<?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>2026-09-19T00:57:40Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/122264" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/122264</identifier><datestamp>2021-07-05T14:03:20Z</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">Michael S. Triantafyllou.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Gilligan, Brian Kenneth.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Department of Mechanical Engineering</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2019-09-17T22:44:35Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2019-09-17T22:44:35Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2019</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2019</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/122264</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1117714720</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Naval Architecture and Marine Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019</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 90-95).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This thesis presents a dynamic model that can be used for a digital twin of an electric ship. The model is an end-to-end simulation of a ship from prime mover to maneuvering, seakeeping, and propeller ventilation in random waves representing the behavior of a physical ship. There is a trend towards increasingly networked sensors and actuators to enable condition monitoring, ensure efficient operation, and allow for autonomy. However, a cyberattack on a networked control system presents not just the possibility of information theft but of physical system damage and loss of control. Thus, a detection scheme is proposed for cyber-physical systems using a joint unscented Kalman filter. It is employed to detect cyberattacks in the simulation model of an electric ship including sensor attacks and controller attacks on a gas turbine, synchronous generator, and automatic heading control. Finally, a system theoretic framework is presented for optimal sensor placement to minimize cyber vulnerability.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="sponsorship" lang="en_US">United States. Office of Naval Researchgrant N00014-16-1- 2956</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Brian Kenneth Gilligan.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Naval Architecture and Marine Engineering</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="collection" lang="en_US">S.M.inNavalArchitectureandMarineEngineering Massachusetts Institute of Technology, Department of Mechanical Engineering</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">95 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">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written 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">Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Electric ship digital twin : framework for cyber-physical system security</dim:field>
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   <dim:field mdschema="mit" element="thesis" qualifier="department" lang="en_US">MechE</dim:field>
   <dim:field mdschema="others" element="access-status">unknown</dim:field>
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   	&lt;Title>Electric ship digital twin : framework for cyber-physical system security&lt;/Title>
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   	&lt;PublicationDate>2019&lt;/PublicationDate>
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        	&lt;DisplayName>Gilligan, Brian Kenneth.&lt;/DisplayName>
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    &lt;Keyword>Mechanical Engineering.&lt;/Keyword>
   	&lt;Abstract>This thesis presents a dynamic model that can be used for a digital twin of an electric ship. The model is an end-to-end simulation of a ship from prime mover to maneuvering, seakeeping, and propeller ventilation in random waves representing the behavior of a physical ship. There is a trend towards increasingly networked sensors and actuators to enable condition monitoring, ensure efficient operation, and allow for autonomy. However, a cyberattack on a networked control system presents not just the possibility of information theft but of physical system damage and loss of control. Thus, a detection scheme is proposed for cyber-physical systems using a joint unscented Kalman filter. It is employed to detect cyberattacks in the simulation model of an electric ship including sensor attacks and controller attacks on a gas turbine, synchronous generator, and automatic heading control. Finally, a system theoretic framework is presented for optimal sensor placement to minimize cyber vulnerability.&lt;/Abstract>
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