Date of Award

Spring 2020

Project Type


Program or Major

Civil Engineering

Degree Name

Doctor of Philosophy

First Advisor

Erin Bell

Second Advisor

Ricardo A Medina

Third Advisor

Luis Ibarra


The availability of reliable numerical models is essential to reduce the uncertainties present in the prediction of structural behavior. Experimental studies allow the calibration and development of numerical models capable of characterizing the realistic behavior of structural elements and components until the limit state of collapse is approached. Exterior columns in perimeter steel moment-resisting frame structures that are exposed to strong earthquakes experience bending moment demands with high levels of axial load due to overturning. Deep wide flange sections can be used as exterior columns to increase the lateral stiffness of moment frames without significantly increasing the overall weight of the structure. However, experimental data on the cyclic response of deep steel wide flange sections subjected to large drift, rotation, and axial load demands are scarce. To address this need, this research presents results from an experimental program that deals with studying and quantifying the behavior of 1:8 scaled W36X652 column sections exposed to different monotonic and cyclic loading histories consisting of large drift ratios of up to 0.1 rad, rotations at the tip of the column of up to 0.1 rad, and variable levels of axial loads up to 60% (in compression) of the column axial load carrying capacity that vary between tension and compression are used. The experiments consist of quasi-static experiments and hybrid simulations. The influence of member behavior and axial load on the parameters that control the collapse of the structure was studied. Column plastic rotations from 0.012 to 0.08 rad and post-capping rotations from 0.03 to 0.37 rad were observed depending on the loading history and level of axial load. Further, numerical models of the column were calibrated utilizing the experimental results performed in this research. These models can be used for design and performance prediction of deep column section, especially valued in seismic design and assessment.