Title:
Leveraging Machine Learning to Better Understand Structural Behavior of Concrete Components under Extreme Loads
Author(s):
Paal
Publication:
Web Session
Volume:
ws_F23_Paal.pdf
Issue:
Appears on pages(s):
Keywords:
DOI:
Date:
10/29/2023
Abstract:
Existing physics-based modeling approaches for predicting the seismic response of reinforced concrete frames do not have a good compromise between performance and computational efficiency. High-fidelity models have reasonable predictive performance but are very computationally demanding, while more simplified models lose accuracy but maintain computational efficiency. This presentation will cover recent advances in machine learning-informed prediction of RC components as well as a highly accurate and computationally efficient approach to predicting the performance of RC frames.