SysML Executable Model of an Energy Efficient House and Trade-Off Analysis

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dc.contributor.advisorBaras, John S.en_US
dc.contributor.authorCawasji, Kersasp Aspien_US
dc.contributor.departmentSystems Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2018-07-17T06:34:47Z
dc.date.available2018-07-17T06:34:47Z
dc.date.issued2018en_US
dc.description.abstractWith the growing complexity of energy efficient buildings, the methods of modeling and simulating such structures must account for monitoring several thousand design parameters across multiple diverse domains. As a result, modeling tools are now very specific to their respective domains and are growing more and more incongruous with each other. This calls for a way to integrate multiple modeling tools in the effort to create a single, large model capable to encapsulate data from multiple, different models. Thus, in this thesis, different methods to perform an integration with Systems Modeling Language (SysML) and a simulation tool were identified, described and evaluated. Then, a new method was developed and discussed. Finally, the new method was demonstrated by developing a SysML executable model of a simple two-room house that utilizes solar power for space heating, with a heat pump used as a backup. Using the Functional Mock-up Interface (FMI) standard, the SysML model is integrated with a Modelica model, and a simulation is run in Simulink. Finally, a tradeoff analysis was performed for the purpose of design space exploration.en_US
dc.identifierhttps://doi.org/10.13016/M2W37KZ8V
dc.identifier.urihttp://hdl.handle.net/1903/21083
dc.language.isoenen_US
dc.subject.pqcontrolledSystems scienceen_US
dc.subject.pquncontrolledexecutableen_US
dc.subject.pquncontrolledFMIen_US
dc.subject.pquncontrolledIntegrationen_US
dc.subject.pquncontrolledMBSEen_US
dc.subject.pquncontrolledSimulinken_US
dc.subject.pquncontrolledSysMLen_US
dc.titleSysML Executable Model of an Energy Efficient House and Trade-Off Analysisen_US
dc.typeThesisen_US

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