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Thermal performance prediction of outdoor swimming pools

Lovell, D, Rickerby, T, Vandereydt, B, Do, L, Wang, X ORCID: 0000-0003-4293-7523, Srinivasan, K and Chua, HT 2019 , 'Thermal performance prediction of outdoor swimming pools' , Building and Environment, vol. 160 , pp. 1-11 , doi: 10.1016/j.buildenv.2019.106167.

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The sizing of water heating plants for outdoor community swimming pools conventionally relies on empirical methods and industry guidelines that seldom account for local climatic conditions. In the absence of a model that accounts for all modes of heat and mass transfer, the prediction of water temperature of an outdoor pool and hence the sizing of the heating plant can result in either significant over or under estimation which could impact on not only capital and operating costs but also on complying with environmental accountability and control strategy. The model developed herein accounts for numerous contributors to the thermal energy balance of pool water, notable among them being free and forced convection heat and mass transfer to/from pool and radiation cooling to the sky. Cloud and rain effects are also incorporated into the model. The role of solar and ambient weather conditions is emphasised. The first-principle and analytical model has been calibrated against data from an Olympic sized swimming pool in Perth, Australia. A comparison between various models in the literature shows that the present model is able to replicate experimental data much more closely than others, with 82% of the results being within ±0.5 °C of the actual measured pool temperatures and with 67% of the predicted heating capacities being within ±100 kW of the measured heating capacities.

Item Type: Article
Authors/Creators:Lovell, D and Rickerby, T and Vandereydt, B and Do, L and Wang, X and Srinivasan, K and Chua, HT
Keywords: swimming pool, heat and mass transfer, heating capacity, geothermal
Journal or Publication Title: Building and Environment
Publisher: Elsevier
ISSN: 0360-1323
DOI / ID Number: 10.1016/j.buildenv.2019.106167
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© 2019 Elsevier Ltd. All rights reserved.

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