This study is focused on assessing the seismic resilience of two 42-story reinforced concrete dual system tall buildings designed by different methods. A systematic rating approach based on the United States Resiliency Council (USRC) Seismic Rating procedure is used as the resilience metric. The two buildings were developed as part of the Pacific Earthquake Engineering Research (PEER) Institute’s Tall Building Initiative (TBI) project. Both buildings were designed based on an assumed site location in Los Angeles, California. One variant was designed using prescriptive code provisions and the second using the Los Angeles Tall Building Structural Design Council (LATBSDC, 2008) Guidelines. The Seismic Performance Prediction Program (SP3) is used to perform the building rating analysis based on the FEMA P-58 methodology (FEMA, 2012). Ratings are established for the three categories of performance including safety, repair cost and functional recovery time. The results showed that both buildings achieve ratings of five and two stars for the safety and recovery dimensions respectively. However, for damage dimension, 2A gets a four stars rating while 2B has a five stars rating. At the design basis earthquake (DBE) level, the mean repair cost normalized by the building replacement value is 5.57% for the code-based building and 4.01% for the LATBSDC building. However, at the MCE level, the repair costs for the LATBSDC building (20%) is about 18% higher than that of the code-based building (17%). This result is explained by the fact that the residual drift demands are significantly higher in LATBSDC building and dominates the losses at the MCE level. For both buildings, the REDi recovery time is dominated by impeding factors which account for more than 75% of the functional recovery time.

Structures are generally under the risk of earthquake events, especially in regions with high seismicity. However, rather than occur individually, the seismic events are tend to happen in sequence of the mainshock and the multiple aftershocks, which would cause additional damage to the damaged buildings in post-mainshock environment and increase the probability of collapse. This study mainly focuses on characterizing the seismic risk of a 4-story steel frame under mainshock-aftershock earthquake sequences. The damage of the structure are captured using the maximum story drift ratio and the energy-based damage indices, of which the performances are evaluated and compared in prior. The result shows that the energy-based damage index has higher ability to capture the potential structural damage and tend to display higher rate of collapse in the lifetime of buildings.

Quantifying and propagating aleatory and epistemic uncertainty in nonlinear structural response simulation is key to robust performance-based seismic assessments. In this thesis, the focus is on the probabilistic seismic performance assessment of a non-ductile three-story reinforced concrete infilled frame building. The uncertainty in ground motion records and the uncertainty embedded in structural model parameters are explicitly considered. An equivalent strut model is used for the masonry infill walls, where the six constitutive parameters that define its backbone curve are treated as random variables. The variability in these parameters is characterized by developing correlated and uncorrelated distributions of the deduced-to-predicted ratios using data from 113 experimental tests. The uncertainties are propagated using Latin hypercube sampling to generate randomized structural model realizations. Multiple stripe analysis is performed with hazard-consistent ground motions. The effect of considering modeling uncertainty is investigated in terms of the distributions of maximum story drift ratios and drift based fragility functions. It is shown that the inclusion of modeling uncertainty has significant effects on the seismic performance of the case study building. The dispersion in the response and the mean annual frequency of exceeding the drift-based limit states are increased when modeling uncertainty is included. The initial stiffness of the infill walls is observed to have the most significant contribution to the performance of the building.

Controlled rocking steel braced frames (CRSBFs) have been developed with the goal of minimizing the post-earthquake impact of primary building functions. While there has been significant research to date to demonstrate the viability of the CRSBF as a high-performance system, much less has been accomplished in the development of performance-based design and assessment methods. This research is focused on developing models, tools and techniques for practicing engineers to analyze, design and assess the performance of CRSBFs. To avoid the computational expense of nonlinear response history analyses, an approximate method is formulated to estimate the CRSBF drift demands using the primary design parameters. Additionally, a reliability-based methodology for establishing the load and resistance factors for the force-controlled (braced frame) members is formulated. A key departure from previously developed capacity design approaches is the development of an explicit link between the effect of the failure of the force-controlled components and system level performance limit states (collapse and post-earthquake structural safety). The results from a case study applied to 3-, 6- and 9-story building cases show that the effect of force-controlled components is more significant for the collapse limit state compared to post-earthquake structural safety. Also, even when the resistance to load factor ratio (ϕ/γ) is increased to 1.8, the 50-year collapse probability remained below the 1% threshold prescribed by current building codes. The effect of record-to-record and modeling uncertainty on the seismic response and performance assessment of CRSBFs is also studied. The results showed that the impact of modeling uncertainty on seismic performance increases with the building height. To enable practitioners to estimate the service life costs of potential designs, surrogate models are developed to assess earthquake-induced life cycle economic loss and environmental impacts. The effectiveness of the surrogate models is demonstrated by evaluating their accuracy on “unseen” (i.e., not used in the development of the surrogate models) designs. 

Housing plays a primary role in post-earthquake recovery because all sectors of the economy rely on residents having healthy living conditions so that they will remain in the affected region. Therefore, understanding the time-dependent effects of earthquake events on housing is critical for improving post-earthquake trends through policy and planning interventions. This study develops an integrated framework for modeling post-earthquake housing recovery that combines probabilistic building performance with the decisions, actions and socioeconomic vulnerability of the affected populations. Building performance is characterized using limit states such as post-earthquake occupiability and repairability, which are explicitly linked to community functionality and recovery. Fragility functions are used to link the probability of exceeding these limit states to ground shaking intensities. Household decisions are modeled using empirical probabilistic utility models. Probabilistic discrete state models are implemented to represent post-earthquake recovery trajectories at the building, neighborhood and community scales. These models, which are inherently stochastic, can be purely empirical, such that the temporal parameters are sampled from an appropriate probability distribution. Alternatively, a simulation-based model can be employed to explicitly account for the effect of resource-availability on the time to complete relevant recovery activities. Socioeconomic vulnerability and other exogenous (external to household) and endogenous (external to household) factors are statistically linked to the temporal recovery parameters. The proposed model can be used to assist policy-makers, municipal governments and planners in understanding the possible interdependencies, interventions, and tradeoffs associated with post-earthquake housing recovery.

