The impact of a PEER funded research project "Bayesian Inference for Mechanics-Based Digital Twinning of Bridges" is highlighted below. The project Principal Investigator (PI) is Hamed Ebrahimian, Assistant Professor, University of Nevada, Reno. The Research Team includes Abdelrahman Taha, Graduate Student Researcher, University of Nevada, Reno.
PEER’s Performance-Based Engineering (PBE) methodology is now accepted in the engineering community and used in practice for design of new structures or assessment of existing ones. Dynamic nonlinear time-history analysis is at the center of this methodology, so any improvement in the numerical modeling of the structures reduces overall uncertainties of the final outcomes. Damping energy dissipation, nonlinear material behavior, and SFSI effects are among sources of uncertainties, which can only be addressed through model inversion using real-life data. This project can potentially impact the state-of-practice through validation of design models, potential development of guidelines for more accurate forward modeling, and development of digital inventory of bridge infrastructures across California to be continuously trained with data.