesian target response spectrum allow analysts select those ground motions to which their structures are the most sensitive, its flexibility permits the incorporation of additional information (preferences) into the target response spectrum development. This dissertation addresses four critical questions in PBEE: (1) how can we best define ground motion at a site?; (2) if ground motion can only be defined by multiple metrics, how can we easily derive the probability of such shaking at a site?; (3) how do we use these multiple metrics to select a set of ground motion records that best capture the site’s unique seismicity; (4) when those records are used to analyze the response of a structure, how can we be sure that a standard linear regression technique accurately captures the uncertainty in structural response at low and high levels of shaking?
- Doctoral Dissertations