Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building
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...
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doaj-3bb9a4b65c924d56a9ea5efd54cbeb072020-11-25T00:38:34ZengMDPI AGSensors1424-82202016-07-01167101610.3390/s16071016s16071016Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT BuildingYoung-Jin Cha0Peter Trocha1Oral Büyüköztürk2Department of Civil Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, CanadaGEI Consultants Inc., Woburn, MA 01801, USADepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USATall 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.http://www.mdpi.com/1424-8220/16/7/1016spectral analysissystem identificationsensor networkdynamic responseambient vibration |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Young-Jin Cha Peter Trocha Oral Büyüköztürk |
spellingShingle |
Young-Jin Cha Peter Trocha Oral Büyüköztürk Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building Sensors spectral analysis system identification sensor network dynamic response ambient vibration |
author_facet |
Young-Jin Cha Peter Trocha Oral Büyüköztürk |
author_sort |
Young-Jin Cha |
title |
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building |
title_short |
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building |
title_full |
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building |
title_fullStr |
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building |
title_full_unstemmed |
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building |
title_sort |
field measurement-based system identification and dynamic response prediction of a unique mit building |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-07-01 |
description |
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. |
topic |
spectral analysis system identification sensor network dynamic response ambient vibration |
url |
http://www.mdpi.com/1424-8220/16/7/1016 |
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