A Novel AI-Based Thermal Conductivity Predictor in the Insulation Performance Analysis of Signal-Transmissive Wall

Xiaolei Wang (), Xiaoshu Lü (), Lauri Vähä-Savo and Katsuyuki Haneda
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Xiaolei Wang: Department of Electrical Engineering and Energy Technology, University of Vaasa, P.O. Box 700, FIN-65101 Vaasa, Finland
Xiaoshu Lü: Department of Electrical Engineering and Energy Technology, University of Vaasa, P.O. Box 700, FIN-65101 Vaasa, Finland
Lauri Vähä-Savo: Department of Electronics and Nanoengineering, School of Electrical Engineering, Aalto University, P.O. Box 13500, FIN-00076 Espoo, Finland
Katsuyuki Haneda: Department of Electronics and Nanoengineering, School of Electrical Engineering, Aalto University, P.O. Box 13500, FIN-00076 Espoo, Finland

Energies, 2023, vol. 16, issue 10, 1-16

Abstract: It is well known that thermal conductivity measurement is a challenging task, due to the weaknesses of the traditional methods, such as the high cost, complex data analysis, and limitations of sample size. Nowadays, the requirement of quality of life and tightening energy efficiency regulations of buildings promote the demand for new construction materials. However, limited by the size and inhomogeneous structure, the thermal conductivity measurement of wall samples becomes a demanding topic. Additionally, we find the thermal parameter values of the samples measured in the laboratory are different from those obtained by theoretical computation. In this paper, a novel signal-transmissive wall is designed to provide the problem solving of signal connectivity in 5G. We further propose a new thermal conductivity predictor based on the Harmony Search (HS) algorithm to estimate the thermal properties of laboratory-made wall samples. The advantages of our approach over the conventional methods are simplicity and robustness, which can be generalized to a wide range of solid samples in the laboratory measurement.

Keywords: thermal conductivity; specific heat; artificial intelligence; harmony search; optimization methods; large sample measurement; 5G passive antenna system; sandwich wall (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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