Session Overview
Presented By: Mervyn Kowalsky
Affiliation: North Carolina State University
Description: The session moderators will introduce the session and define learning objectives and plans for interaction.
How do We Define Displacement Capacity of RC Bridge Columns, and do We Know How to Calculate it?
Presented By: Fabiola Claure
Affiliation: North Carolina State University
Description: The prediction of the displacement capacity of RC members requires criteria for defining the conditions by which the capacity is reached. In this presentation, displacement capacity is redefined as a limit state displacement. Limit states may be based on material strains or sectional resistance limits, for example a 20% loss of strength. This presentation will discuss simple methods for calculating the displacement capacity of bridge columns based upon flexure, shear, and stability limits, including the discussion of recent shake table tests to collapse which suggest that the stability limits proposed in multiple codes may need further study.
Drift Capacity of Retrofitted Reinforced Concrete Columns
Presented By: Julian Rincon
Affiliation: University of Canterbury
Description: Estimating the drift capacity of reinforced concrete (RC) columns remains a challenging task in earthquake engineering. Over the past decades, numerous empirical models have been developed to estimate the drift capacity of RC columns under cyclic loading. Nevertheless, comparisons with experimental data often show that these models fail to accurately capture observed drift capacities. The complexity increases further for retrofitted columns, where available experimental data are limited. This presentation addresses the challenges of estimating drift capacity in retrofitted RC columns and evaluates the performance of various methods against a database of experimental results for retrofitted columns.
Quantifying the Impact of Construction and Demand Variability on Seismic Performance Limit States in RC Bridge Columns
Presented By: Ana Paula Bona Barros Medeiros
Affiliation: North Carolina State University
Description: In the aftermath of a potentially damaging earthquake, it is crucial to rapidly and accurately assess the seismic performance of critical infrastructure, in order to support emergency response and minimize potential losses. Bridges, in particular, play a vital role as post-earthquake lifelines, and their structural elements—such as reinforced concrete columns—must be evaluated through well-defined performance limit states to ensure reliable and informed decision-making. These limit states are best defined using engineering demand parameters that serve as effective measures of deformation, such as steel and concrete strains, which capture material-level behavior with high precision. Based on this, empirical expressions were developed to represent performance limit states in terms of strain values. This study adopts a deterministic approach to investigate the variability of these limit states in RC circular columns by varying five design parameters, including material properties and detailing aspects such as transverse reinforcement spacing. Each parameter was assigned lower and upper bounds to reflect realistic variations that may occur due to construction practices, such as differences in spiral spacing, or natural variability in material properties. The analysis also considers a multi-column pier configuration, where overturning moments can modify the magnitude of axial load on the columns, further influencing their seismic response. Moment-curvature and force-displacement relationships were developed for each combination of parameters, producing a dataset of deterministic outcomes. These resulting displacements were then used to construct cumulative distribution functions, allowing a probabilistic characterization of each performance limit state under different construction and demand conditions. This analyses results enhance the clarity and practical use of performance limit states in a post-earthquake scenarios, where rapid and reliable assessment is essential.
Estimating the Drift Capacity of RC Columns using Machine Learning
Presented By: Liam Pledger
Affiliation: University of Canterbury
Description: An accurate estimate of the drift capacity of structures is critical for both the design and assessment of structures. Drift capacity is often used to quantify the seismic vulnerability of structures. An open-source machine learning (ML) model has been developed to estimate the drift capacity of reinforced concrete (RC) columns. The accuracy of the new method is compared against that of existing methods using test results from a dataset of 341RC columns subjected to cyclic loading. The mean of the ratio of estimated to measured drift capacity for the developed ML model was 1.0 with a coefficient of variation (CV) of 0.33. In comparison, the regression equation currently adopted in New Zealand and the US to estimate the drift capacity of RC columns has a mean of 0.44 and a CV of 0.67. Other empirical methods assessed in this study also led to large scatter and no discernible correlation between estimated and measured drift capacity. The developed ML model provides more accurate results than existing methods and is capable of estimating the drift capacity of RC columns with a broad range of characteristics with (a) axial load ratios ranging from 0.0 to 0.9, (b) transverse area reinforcement ratios up to 2%, (c) longitudinal reinforcement ratios up to 6%, and (d) drift capacities up to 10%. The open-source model can be used by engineers and researchers alike to provide more accurate estimates of drift capacity during the design process, modelling of RC structures, and assessment of existing buildings.
Panel Discussion
Presented By: Jeffrey Rautenberg
Affiliation: Wiss, Janney, Elstner Associates
Description: Presenters and the audience will engage in a discussion related to the session topic.