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Thermal heat transfer and energy modeling through incorporation of phase change materials (PCMs) into polyurethane foam

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  • Nandy, Aditi
  • Houl, Yassine
  • Zhao, Weihuan
  • D'Souza, Nandika Anne

Abstract

Decreasing HVAC energy consumption through insulation effectiveness enables low energy use, low carbon emissions, and high thermal comfort in sustainable buildings. PCMs for energy storage are an innovative option, but in buildings, their high thermal conductivity is a concern.The PCM latent heat of fusion and thereby it’s transition temperature has been a key parameter in PCM selection but little is known of the effect of PCM on building energy contributions arising from increasing thermal conductivity (k), density (ρ), and specific heat capacity (Cp). To resolve this, in this paper, two PCMs with transition temperature above and below the outdoor temperature incorporated in highly porous flexible polyurethane foam were evaluated using a one-dimensional (1D) foam core panel built in COMSOL Multiphysics®. The simulations were run using the summer season in a humid subtropical climate zone with an outdoor temperature of 35 °C. It was found that apart from the latent heat of fusion, the combined effects of high ρ and Cp could mitigate the increased k of PU-PCM composites to improve the insulation performance. Building energy modeling using EnergyPlus with the foam core incorporated into a structural insulated panel (SIP), revealed that the use of PCMs regardless of the transition temperature could reduce annual electricity consumption by 15–20%, with a significant amount of energy savings arising from the cooling load in summer.

Suggested Citation

  • Nandy, Aditi & Houl, Yassine & Zhao, Weihuan & D'Souza, Nandika Anne, 2023. "Thermal heat transfer and energy modeling through incorporation of phase change materials (PCMs) into polyurethane foam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:rensus:v:182:y:2023:i:c:s1364032123002678
    DOI: 10.1016/j.rser.2023.113410
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    1. Liu, Bokai & Wang, Yizheng & Rabczuk, Timon & Olofsson, Thomas & Lu, Weizhuo, 2024. "Multi-scale modeling in thermal conductivity of Polyurethane incorporated with Phase Change Materials using Physics-Informed Neural Networks," Renewable Energy, Elsevier, vol. 220(C).

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