Numerical and Experimental Analysis of Heat Flow at Window-to-Wall Interface

Pomada, Marta; Adamus, J.; Boruszewski, Artur

doi:10.3390/en15103837

Cited by 4 publications

(6 citation statements)

References 23 publications

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“…In these works, the optimal shift of the window relative to the thermal insulation layer was determined based on the value of the Ψ coefficient. Similar aspects of heat flow in the steady state using the TRISCO program were analysed in [36,[49][50][51]. The conclusions from the works [18,47,52] are consistent with the results of the authors' work, although the analyses included different variants of window installation and different wall structures.…”

Section: Introductionsupporting

confidence: 69%

“…Two window locations:  First location: window flush with the face of the load-bearing layer,  Second location: window optimally shifted into the thermal insulation layer, in accordance with the previously performed calculations [36].…”

mentioning

confidence: 71%

“…Second location: window optimally shifted into the thermal insulation layer, in accordance with the previously performed calculations [36].…”

mentioning

confidence: 82%

“…The possibilities of using recycled materials and bio-waste to improve the thermal parameters of external walls were analysed in [32,33]. In paper [34], the thermal-humidity and strength parameters of composite elements used during window installation were analysed, and in papers [35,36], additionally, the possibility of reinforcing composite beams with metal profiles was analysed. Many works, including [37,38], concern the improvement of the insulation parameters of the windows themselves.…”

Section: Introductionmentioning

confidence: 99%

“…The work is a continuation of research into the field of window installations in a layer of thermal insulation. In papers [34,36], the authors analysed the influence of the window type and the method of installation on the thermal and humidity parameters. The analyses showed that the value of the linear heat transmittance coefficient Ψ for the same variants of the external wall, but for windows with different heat transfer coefficients Uw, were very similar.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Influence of External Wall Material Type on the Thermal Bridge at the Window-to-Wall Interface

Adamus,

Pomada

2023

Materials

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Background: Although many works focus on increasing the energy efficiency of buildings, there are still a number of problems that need to be solved, such as reducing heat losses at the window-to-wall interface, especially since the requirements for saving energy used for heating/cooling rooms are constantly increasing. This paper analyses the impact of the material parameters of the external wall and the window installation in the insulation layer on the size of thermal bridges around the window. Purpose: The aim of the work is to demonstrate the benefits resulting from the correct installation of the window, the appropriate location of the window in relation to the face of the external wall, as well as the correct selection of construction materials. Methodology: In order to show the improvement in the energy efficiency of buildings, an analysis of the heating/cooling energy consumption was carried out for the selected buildings. The thermal and humidity analyses were carried out using TRISCO program, while the economic analysis was performed using the Audytor OZC program. Results: It was found that the proposed system of window installation in the thermal insulation layer reduced the annual heating demand by at least 10% on average. Conclusions: It has been shown that the method of window installation and the type of the wall structural materials are interrelated and therefore should be considered simultaneously. Their proper selection allows for a reduction in the amount of energy needed for heating and cooling buildings, and thus a reduction of heating/cooling costs, as well as limiting greenhouse gas emissions.

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Section: Introductionsupporting

confidence: 69%

mentioning

confidence: 71%

“…Second location: window optimally shifted into the thermal insulation layer, in accordance with the previously performed calculations [36].…”

mentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of the Influence of External Wall Material Type on the Thermal Bridge at the Window-to-Wall Interface

Adamus,

Pomada

2023

Materials

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Thermal transmittance of a composite lightweight wall panel with integrated load-bearing structure: Experimental versus numerical approach

Gaši,

Milovanović,

Tkalčić

et al. 2023

Case Studies in Construction Materials

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Using fuzzy system as AI tool to minimize thermal bridges in design of external walls

Pomada,

Cpałka,

Lacki

et al. 2024

Preprint

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Buildings significantly contribute to climate change, accounting for approximately one-third of global energy consumption and a quarter of CO2 emissions. Therefore, all actions aimed at increasing building energy efficiency are of great importance. This study explores the application of fuzzy system – an artificial intelligence (AI) tool – for optimizing external wall designs, specifically focusing on minimizing thermal bridges at the window-to-wall connection. To achieve this, traditional thermal bridge analysis using the TRISCO program to generate training sets was employed. The data collected from thermal analysis served as input for machine learning. The fuzzy system was then utilized to estimate linear heat transmittance coefficients, which quantify heat loss through thermal bridges. The proposed AI approach demonstrates excellent performance, generating precise linear heat transmittance coefficient values. Importantly, due to its ability to generalize knowledge, the trained system accurately determines the value of the Ψ coefficient for cases not included in the training data – those for which traditional analysis using the TRISCO program had not been previously performed. By leveraging this approach for thermal bridge analysis, it becomes possible to reduce the need for classical analyses, which often involve time-consuming calculations, expensive experiments, and extensive designer expertise in selecting optimal solution.

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Numerical and Experimental Analysis of Heat Flow at Window-to-Wall Interface

Cited by 4 publications

References 23 publications

Analysis of the Influence of External Wall Material Type on the Thermal Bridge at the Window-to-Wall Interface

Analysis of the Influence of External Wall Material Type on the Thermal Bridge at the Window-to-Wall Interface

Thermal transmittance of a composite lightweight wall panel with integrated load-bearing structure: Experimental versus numerical approach

Using fuzzy system as AI tool to minimize thermal bridges in design of external walls

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