Ambient Vibration Monitoring and Structural Identification

Dates: September 2005 – March 2009

Location: New York City Area

PIs: A.E. AktanF.L. Moon

Researchers: K. Grimmelsman, Q. Pan, J. Prader,

Partners: Parsons Corporation and Pennoni Associates, Inc.


The recent re-mapping of the seismic hazards in the New York City region has prompted infrastructure owners to perform seismic vulnerability assessments on their most critical assets. As part of these efforts, IIS partnered with Parsons Corporation which was tasked with examining the Brooklyn Bridge (NYC DOT), the Henry Hudson Bridge (NY MTA) and the Throgs Neck Bridge (NY MTA). The principal role of Drexel in these efforts was to perform ambient vibration testing of each structure using dense sensor arrays to obtain estimates of the operating frequencies and mode shapes.  To accomplish this, a suite of different post-processing and modal identification approaches were employed and new techniques to simulate multi-reference impact tests were developed along with strategies to reliably address lightly coupled structural systems.

In addition, Drexel personnel aided in the correlation of various simulation models with the observed modal parameters. Following this correlation, Parsons Corporation leveraged the models to assess the seismic performance/vulnerability of each structure and to make recommendations as to the appropriateness of various interventions.

Selected Publications

Pan, Q, K. Grimmelsman, F.L. Moon and A.E. Aktan (2011) “Mitigating Epistemic Uncertainty in Structural Identification.”  ASCE Journal of Structural Engineering

Zhang, J., Prader, K.A. Grimmelsman, F.L. Moon, A.E. Aktan, and A. Shama (2009) “Challenges in Experimental Vibration Analysis for Structural Identification and Corresponding Engineering Strategies,” Keynote Paper, Experimental Vibration Analysis for Civil Engineering Structures (EVACES), October 14-16, 2009, Wroclaw, Poland

Grimmelsman, K., K. Ciloglu, Q. Pan, R. Zhang, F.L. Moon and A.E. Aktan (2005) “Impacts of Uncertainty and their Mitigation for Improving Data Reliability from Field Measurements,” 2nd International Conference on Structural Health Monitoring of Intelligent Infrastructure, Shenzhen, China