Prediction and Analysis of the Thermal Performance of Composite Vacuum Glazing

Shi, Yangjie; Xi, Xiaobo; Zhang, Yifu; Xu, He-Yong; Zhang, Jianfeng; Zhang, Ruihong

doi:10.3390/en14185769

Cited by 7 publications

(5 citation statements)

References 20 publications

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“…The results of numerous studies on heat transfer through single-and double-chamber windows are presented in previous works [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. Gan [1] studied heat transfer through a double-glazed window.…”

Section: Analysis Of Known Research Resultsmentioning

confidence: 99%

“…These sliding windows are expected to generate electrical energy as well as provide effective thermal insulation. Shi et al [13] note that the modern approach to improving the thermal insulation characteristics of glass units involves a combination of vacuum glazing and the application of low-emission coatings to its surfaces. In this work, based on the results of numerical simulations and experimental studies, the influence of different positions of low-emission coatings in relation to vacuum glasses on the heat transfer characteristics of this system is analyzed.…”

Section: Analysis Of Known Research Resultsmentioning

confidence: 99%

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Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating

Koshlak,

Basok,

Davydenko

2024

Energies

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The numerical modeling of radiation and convective heat transfer through a double-chamber glass unit was carried out to substantiate the increase in the heat transfer resistance of this unit via the application of low-emission coatings to glass surfaces. In the space between the panes of a window without low-emission coatings, the amount of heat transferred via radiation exceeds the amount of heat transferred via thermal conductivity and convection. The question of the effect of low-emissivity coatings on reducing heat loss through a window has not yet been sufficiently studied. This problem is also not sufficiently reflected in the literature. In this regard, this paper presents the results of numerical simulation aimed at studying the effect of low-emissivity coatings on heat transfer through a double-chamber glass unit. Simulation is carried out by numerically solving a system of equations of fluid dynamics and energy for the air gap and glass. Boundary conditions of the fourth kind are set on the internal surfaces of the chambers, taking into account the radiation and conduction components of the total heat flux emanating from the glass. The results of modeling heat transfer through a glass unit with ordinary glass show that about 60% of the heat is transferred by radiation. Therefore, an effective measure to reduce heat loss through windows is to reduce the radiation component of the total heat flux by applying a low-emissivity coating to the internal surfaces of the glass unit. This allows for the reduction of the overall heat flux (and, accordingly, heat loss to the environment) by 20–34%, depending on the number of glass surfaces with such a coating.

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Section: Analysis Of Known Research Resultsmentioning

confidence: 99%

Section: Analysis Of Known Research Resultsmentioning

confidence: 99%

Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating

Koshlak,

Basok,

Davydenko

2024

Energies

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“…The data is first trained with a weak trainer. [8] The loss function of the i th sample of the t th round has the negative gradient as shown in Equation (1).When the loss function is squared, the negative gradient value is the residual of the current model.…”

Section: Gradient Boostingmentioning

confidence: 99%

“…Vacuum glass is widely used in infrastructure to reduce energy consumption. [1] As for the reduction of energy consumption is through the development of adaptive glass technology. [2] However,the structure is more complex.…”

mentioning

confidence: 99%

Prediction of heat transfer performance of vacuum glass based on extreme gradient boosting algorithm

Jia

Wang

2023

Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023)

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In this paper, a non-stationary detection method based on the artificial intelligence algorithm XGBoost is proposed for the detection of the U-value of the vacuum glass. By analyzing the heat transfer characteristics of vacuum glass and considering the detection efficiency, the features are selected as hot end temperature, ambient temperature, and characteristic temperature change rate. In this paper, the training effect of a model is measured comprehensively by the scores of MAE, MSE, and R2. Three models, KNN, GBDT, and XGBoost, are used to train the dataset and compare the prediction results. After the comparison, XGBoost has the best prediction effect. Finally, the fitted model is validated by 5*2 nested cross-loop, and the analysis results show that the fitted model has better stability, which greatly enhances the credibility of the model. After a series of experiments, it is known that the small sample of non-stationary method and multiple interference problems can all be solved by XGBoost algorithm with certain stability, which can provide ideas for further industrialized testing.

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“…In the study, besides the economic benefits, the effect of the energy performance of the windows on the energy performance of the building was also examined. Shi Y et al [41] proposed an estimation method of the composite vacuum glazing (CVG) heat transfer coefficient in their study. The theoretical calculation formula for the heat transfer coefficient of CVG has been established.…”

Section: Introductionmentioning

confidence: 99%

Benefitting from Solar Energy Due to Different Emissivity Levels of Multiple Glass Windows for Buildings

Kon¹,

Caner²

2022

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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ÖzIn the study, firstly, heat transfer coefficients of windows were calculated according to the highest and lowest emissivity values. Secondly, monthly average solar radiation values were determined. The heat transfer coefficient calculated for double, triple and quadruple glass windows. Thirdly, the solar radiation in the south, north and east/west directions of the five climatic zones were multiplied by the shading factor, surface area and the solar energy factor of discrete buildings. Thus, the solar energy gain value for the heating period and solar energy losses for cooling period was determined. Finally, passive solar energy gains are calculated during the heating and cooling period for all climate zones. It has been calculated that in the fifth climatic zone in south direction, heat loss from windows with 0.05 emissivity can be provided with passive solar energy by 167.9% in double-glazed windows, 258.7% in triple-glazed windows and 349.1% in quadruple-glazed windows.Çalışmada öncelikle en yüksek ve en düşük yayma oranlarına göre pencerelerin ısı transfer katsayıları hesaplanmıştır. İkinci olarak aylık ortalama güneş ışınımı değerleri belirlenmiştir. İkili, üçlü ve dörtlü cam pencereler için ısı transfer katsayıları hesaplanmıştır. Üçüncü olarak, beş iklim bölgesinin güney, kuzey ve doğu/batı yönündeki güneş radyasyonu, ayrı binaların gölgeleme faktörü, yüzey alanı ve güneş enerjisi faktörü ile çarpılmıştır. Böylece ısıtma periyodu için güneş enerjisi kazanç değeri ve soğutma periyodu için güneş enerjisi kayıpları belirlenmiştir. Son olarak, tüm iklim bölgeleri için ısıtma ve soğutma periyodu boyunca pasif güneş enerjisi kazanımları hesaplanmıştır. Güney yönünde beşinci iklim kuşağında 0.05 yayma oranına sahip pencerelerden ısı kaybının pasif güneş enerjisi ile çift camlı pencerelerde %167.9, üç camlı pencerelerde %258.7 ve dört camlı pencerelerde %349.1 sağlanabileceği hesaplanmıştır.

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Prediction and Analysis of the Thermal Performance of Composite Vacuum Glazing

Cited by 7 publications

References 20 publications

Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating

Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating

Prediction of heat transfer performance of vacuum glass based on extreme gradient boosting algorithm

Benefitting from Solar Energy Due to Different Emissivity Levels of Multiple Glass Windows for Buildings

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