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David Daily

dc.contributor.advisorBaras, Johnen_US
dc.contributor.authorDaily, David Richarden_US
dc.date.accessioned2014-06-24T05:38:09Z
dc.date.available2014-06-24T05:38:09Z
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1903/15145
dc.description.abstractEnergy efficient buildings are becoming more necessary to meet government standards, reduce operating costs, and curb emissions. However, designing efficient buildings is significantly complicated as designers must account for hundreds of design parameters across multiple domains. Simulation-based, design space exploration allows for designers to model a building's performance for multiple designs. These simulations can be computationally expensive and time consuming. This thesis explores trade-off analysis in building design space exploration through the use of multi-objective optimization software that seeks to quickly produce optimal designs. Three different techniques are developed producing optimal design configurations for each technique.en_US
dc.language.isoenen_US
dc.titleDavid Dailyen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentSystems Engineeringen_US
dc.subject.pqcontrolledSystem scienceen_US
dc.subject.pqcontrolledEnergyen_US
dc.subject.pquncontrolledDesign Space Explorationen_US
dc.subject.pquncontrolledEnergy Modelingen_US
dc.subject.pquncontrolledModel Based System Engineeringen_US
dc.subject.pquncontrolledNet Zero Buildingsen_US
dc.subject.pquncontrolledOptimizationen_US
dc.subject.pquncontrolledTrade-Offen_US


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