Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/32937
Title: | Frequency-domain regression method for estimating CTF models of building multilayer constructions | Authors: | Chen, Y Wang, S |
Keywords: | Building energy analysis CTF model FDR method Frequency-responce characteristics HVAC system Simulation |
Issue Date: | 2001 | Publisher: | Elsevier | Source: | Applied mathematical modelling, 2001, v. 25, no. 7, p. 579-592 How to cite? | Journal: | Applied mathematical modelling | Abstract: | The conduction transfer function (CTF) models of heat conduction through building constructions are widely used in building energy analysis and heating, ventilation, and air conditioning (HVAC) system design and simulation. A frequency-domain regression (FDR) method is developed to estimate the CTF model of a building construction from its theoretical response characteristics in this paper. First, the theoretical response characteristics are calculated simply by numerical matrix multiplication. The CTF coefficients are then obtained by simply solving a set of linear equations. The tests and comparisons have shown that CTF models obtained by the FDR method are completely equivalent to those found by the methods currently available. The FDR method can provide a short series of CTF coefficients, and the models by this method have a high accuracy in calculating heat gain/loss through building constructions. The FDR method is very simple and straightforward, has high computational speeds, and needs less computational efforts. Therefore, the FDR method is much easier and convenient to use and implement in building energy analysis and HVAC system simulation programs. | URI: | http://hdl.handle.net/10397/32937 | ISSN: | 0307-904X | DOI: | 10.1016/S0307-904X(00)00067-6 |
Appears in Collections: | Journal/Magazine Article |
Show full item record
SCOPUSTM
Citations
21
Last Week
0
0
Last month
0
0
Citations as of Feb 12, 2019
WEB OF SCIENCETM
Citations
19
Last Week
0
0
Last month
0
0
Citations as of Feb 19, 2019
Page view(s)
83
Last Week
0
0
Last month
Citations as of Feb 19, 2019

Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.