The increase in seismic activity after a large-magnitude earthquake coupled with the reduction in the lateral load-carrying capacity of the affected structures presents a significant human and financial risk to communities. The focus of this study is placed on formulating a framework for quantifying the impact of both the elevated post-mainshock seismic hazard as well as the mainshock-induced structural damage on building seismic performance. The viability of the proposed framework is examined through its application to mainshock-aftershock seismic performance evaluation of a set of reinforced concrete frames. Additionally, discrepancies between the frequency content of mainshock and aftershock ground motions and their impact on the seismic performance of RC moment frames is investigated. Two metrics are used in evaluating the seismic performance; seismic risk and seismic-induced financial losses. Both metrics are evaluated in both pre- and post-mainshock environments. The time-dependent nature of seismic hazard in the post-mainshock environment is accounted for through the adoption of a Markov risk assessment framework. In the post-mainshock environment, the seismic risk is examined as a function of the time elapsed since the mainshock’s occurrence while in the pre-mainshock environment, the risk is investigated during an assumed lifespan of 50 years for the studied structures. For the buildings and the high-seismicity site used in this study, both the increased post-mainshock seismic hazard as well as the reduction in the structural capacity are found to have a great influence on the seismic risk. The application of the proposed frameworks for seismic performance under mainshock-aftershock ground motions to the reinforced concrete frame buildings in Los Angeles County is also demonstrated. The outcomes of the regional seismic performance analysis show that omitting aftershocks from the seismic performance steps would lead to underestimating annual expected seismic risk and loss by up to 50% and 15%.

With the embrace of the seismic resilience concept as a measure of the ability of constructed facilities and communities to contain the effects of an earthquake and achieve a timely recovery, the critical role of tall buildings in supporting community functionality, has been brought to the forefront. This study presents a series of frameworks for performing post-earthquake assessment and optimal decision-making for tall buildings. A machine learning framework to assess structural safety is first proposed and applied to a low-rise frame building. A similar methodology is then adapted for tall buildings, while incorporating robust techniques to deal with the high-dimension feature space that arises because of the large number of structural components. Seismic risk assessment is then carried out for the tall building by comparing the time-dependent probability of exceeding various response demand limits over a pre-defined period considering both mainshock-only and mainshock-aftershock hazard. The risk-based consistency of the limit state acceptance criteria for engineering demand parameters is also examined. Finally, a methodology to support optimal decision-making following the mainshock is developed with the goal of minimizing expected financial losses and, at the same time, ensuring life safety. The proposed prediction model, risk assessment methodology and optimal decision-making strategy can provide critical insights into the seismic performance of mainshock-damaged tall buildings and inform the post-earthquake actions of occupants, structural engineers, insurance companies and policymakers.

Water distribution systems are vital to the well-being of communities because they contribute to the functionality of all other infrastructure and lifeline systems. Earthquakes and other natural hazards can cause damage to the components of a water distribution system, causing far-reaching socioeconomic consequences. This research begins with the development of an end-to-end simulation framework to model post-earthquake functional loss and restoration of a water system, which encompasses seismic hazard characterization, component damage assessment, hydraulic performance evaluation, and network restoration modeling. The modeling framework is validated using data from the 2014 South Napa Earthquake and extended to a hypothetical scenario. The end-to-end simulation framework is then extended to consider stochastic event set assessments of the water network using the UCERF2 (Uniform California Earthquake Rupture Forecast, Version 2) earthquake rupture forecast model. Given that the end-to-end performance evaluation of distributed infrastructure for a large set of events is computationally expensive, a framework that uses Active learning to select a subset of ground motion maps and associated occurrence rates that reasonably estimates the water network risk is also developed. To deal with the temporal complexities that are embedded in the post-earthquake restoration process, a dynamic updating methodology is developed to reduce uncertainties in the outcomes of post-event recovery forecasts using Bayesian Inferencing, by exploiting real-time data. The specific example of updating predictions (post-earthquake functional recovery forecasts including total recovery time and complete recovery trajectory) is presented and validated on a real pipe network (Napa water system) and event (2014 earthquake and recovery). Ultimately, the frameworks and models developed as part of this work can inform risk-based decision making and resilience planning of water networks and other lifeline systems.

A reinforced concrete frame with rocking spine system is evaluated using reliability-index method with main objective of establishing the load and resistance factors for the force-controlled components. A nonlinear structural model of a six-bay six-story concrete frame building with stiff infill panels idealized as compression only struts was constructed in OpenSees. Spine-infills, spine-beams, and spine-columns, are considered as force-controlled components, while non-spine infills and adjacent beams are considered as deformation-controlled components. The model is evaluated with 44 ground motions through Incremental Dynamic Analysis (IDA) to determine the demands in the force-controlled components. The model was also evaluated through response spectrum analysis to define the system’s yield modification factor, , which is used along with hazard curve to obtain the reliability index of the system, . The capacity,,and demand,factors are calculated by defining the probability of demand surpassing capacity in 50 years equal to 0.05%, 0.1%, 0.2%, 0.5%, and 1%. The results show that the decreases as and increases. The capacity and demand factors of spine-infill struts, spine-beams, and spine-columns for 0.1% P(D>C)50 years are: ;; ; respectively.