Modeling the effect of roof coatings materials on the building thermal temperature variations based on an artificial intelligence

This paper presents the benefits of applying the artificial neural networks technique to model the building indoor temperature variations caused by implementing roof coatings. Four of the most common roof coating used in Mexican constructions were considered. The study evaluated test cells at outdoo...

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Bibliographic Details
Published in:Journal of physics. Conference series 2022-01, Vol.2180 (1), p.12014
Main Authors: May Tzuc, O., Hernandez-Pérez, I., Castro, Karla M Aguilar, Jiménez Torres, M., Castillo-Téllez, M, Demesa López, N
Format: Article
Language:English
Subjects:
Ambient temperature
Artificial intelligence
Artificial neural networks
Coating effects
Indoor environments
Modelling
Optical properties
Physical properties
Physics
Relative humidity
Roofs
Sensitivity analysis
Solar radiation
Temperature
Thermal comfort
Thermodynamic properties
Wind speed
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Summary:This paper presents the benefits of applying the artificial neural networks technique to model the building indoor temperature variations caused by implementing roof coatings. Four of the most common roof coating used in Mexican constructions were considered. The study evaluated test cells at outdoors and instrumented them to measure the indoor temperature variation. The environmental parameters solar radiation, wind speed, ambient temperature, and relative humidity were also monitored. The results showed the viability of modeling the thermal behavior generated by the roof coatings with an accuracy greater than 90%. It implies the ability to predict internal temperatures based on the physical properties of the material and environmental variables, being a feasible tool in the search for thermal comfort for buildings in the region. In addition, the results of the sensitivity analysis identified to what extent to improve the optical properties of the material impact on the heat transferred to the interior.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2180/1/012014