Machine Learning In Bridge Design

The goal of this project is to develop deep understanding of different applications of machine
learning that are better suited for different structural and bridge engineering problems from structural
health monitoring/prediction, automated prediction of structural forms’ capacities; material
characteristics, and automated design practices

Specific Objectives:

• Conduct Literature Search
• Identify Bridge Engineering Applications for automation through Machine Learning
• Develop Machine Learning Techniques for Structural Health Prediction of Bridges During Extreme Events

Project Description: The application of machine learning (ML) and artificial intelligence (AI) are
implemented in different forms in our modern society. ML and AI can enhance the resilience of
bridge infrastructure by providing rapid decision making tools (prediction) following extreme events.

Funding Agency:  U.S. DOT through ABC-UTC

Funding: $50,000 (on-going)

Abstract: This study will develop machine learning techniques for structural health predictions for
bridge infrastructure during seismic events

Research Team: One faculty member, One graduate student, 6 undergraduate students

Readily Implementable Products (Impact): This project will have a broader impact in application of ML in bridge design and monitoring leading to automated disaster responses