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dc.contributor.advisorGarrison, Michael
dc.creatorMorales, Cristian Enriqueen
dc.date.accessioned2013-11-21T18:27:19Zen
dc.date.issued2013-05en
dc.date.submittedMay 2013en
dc.identifier.urihttp://hdl.handle.net/2152/22346en
dc.descriptiontexten
dc.description.abstractThe purpose of this thesis is to develop a simple tool that can help designers and researchers obtain general guidelines for buildings in terms of energy usage and LCC. Another objective of this thesis is to apply this tool to residential buildings in order to understand which variables are relevant in terms of energy consumption and LCC costs. A one-story rectangular house was parameterized in terms of five variables: total glazing area; south window-to-wall ratio (WWR); east and west WWR (which are symmetrical for these two facades); insulation width; and window type (ranging from a single clear window to a double low e-clear argon filled window). A high average glazing area (30-40% of floor area) was applied in order to increase energy loads and to augment the importance of the window properties. Simulation was performed through Energy-plus (in conjunction with a code developed especially for this project) for three cities: Austin, Boston, and Seattle. A total of 1055 simulations were run for each city. The experiment showed that only the total glazing area, the E-W WWR and the window types were relevant variables. The former variable is highly correlated with total energy consumption across all cities. Another important conclusion was that each variable's effect on energy consumption worked independently of each other, as there were no considerable differences when analyzing variables individually, as opposed to analyzing them holistically. Results showed that, for Austin and Boston, it was possible to reduce energy loads by 35% and 27% respectively with a double low-e green window (as compared to a single clear window). Similarly, Seattle showed a reduction of 29% for a double low e-clear argon filled window. Nevertheless, the simplest type of window (type 1) presented the best results in terms of LCC. Therefore, we can conclude that only under a high-energy demand situation, such as with office buildings, would it be possible to obtain positive LCC results for double glazed windows. Consequently, double glazed windows will not present positive economical results in typical residential buildings. A second simulation was performed under a tighter HVAC schedule and higher internal loads. In this new scenario, the best windows were the same as with the first simulation, but maximum energy savings were higher: 50%, 34% and 35% for Austin, Boston, and Seattle, respectively. Nevertheless, when considering LCC, a double-clear window presented the best results for Austin, Boston, and Seattle, with 17%, 11%, and 5% reductions in costs respectively compared to the type 1 window. Therefore, if designers are only concerned with costs, the problem of what window to choose becomes non-trivial only for high-energy demand cases.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.subjectParametric modelingen
dc.subjectLCC analysisen
dc.subjectCost-efficient windowsen
dc.subjectEnergy simulationen
dc.titleParametric energy modeling tool for climate dependent guidelinesen
dc.date.updated2013-11-21T18:27:19Zen
dc.description.departmentArchitectureen
thesis.degree.departmentArchitecture, School ofen
thesis.degree.disciplineSustainable Designen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Sustainable Designen


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