Strengthening American Infrastructure - Research

Over the summer of 2025, I worked as a research assistant in the SAI-R (Strengthening American Infrastructure – Research) project at the Intelligent Infrastructure Systems Laboratory (IISL) in Bowen Laboratory at Purdue University. The goal of this research project was to identify effective retrofit and repair strategies for nonductile reinforced concrete buildings (NDRCBs), and was achieved through experimental testing performed on large-scale reinforced concrete columns and hybrid simulations. Throughout my work, I gained experience in a broad range of engineering topics, such as MATLAB, finite element analysis, control systems.

Individual Responsibilities:

• Developed a MATLAB application for presenting displacement data, notes, and photos from tests (see details below)
• Conducted data collection from academic dissertations to tune a finite element analysis (FEA) model in OpenSeesPy, and ran material component simulations and helped debug the existing simulation program
• Assisted in instrumentation setup and data collection during large-scale structural testing
• Created comprehensive documentation of post-test damage on concrete specimen

One of my key projects at the lab was designing and developing a presentation tool that consolidated notes, photos, and displacement data into a single, user-friendly format. Tests sometimes lasted over 10 hours and generated a large volume of information; concisely and effectively presenting this data to others was a significant challenge.

The PI’s two main requirements for this tool were ease of use and reusability; it needed to be simple to present and easy for future researchers to use with tests. To accomplish this, I utilized MATLAB App Designer to create an application for the data presentation. I designed the UI (pictured below) to feature a slider to navigate data over time and a dropdown menu to easily switch between tests. To ensure ease of use for future tests, I designed it to automatically handle a variety of data setups and process large test files just once to ensure simple operation.

The app featured an interactive slider to easily view photos, notes, and data from any point during the test.

Outcomes:

My contributions to the project proved to be very important to the project’s progress. I was quickly able to adapt to the team and the many nuances of a large-scale structural research project. My programming experience proved to be a valuable asset in this effort, as I regularly assisted the PI with tasks such as data analysis in MATLAB and debugging FEA programs in Python. I was an integral part of the team and my work proved invaluable during the culmination of the three-year project.