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Multi-scale simulation study on the heat transfer characteristics of phase-change walls

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  • Li, Min
  • Yan, Dandan
  • Shi, Junbing

Abstract

The establishment of a multi-scale heat transfer model of the wall containing phase-change thermal insulation mortar (PCTIM) can clearly reflect the actual distribution of the phase change material in the PCTIM and the effect of the phase change components on the heat transfer characteristics of the wall. In this study, firstly, a mesoscopic two-phase stochastic composite model of PCTIM was established to calculate the effective thermal performance. The results showed that the thermal conductivity of PCTIM decreased with an increase of shaped-stabilized phase-change material (SSPCM) content. Then a multi-scale heat transfer model was used to study the influence of the content and the thermal property parameters of the phase-change material in PCTIM on the heat transfer characteristics of the outer wall. The results exhibited that the PCTIM with a phase-change temperature of 25–27 °C could play the role of increasing indoor thermal comfort in transition season and reducing building energy consumption in summer. In addition, with the increase of the latent heat and content of SSPCM, the temperature fluctuation of the phase change wall in the transition season was reduced by 31.1% and 30.6%, respectively, and the cumulative heat gain in summer was reduced by 8.8% and 16.8%, respectively, which effectively improved the temperature control effect of the phase-change wall in the transition season and the energy-saving effect in summer. However, with the increase of the thermal conductivity of SSPCM, the thermal regulation ability of the phase change wall in the transition season increased (the temperature fluctuation reduced by 6.7%), but the energy saving effect in summer decreased (the cumulative heat gain increased by 10.4%).

Suggested Citation

  • Li, Min & Yan, Dandan & Shi, Junbing, 2022. "Multi-scale simulation study on the heat transfer characteristics of phase-change walls," Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:energy:v:259:y:2022:i:c:s0360544222017996
    DOI: 10.1016/j.energy.2022.124896
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    References listed on IDEAS

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    1. Xin Xiao & Qian Hu & Huansong Jiao & Yunfeng Wang & Ali Badiei, 2023. "Simulation and Machine Learning Investigation on Thermoregulation Performance of Phase Change Walls," Sustainability, MDPI, vol. 15(14), pages 1-22, July.

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