title: Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.
abstract: Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.
authors.affiliation: Department of Civil Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada. young.cha@umanitoba.ca.
authors.forename: Young-Jin
authors.initials: YJ
authors.lastname: Cha
authors.affiliation: GEI Consultants Inc., Woburn, MA 01801, USA. ptrocha@geiconsultants.com.
authors.forename: Peter
authors.initials: P
authors.lastname: Trocha
authors.affiliation: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. obuyuk@mit.edu.
authors.forename: Oral
authors.initials: O
authors.lastname: Büyüköztürk
keywords: ambient vibration; dynamic response; sensor network; spectral analysis; system identification