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Predictions' robustness of one-dimensional model of hydronic floor heating: novel validation methodology using a thermostatic booth simulator and uncertainty analysis
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Energy Efficiency)ORCID iD: 0000-0002-2822-0000
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Energy Efficiency)
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Energy Efficiency)
2018 (English)In: Journal of Building Physics, ISSN 1744-2591, E-ISSN 1744-2583, Vol. 41, no 5, p. 418-444Article in journal, Editorial material (Refereed) Published
Abstract [en]

Hydronic floor heating models provide predictions in estimating heat transfer rates and floor surface temperature. Information on the model performance and range of validity of its results are often lacking in literature. Researchers have to know the accuracy and robustness of the model outcomes for performing energy and climate comfort calculations. This article proposes a novel validation methodology based on the uncertainty analysis of input data/parameters of one-dimensional model of hydronic floor heating tested in a thermostatic booth simulator and compared with experimental measurements. The main results are: (1) prediction accuracy between 0.4% and 2.9% for Tf and between 0.7% and 7.8% for qup when the serpentine has tube spacing (p) of 0.30 m, (2) prediction accuracy between 0.5% and 1.4% for Tf and between 8.7% and 12.9% for qup with p = 0.15m and (3) Tfld mostly affects predictions with oscillations between 6.2% and 2.2% for qup. This model provides robust and reliable predictions exclusively for qup when p = 0.30m.

Place, publisher, year, edition, pages
Sage Publications, 2018. Vol. 41, no 5, p. 418-444
Keywords [en]
One-Dimensional model of hydronic floor heating, thermostatic booth simulator, validation methodology, uncertainty bands, differential sensitivity analysis, robustness of model's predictions
National Category
Building Technologies
Research subject
Physics
Identifiers
URN: urn:nbn:se:umu:diva-136486DOI: 10.1177/1744259117721002ISI: 000429862600002OAI: oai:DiVA.org:umu-136486DiVA, id: diva2:1111581
Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2018-09-21Bibliographically approved
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Brembilla, ChristianÖstin, RonnyOlofsson, Thomas

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