<?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>2026-09-19T12:31:12Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/105690" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/105690</identifier><datestamp>2022-01-13T07:54:05Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131024</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">Paul D. Sclavounos.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Larson, David F. H</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">Massachusetts Institute of Technology. Department of Mechanical Engineering</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2016-12-05T19:58:11Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2016-12-05T19:58:11Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/105690</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">964521691</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.</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 (page 54).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">A procedure is developed for modeling stochastic ocean wave and wind loads as diffusive stochastic differential equations (SDE) in a state space form to derive the response statistics of offshore structures, specifically wind turbines. Often, severe wind and wave systems are highly nonlinear and thus treatment as linear systems is not applicable, leading to computationally expensive Monte Carlo simulations. Using Stratonovich-form diffusive stochastic differential equations, both linear and nonlinear components of the wind thrust can be modeled as 2 state SDE. These processes can be superposed with both the linear and nonlinear (inertial and viscous) wave forces, also modeled as a multi-dimensional state space SDE. Furthermore, upon implementing the ESPRIT algorithm to fit the autocorrelation function of any real sea state spectrum, a simple 2-state space model can be derived to completely describe the wave forces. The resulting compound state-space SDE model forms the input to a multi-dimension state-space Fokker-Planck equation, governing the dynamical response of the wind turbine structure. Its solution yields response, fatigue and failure statistics-information critical to the design of any offshore structure. The resulting Fokker-Planck equation can be solved using existing numerical schemes.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by David F.H. Larson.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.B.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">54 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">Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Modeling nonlinear stochastic ocean loads as diffusive stochastic differential equations to derive the dynamic responses of offshore wind turbines</dim:field>
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   	&lt;Title>Modeling nonlinear stochastic ocean loads as diffusive stochastic differential equations to derive the dynamic responses of offshore wind turbines&lt;/Title>
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   	&lt;PublicationDate>2016&lt;/PublicationDate>
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        	&lt;DisplayName>Larson, David F. H&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;License>http://dspace.mit.edu/handle/1721.1/7582&lt;/License>
    &lt;Keyword>Mechanical Engineering.&lt;/Keyword>
   	&lt;Abstract>A procedure is developed for modeling stochastic ocean wave and wind loads as diffusive stochastic differential equations (SDE) in a state space form to derive the response statistics of offshore structures, specifically wind turbines. Often, severe wind and wave systems are highly nonlinear and thus treatment as linear systems is not applicable, leading to computationally expensive Monte Carlo simulations. Using Stratonovich-form diffusive stochastic differential equations, both linear and nonlinear components of the wind thrust can be modeled as 2 state SDE. These processes can be superposed with both the linear and nonlinear (inertial and viscous) wave forces, also modeled as a multi-dimensional state space SDE. Furthermore, upon implementing the ESPRIT algorithm to fit the autocorrelation function of any real sea state spectrum, a simple 2-state space model can be derived to completely describe the wave forces. The resulting compound state-space SDE model forms the input to a multi-dimension state-space Fokker-Planck equation, governing the dynamical response of the wind turbine structure. Its solution yields response, fatigue and failure statistics-information critical to the design of any offshore structure. The resulting Fokker-Planck equation can be solved using existing numerical schemes.&lt;/Abstract>
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