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Title: A comparison of thermal zone aggregation methods

Abstract

The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.

Authors:
 [1];  [1]
  1. Cornell University
Publication Date:
Research Org.:
Cornell University, Ithaca, NY
Sponsoring Org.:
USDOE National Energy Technology Lab; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
OSTI Identifier:
1081563
Report Number(s):
DOE/EE0003921-9
DOE Contract Number:  
EE0003921
Resource Type:
Conference
Resource Relation:
Conference: 2012 IEEE 51st Annual Conference on Decision and Control (CDC)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; buildings; geometric building information models; hierarchical cluster partitioning methods; thermal zone aggregation-based model reduction

Citation Formats

Dobbs, Justin R., and Hencey, Brandon M. A comparison of thermal zone aggregation methods. United States: N. p., 2012. Web. doi:10.1109/CDC.2012.6425888.
Dobbs, Justin R., & Hencey, Brandon M. A comparison of thermal zone aggregation methods. United States. https://doi.org/10.1109/CDC.2012.6425888
Dobbs, Justin R., and Hencey, Brandon M. Mon . "A comparison of thermal zone aggregation methods". United States. https://doi.org/10.1109/CDC.2012.6425888. https://www.osti.gov/servlets/purl/1081563.
@article{osti_1081563,
title = {A comparison of thermal zone aggregation methods},
author = {Dobbs, Justin R. and Hencey, Brandon M.},
abstractNote = {The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.},
doi = {10.1109/CDC.2012.6425888},
url = {https://www.osti.gov/biblio/1081563}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {12}
}

Conference:
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