volume 244 pages 122610

Thermal performance of an advanced smart fenestration systems for low-energy buildings

Yang Ming 1
Yanyi Sun 1
Xin Liu 1
Liantuan Xiao 1
Xiao Liu 1
Yupeng Wu 1
Publication typeJournal Article
Publication date2024-05-01
scimago Q1
wos Q1
SJR1.579
CiteScore11.0
Impact factor6.9
ISSN13594311, 18735606
Mechanical Engineering
Industrial and Manufacturing Engineering
Energy Engineering and Power Technology
Fluid Flow and Transfer Processes
Abstract
Windows significantly influence a building's indoor environment and energy consumption due to their high optical transmittance and low thermal resistance comparing with walls, affecting both indoor daylight comfort and heat gain or loss. Thermotropic (TT) materials can offer dynamic regulation of solar energy, improving building energy efficiency. Parallel slats transparent insulation materials (PS-TIM) integrated into the air cavity of double-glazing windows can effectively increase the thermal resistance of a window. In this study, these two advanced technologies were combined to develop a new type of adaptive fenestration system, named Thermotropic Parallel Slat Transparent Insulation Material (TT PS-TIM) system. The selected TT hydrogel, 5 wt.% poly(N-isopropyl acrylamide) (PNIPAm), was sandwiched within polymethyl methacrylate (PMMA) slices. The slats were subsequently proposed between two glass panes to form a parallel slat transparent insulation materials system. To investigate the thermal and optical properties of the TT slats as well as the thermal performance (i.e., solar heat gain coefficient, and dynamic thermal performance in summer and winter) of the TT PS-TIM system with different slats intervals, a novel model combining Ray-tracing technique and Computational Fluid Dynamics (CFD) has been proposed. The findings of this study reveal that a TT PS-TIM system incorporating 5 wt.% PNIPAm slats can offer a substantial reduction (up to 0.5) in solar transmittance as it transitions from a clear to a translucent state. Accompanied with the phase transition of the TT slats, there is a significant reduction in the Solar Heat Gain Coefficient (SHGC) of the window system. This effectively decreases the unwanted solar heat gain, thus improving the overall buildings thermal performance. According to the advanced transient simulation results based on the weather conditions of London, the TT PS-TIM system exhibits superior performance evidenced by over a 30% reduction in heat gain during summer and approximately a 20% reduction in heat loss during winter in contrast to a conventional Double Glazing (DG) system. This is evident in the form of reduced heat gain during summer and minimized heat loss during winter, resulting in a more thermally balanced environment throughout the year. The comprehensive thermal investigation of TT PS-TIM can effectively help to increase the accuracy of the further energy and daylight analysis.
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GOST Copy
Ming Y. et al. Thermal performance of an advanced smart fenestration systems for low-energy buildings // Applied Thermal Engineering. 2024. Vol. 244. p. 122610.
GOST all authors (up to 50) Copy
Ming Y., Sun Y., Liu X., Xiao L., Liu X., Wu Y. Thermal performance of an advanced smart fenestration systems for low-energy buildings // Applied Thermal Engineering. 2024. Vol. 244. p. 122610.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.applthermaleng.2024.122610
UR - https://linkinghub.elsevier.com/retrieve/pii/S1359431124002783
TI - Thermal performance of an advanced smart fenestration systems for low-energy buildings
T2 - Applied Thermal Engineering
AU - Ming, Yang
AU - Sun, Yanyi
AU - Liu, Xin
AU - Xiao, Liantuan
AU - Liu, Xiao
AU - Wu, Yupeng
PY - 2024
DA - 2024/05/01
PB - Elsevier
SP - 122610
VL - 244
SN - 1359-4311
SN - 1873-5606
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Ming,
author = {Yang Ming and Yanyi Sun and Xin Liu and Liantuan Xiao and Xiao Liu and Yupeng Wu},
title = {Thermal performance of an advanced smart fenestration systems for low-energy buildings},
journal = {Applied Thermal Engineering},
year = {2024},
volume = {244},
publisher = {Elsevier},
month = {may},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1359431124002783},
pages = {122610},
doi = {10.1016/j.applthermaleng.2024.122610}
}