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Title: Structured building model reduction toward parallel simulation

Abstract

Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to improve simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inherently limited by inter-processor communication. This paper bridges these disparate techniques to implement efficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allocate processing resources. Experimental results demonstrate faster simulation and low error without any interprocessor communication.

Authors:
 [1];  [1]
  1. Cornell University
Publication Date:
Research Org.:
Cornell Univ., Ithaca, NY (United States)
Sponsoring Org.:
USDOE National Energy Technology Lab; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
Contributing Org.:
Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA
OSTI Identifier:
1089754
Report Number(s):
DOE/EE0003921-12
DOE Contract Number:  
EE0003921
Resource Type:
Conference
Resource Relation:
Conference: 13th International Conference of the International Building Performance Simulation Association
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; model reduction; parallel simulation; structured model reduction; aggregation; clustering

Citation Formats

Dobbs, Justin R., and Hencey, Brondon M. Structured building model reduction toward parallel simulation. United States: N. p., 2013. Web.
Dobbs, Justin R., & Hencey, Brondon M. Structured building model reduction toward parallel simulation. United States.
Dobbs, Justin R., and Hencey, Brondon M. 2013. "Structured building model reduction toward parallel simulation". United States. https://www.osti.gov/servlets/purl/1089754.
@article{osti_1089754,
title = {Structured building model reduction toward parallel simulation},
author = {Dobbs, Justin R. and Hencey, Brondon M.},
abstractNote = {Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to improve simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inherently limited by inter-processor communication. This paper bridges these disparate techniques to implement efficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allocate processing resources. Experimental results demonstrate faster simulation and low error without any interprocessor communication.},
doi = {},
url = {https://www.osti.gov/biblio/1089754}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Aug 26 00:00:00 EDT 2013},
month = {Mon Aug 26 00:00:00 EDT 2013}
}

Conference:
Other availability
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