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Building energy modeling for green a...

DeBlois, Justin.

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Building energy modeling for green architecture and intelligent dashboard applications.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Building energy modeling for green architecture and intelligent dashboard applications./
作者:	DeBlois, Justin.
面頁冊數:	153 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Contained By:	Dissertation Abstracts International75-06B(E).
標題:	Engineering, Mechanical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3585449
ISBN:	9781303779398

Building energy modeling for green architecture and intelligent dashboard applications.
DeBlois, Justin.

Building energy modeling for green architecture and intelligent dashboard applications. - 153 p.

Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.

Thesis (Ph.D.)--University of Pittsburgh, 2013.

Buildings are responsible for 40% of the carbon emissions in the United States. Energy efficiency in this sector is key to reducing overall greenhouse gas emissions. This work studied the passive technique called the roof solar chimney for reducing the cooling load in homes architecturally. Three models of the chimney were created: a zonal building energy model, computational fluid dynamics model, and numerical analytic model. The study estimated the error introduced to the building energy model (BEM) through key assumptions, and then used a sensitivity analysis to examine the impact on the model outputs. The conclusion was that the error in the building energy model is small enough to use it for building simulation reliably. Further studies simulated the roof solar chimney in a whole building, integrated into one side of the roof. Comparisons were made between high and low efficiency constructions, and three ventilation strategies. The results showed that in four US climates, the roof solar chimney results in significant cooling load energy savings of up to 90%. After developing this new method for the small scale representation of a passive architecture technique in BEM, the study expanded the scope to address a fundamental issue in modeling - the implementation of the uncertainty from and improvement of occupant behavior. This is believed to be one of the weakest links in both accurate modeling and proper, energy efficient building operation. A calibrated model of the Mascaro Center for Sustainable Innovation's LEED Gold, 3,400 m2 building was created. Then algorithms were developed for integration to the building's dashboard application that show the occupant the energy savings for a variety of behaviors in real time. An approach using neural networks to act on real-time building automation system data was found to be the most accurate and efficient way to predict the current energy savings for each scenario. A stochastic study examined the impact of the representation of unpredictable occupancy patterns on model results. Combined, these studies inform modelers and researchers on frameworks for simulating holistically designed architecture and improving the interaction between models and building occupants, in residential and commercial settings. v.

ISBN: 9781303779398Subjects--Topical Terms:

783786
Engineering, Mechanical.

Building energy modeling for green architecture and intelligent dashboard applications.
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