Henry V. Burton

Simulation of Seismic Collapse in Nonductile Reinforced Concrete Frame Buildings with Masonry Infills

AbstractImproved analysis methods and guidelines are presented to simulate the seismic collapse of nonductile concrete frame buildings with masonry infills. The analysis tools include an inelastic dual-strut model that captures the post-peak behavior of the masonry infill and its interaction with the surrounding frame. The dual compression struts capture the column-infill interaction that can cause shear failure of the columns and loss of their vertical load carrying capacity. A rigid softening shear degradation model is implemented in the beam-column elements to capture the shear failure of nonductile RC columns. Guidelines are presented to determine the strut model parameters based on data from 14 experimental tests on infill frames. The models are applied in three-dimensional nonlinear dynamic analyses of a three-story nonductile concrete frame prototype building with infills. The incremental dynamic analyses technique is utilized to understand the effect of the infill-column interaction and the rockin...

Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience

AbstractA framework is presented for incorporating probabilistic building performance limit states in the assessment of community resilience to earthquakes. The limit states are defined on the basis of their implications to postearthquake functionality and recovery. They include damage triggering inspection, occupiable damage with loss of functionality, unoccupiable damage, irreparable damage, and collapse. Fragility curves are developed linking earthquake ground motion intensity to the probability of exceedance for each of the limit states. A characteristic recovery path is defined for each limit state on the basis of discrete functioning states, the time spent within each state, and the level of functionality associated with each state. A building recovery function is computed accounting for the uncertainty in the occurrence of each recovery path and its associated limit state. The outcome is a probabilistic assessment of recovery of functionality at the building level for a given ground motion intensit...

Predicting the dissolution kinetics of silicate glasses using machine learning

Abstract Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, even for untrained data, thanks to its inherent ability to handle non-linear data. We further note that the predictive ability of simpler methods, such as linear regression, could be improved using additional physics-based constraints. Such methods, called as physics-informed machine learning can be used to extrapolate the behavior of untrained compositions as well. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties.

Rocking Spine for Enhanced Seismic Performance of Reinforced Concrete Frames with Infills

AbstractA rocking spine system is introduced as an alternative to more conventional approaches to improve the seismic collapse safety of concrete frames with masonry infills. Although infill frames are not formally recognized in ASCE 7 or other current U.S. building codes for new buildings, infills are present in many existing buildings, and infill frames are still a prevalent type of new construction that is permitted in many parts of the world. The proposed technique uses structural spines, constructed using either strong infill panels or concrete walls, to resist earthquake effects through controlled rocking action. The primary sources of overturning resistance are gravity loads on the spine and the restraint provided by beams and infill panels in framing bays adjacent to the spine. Equations are developed to describe the rocking response of the spine, relating the rigid-body kinematics to the internal deformations, forces and limit states in beams, columns, and infill panels. The main aspects of the d...

Integrating Performance Based Engineering and Urban Simulation to Model Post-Earthquake Housing Recovery

The efficacy of various types of intervention measures intended to facilitate post-earthquake housing recovery can be evaluated ahead of time by using simulation models to quantify their benefits and tradeoffs. Towards this end, this paper presents a conceptual framework comprised of three components for modeling post-earthquake housing recovery. The modeling framework starts with a probabilistic assessment of building-level damage using recovery-based limit states that characterize post-earthquake functionality, inhabitability, and repairability. These limit states are the basis for the second component, which includes two different utility-based models for representing post-earthquake household decision making. Stochastic models to probabilistically quantify building-level recovery trajectories comprise the third and final component of the framework. Collectively, these alternative models can integrate the effect of building states, available resources, household decisions, and endogenous factors such as lifeline restoration. The modeling framework can be scaled to model spatiotemporal scenarios of housing recovery to inform jurisdictional-level policies, plans, and interventions to increase residential community resilience.

Replicating the Recovery Following the 2014 South Napa Earthquake Using Stochastic Process Models

Post-earthquake recovery models can be used as decision support tools for pre-event planning. However, due to a lack of available data, there have been very few opportunities to validate and/or calibrate these models. This paper describes the use of building damage, permitting, and repair data from the 2014 South Napa Earthquake to evaluate a stochastic process post-earthquake recovery model. Damage data were obtained for 1,470 buildings, and permitting and repair time data were obtained for a subset (456) of those buildings. A “blind” prediction is shown to adequately capture the shape of the recovery trajectory despite overpredicting the overall pace of the recovery. Using the mean time to permit and repair time from the acquired data set significantly improves the accuracy of the recovery prediction. A generalized model is formulated by establishing statistical relationships between key time parameters and endogenous and exogenous factors that have been shown to influence the pace of recovery.

Response surface analysis and optimization of controlled rocking steel braced frames

As an alternative to conventional seismic force resisting systems, controlled rocking steel braced frames (CRSBFs) can effectively eliminate permanent structural damage after earthquakes. Together with the rocking action in the braced frame, post-tensioning (PT) elements and fuse members are used to provide self-centering and energy dissipation, respectively. This study firstly aims to assess the influence of design parameters related to the fuse and PT materials on the seismic response of CRSBFs. These factors include the yield strength, initial stiffness, and strain hardening ratio of the fuse, the initial force and modulus of elasticity of the PT strands, and the gravity load on the rocking column. Additionally, different analysis cases are considered to include the effects of frame aspect ratio and earthquake intensity level. Nonlinear response history analyses are performed with factor combinations generated using a design of experiment methodology. The second goal of the study is focused on optimizing the seismic response of CRSBFs with respect to the influential factors identified in the sensitivity analyses. Using a response surface methodology and desirability approach, multiple-response optimization is applied to determine the design variable values needed to simultaneously minimize the maximum transient and residual roof drift ratio and peak floor acceleration. Among other results, it is found that the fuse strain hardening ratio and PT strand modulus of elasticity do not significantly influence the seismic response demands in CRSBFs. The results of the multi-response optimization demonstrate that the initial PT force is most useful for minimizing all three seismic response demand parameters.