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Open Computing Infrastructure for Sharing Data Analytics to Support Building Energy Simulations

AbstractBuilding energy simulation plays an increasingly important role in building design and operation. This paper presents an open computing infrastructure, Virtual Information Fabric Infrastructure (VIFI), that allows building designers and engineers to enhance their simulations by combining emp...

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Bibliographic Details
Published in:Journal of computing in civil engineering 2019-11, Vol.33 (6)
Main Authors: Karaguzel, Omer T, Elshambakey, Mohammed, Zhu, Yimin, Hong, Tianzhen, Tolone, William J, Das Bhattacharjee, Sreyasee, Cho, Isaac, Dou, Wenwen, Wang, Haopeng, Lu, Siliang, Khalefa, Mohamed, Tao, Yong
Format: Article
Language:English
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Summary:AbstractBuilding energy simulation plays an increasingly important role in building design and operation. This paper presents an open computing infrastructure, Virtual Information Fabric Infrastructure (VIFI), that allows building designers and engineers to enhance their simulations by combining empirical data with diagnostic or prognostic models. Based on the idea of dynamic data-driven application systems (DDDAS), the VIFI infrastructure complements conventional data-centric sharing strategies and addresses key data-sharing concerns such as the privacy of building occupants. To demonstrate the potential of the VIFI infrastructure, an empirically derived lighting schedule in the US Department of Energy’s small office building reference model is simulated. The case-study simulation is used to explore (1) the possibility and potential of integrating data-centric and analytic-centric sharing strategies; (2) the method of combining empirical data with simulations; (3) the creation, sharing, and execution of analytics using VIFI; and (4) the impact of incorporating empirical data on energy simulations. Although the case study reveals clear advantages of the VIFI data infrastructure, research questions remain surrounding the motivation and benefits for sharing data, the metadata that are required to support the composition of analytics, and the performance metrics that could be used in assessing the applications of VIFI.
ISSN:0887-3801
1943-5487
DOI:10.1061/(ASCE)CP.1943-5487.0000857