LAPSE:2023.19414
Published Article

LAPSE:2023.19414
Prediction and Analysis of the Thermal Performance of Composite Vacuum Glazing
March 9, 2023
Abstract
In this paper, a prediction method of the heat transfer coefficient of composite vacuum glazing (CVG) is proposed. By analyzing the heat transfer process of CVG, the theoretical calculation formula for the heat transfer coefficient of CVG is established. CVG temperature variation under the test conditions specified in the national standard is simulated using ANSYS. The CVG heat transfer coefficient is calculated by combining the theoretical formula and simulation results. The simulation results are then verified by comparison to a physical experiment. The results show that the deviations between the experimental and predicted values are ≤3.8%, verifying the accuracy of the simulation results and proving that the model can be used in engineering practice. Furthermore, the effects of different coating positions on the heat transfer performance of CVG are studied. The results show that different coating positions have a significant impact on the heat transfer coefficient of CVG. The heat transfer coefficient is shown to be lowest to highest under the following conditions: when the Low-E coatings are located on both sides of the vacuum layer (2LC-V), followed by Low-E coatings on the side of glass pane II near the vacuum layer (1LC-V), Low-E coatings located on the side of glass pane I near insulating layer (1LC-I), and finally, when there are no Low-E coatings (NLC) on the glass panes. Overall, this model is an effective and accurate analysis method of the heat transfer coefficient.
In this paper, a prediction method of the heat transfer coefficient of composite vacuum glazing (CVG) is proposed. By analyzing the heat transfer process of CVG, the theoretical calculation formula for the heat transfer coefficient of CVG is established. CVG temperature variation under the test conditions specified in the national standard is simulated using ANSYS. The CVG heat transfer coefficient is calculated by combining the theoretical formula and simulation results. The simulation results are then verified by comparison to a physical experiment. The results show that the deviations between the experimental and predicted values are ≤3.8%, verifying the accuracy of the simulation results and proving that the model can be used in engineering practice. Furthermore, the effects of different coating positions on the heat transfer performance of CVG are studied. The results show that different coating positions have a significant impact on the heat transfer coefficient of CVG. The heat transfer coefficient is shown to be lowest to highest under the following conditions: when the Low-E coatings are located on both sides of the vacuum layer (2LC-V), followed by Low-E coatings on the side of glass pane II near the vacuum layer (1LC-V), Low-E coatings located on the side of glass pane I near insulating layer (1LC-I), and finally, when there are no Low-E coatings (NLC) on the glass panes. Overall, this model is an effective and accurate analysis method of the heat transfer coefficient.
Record ID
Keywords
ANSYS, heat transfer coefficient, insulating glazing, vacuum glazing
Subject
Suggested Citation
Shi Y, Xi X, Zhang Y, Xu H, Zhang J, Zhang R. Prediction and Analysis of the Thermal Performance of Composite Vacuum Glazing. (2023). LAPSE:2023.19414
Author Affiliations
Shi Y: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Xi X: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Zhang Y: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Xu H: Yingtai Group Co., Ltd., Yangzhou 225000, China
Zhang J: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Zhang R: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China
Xi X: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Zhang Y: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Xu H: Yingtai Group Co., Ltd., Yangzhou 225000, China
Zhang J: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China [ORCID]
Zhang R: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China
Journal Name
Energies
Volume
14
Issue
18
First Page
5769
Year
2021
Publication Date
2021-09-13
ISSN
1996-1073
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Original Submission
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PII: en14185769, Publication Type: Journal Article
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LAPSE:2023.19414
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https://doi.org/10.3390/en14185769
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Mar 9, 2023
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