2022
DOI: 10.3390/en15145029
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Combining Deep Learning and the Heat Flux Method for In-Situ Thermal-Transmittance Measurement Improvement

Abstract: Transmission losses through the building envelope account for a large proportion of building energy balance. One of the most important parameters for determining transmission losses is thermal transmittance. Although thermal transmittance does not take into account dynamic parameters, it is traditionally the most commonly used estimation of transmission losses due to its simplicity and efficiency. It is challenging to estimate the thermal transmittance of an existing building element because thermal properties… Show more

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Cited by 4 publications
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