Industry 4.0
Vol. 9 (2024), Issue 6, pg(s) 211-214

DOMINANT TECHNOLOGIES IN “INDUSTRY 4.0”

Thermal bridging Inverse problem: Using neural networks to determine thermal bridge parameters at known Psi-factor

  • 1 University of Architecture, Civil Engineering and Geodesy (UACEG) – Sofia, Bulgaria

Abstract

This paper investigates the inverse problem for thermal bridges – determining design parameters (such as material, geometry, thermal resistance R of the components) of the bridge at a known Psi-factor. By using artificial neural networks, a thermal bridge type IF (wall-floor connection) has been considered to evaluate the effectiveness of the methodology. The results show that the approach provides a fast and accurate way to predict the optimal parameters that meet specific energy efficiency requirements. In the future, this approach could help to determine the parameters of thermal bridges using thermographic images non-invasively.

Keywords

References

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