Conference Editor
Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer
Location
Syracuse, NY
Event Website
http://ibpc2018.org/
Start Date
25-9-2018 3:15 PM
End Date
25-9-2018 5:00 PM
Description
In this paper, the potential of model order reduction for simulating building performance is assessed, via a case study of modelling heat transfer through a massive masonry wall. Two model order reduction techniques – proper orthogonal decomposition and proper generalized decomposition – are investigated and compared. Moreover, to illustrate the performance of model order reduction techniques, the accuracies of the two model order reduction techniques are respectively compared with a standard finite element method. The outcomes show that both of the two model order reduction techniques are able to provide an accurate result, and the proper generalized decomposition tends to be more versatile than the proper orthogonal decomposition method.
Recommended Citation
Hou, Tianfeng; Roels, Staf; and Janssen, Hans, "A comparison of model order reduction methods for the simulation of wall heat transfer" (2018). International Building Physics Conference 2018. 2.
DOI
https://doi.org/10.14305/ibpc.2018.ps02
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
A comparison of model order reduction methods for the simulation of wall heat transfer
Syracuse, NY
In this paper, the potential of model order reduction for simulating building performance is assessed, via a case study of modelling heat transfer through a massive masonry wall. Two model order reduction techniques – proper orthogonal decomposition and proper generalized decomposition – are investigated and compared. Moreover, to illustrate the performance of model order reduction techniques, the accuracies of the two model order reduction techniques are respectively compared with a standard finite element method. The outcomes show that both of the two model order reduction techniques are able to provide an accurate result, and the proper generalized decomposition tends to be more versatile than the proper orthogonal decomposition method.
https://surface.syr.edu/ibpc/2018/posters/2
Comments
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