Estimation of Thermal Networks Using Singular Value Decomposition Method
(2009) In Experimental Heat Transfer 22(1). p.39-57- Abstract
- A model is developed using a thermal network analysis approach. An experimental setup is designed and built to validate the model. The model is based on an inverse thermal network analysis using a singular value decomposition algorithm. The data from the experiments are used to determine the thermal conductances using inverse model's unsteady- and steady-state forms. The model development and experimental results are presented together with possible sources of error and how to avoid or decrease their influence. Good agreement between the thermal network model predictions and experiments was found.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1312823
- author
- Saidi, A. ; Magnusson, P and Sundén, Bengt LU
- organization
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- inverse method, ill-conditioned, singular value decomposition, thermal network, thermal conductance
- in
- Experimental Heat Transfer
- volume
- 22
- issue
- 1
- pages
- 39 - 57
- publisher
- Taylor & Francis
- external identifiers
-
- wos:000262295700004
- scopus:60749083846
- ISSN
- 0891-6152
- DOI
- 10.1080/08916150802530112
- language
- English
- LU publication?
- yes
- id
- e7932617-2fc4-42e4-9604-e66d33d623e0 (old id 1312823)
- date added to LUP
- 2016-04-01 11:57:56
- date last changed
- 2022-01-26 20:49:32
@article{e7932617-2fc4-42e4-9604-e66d33d623e0, abstract = {{A model is developed using a thermal network analysis approach. An experimental setup is designed and built to validate the model. The model is based on an inverse thermal network analysis using a singular value decomposition algorithm. The data from the experiments are used to determine the thermal conductances using inverse model's unsteady- and steady-state forms. The model development and experimental results are presented together with possible sources of error and how to avoid or decrease their influence. Good agreement between the thermal network model predictions and experiments was found.}}, author = {{Saidi, A. and Magnusson, P and Sundén, Bengt}}, issn = {{0891-6152}}, keywords = {{inverse method; ill-conditioned; singular value decomposition; thermal network; thermal conductance}}, language = {{eng}}, number = {{1}}, pages = {{39--57}}, publisher = {{Taylor & Francis}}, series = {{Experimental Heat Transfer}}, title = {{Estimation of Thermal Networks Using Singular Value Decomposition Method}}, url = {{http://dx.doi.org/10.1080/08916150802530112}}, doi = {{10.1080/08916150802530112}}, volume = {{22}}, year = {{2009}}, }