<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T23:29:09Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/82854" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/82854</identifier><datestamp>2022-01-13T07:53:59Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Eduardo Kausel.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Trocha, Peter Adam</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2013-12-06T20:49:32Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2013-12-06T20:49:32Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/82854</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">863418051</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M.)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 127).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Both vibration-based structural health monitoring methodologies and seismic performance analysis rely on estimates of the base-line dynamic behavior of a structure. A common method for making this estimate is through measuring structural motions using sensors deployed in the structure of interest. This procedure was applied to the Green Building, a 20 story structure on the campus of the Massachusetts Institute of Technology. Using a network of 36 accelerometers installed in the structure by the United States Geological Survey, the response accelerations from ambient vibrations, seismic loading, and firework excitations were collected. Spectral analysis methods were applied to the collected data to identify the frequencies and general mode shapes of eight normal modes of the structure. These frequencies were 0.68 Hz, 2.45 Hz, and 8.10 Hz in the east-west direction; 0.75 Hz, 2.85 Hz, and 8.25 Hz in the north-south direction; and 1.45 Hz and 5.05 Hz in torsion. The building was found to have strong torsional responses, an asymmetry in the dynamic behavior of the eastern and western sides, and substantial base rocking motion, even under ambient excitations. Using the original design documents, the Green Building was numerically modeled with a lump-mass stick model and a mixed-element beam-shell finite element model. These models were validated and refined using the collected acceleration data. Initial simulations of seismic excitations demonstrated both models to have good agreement with measured values. The numerical models and structural characterization of the Green Building will be used to further develop vibration-based damage detection methodologies and to predict structural performance during strong seismic events.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Peter Adam Trocha.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">127 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Characterization of structural properties and dynamic behavior using distributed accelerometer networks and numerical modeling</dim:field>
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   	&lt;Title>Characterization of structural properties and dynamic behavior using distributed accelerometer networks and numerical modeling&lt;/Title>
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   	&lt;PublicationDate>2013&lt;/PublicationDate>
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    &lt;Keyword>Civil and Environmental Engineering.&lt;/Keyword>
   	&lt;Abstract>Both vibration-based structural health monitoring methodologies and seismic performance analysis rely on estimates of the base-line dynamic behavior of a structure. A common method for making this estimate is through measuring structural motions using sensors deployed in the structure of interest. This procedure was applied to the Green Building, a 20 story structure on the campus of the Massachusetts Institute of Technology. Using a network of 36 accelerometers installed in the structure by the United States Geological Survey, the response accelerations from ambient vibrations, seismic loading, and firework excitations were collected. Spectral analysis methods were applied to the collected data to identify the frequencies and general mode shapes of eight normal modes of the structure. These frequencies were 0.68 Hz, 2.45 Hz, and 8.10 Hz in the east-west direction; 0.75 Hz, 2.85 Hz, and 8.25 Hz in the north-south direction; and 1.45 Hz and 5.05 Hz in torsion. The building was found to have strong torsional responses, an asymmetry in the dynamic behavior of the eastern and western sides, and substantial base rocking motion, even under ambient excitations. Using the original design documents, the Green Building was numerically modeled with a lump-mass stick model and a mixed-element beam-shell finite element model. These models were validated and refined using the collected acceleration data. Initial simulations of seismic excitations demonstrated both models to have good agreement with measured values. The numerical models and structural characterization of the Green Building will be used to further develop vibration-based damage detection methodologies and to predict structural performance during strong seismic events.&lt;/Abstract>
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