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Estimation of building component UA and gA from outdoor tests in warm and moderate weather conditions
Authors:MJ Jiménez  B Porcar  MR Heras
Affiliation:1. Building Physics Section, KU Leuven University of Leuven, Kasteelpark Arenberg 40 box 02447, 3001 Heverlee, Belgium;2. DTU Compute Dynamical Systems, Technical University of Denmark, Denmark;3. Energy Efficiency in Buildings R&D Unit, CIEMAT, Spain;1. Energy Efficiency in Buildings R&D Unit, CIEMAT, Madrid E-28040, Spain;2. Informatics, Technical University of Denmark, Richard Pedersen Plads, Building 305, 2800 Lyngby, Denmark;3. Department of Applied Physics, University of Granada, Av. Severo Ochoa s/n, E-18071 Granada, Spain;4. CETHIL UMR5008, INSA-Lyon, 9 rue de la physique, F-69621 Villeurbanne, France;1. CETHIL UMR5008, INSA-Lyon, 9 rue de la physique, F-69621 Villeurbanne, France;2. University of Granada, Campus Fuentenueva, E-18071 Granada, Spain;3. Energy Efficiency in Buildings R&D Unit, CIEMAT, Madrid E-28040, Spain
Abstract:Accurate knowledge of the thermal properties of building components is necessary to implement adequate energy saving strategies in buildings. Outdoor experiments using test cells are very useful tools for realistic estimation of these properties. This paper describes the analyses performed, and the procedure followed in identifying and solving some problems found when building components are tested for UA and gA in a test cell under warm and moderate weather conditions. A window component was tested in a PASLINK test cell at the CIEMAT’s ‘Plataforma Solar de Almería (PSA-CIEMAT)’ in Tabernas (Almería, Spain) and several data sets recorded under quite different weather and test conditions were analysed. First the problems identified when applying the usual test and linear analysis procedures are described. Then hypotheses about the cause of these problems are formulated. Afterwards, strategies followed for testing these hypotheses are described. Once the cause of the problems had been identified, they were fine tuned to find a model for accurate UA and gA estimation. This study demonstrated that nonlinear models, in which long wave radiation is considered as nonlinear effect, yield remarkably better performance than the commonly used linear models, for estimating the component UA and gA values.
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