4.7 Article

On the equivalent thermo-physical properties for modeling building walls with unknown stratigraphy

期刊

ENERGY
卷 238, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.121679

关键词

Equivalent thermo-physical properties; Simulation; Unknown stratigraphy; Experimental measurements; Inverse method

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This study conducted experimental campaigns on building walls to generate equivalent homogeneous walls through an inverse approach, addressing the issue of information lack and determining the equivalent thermo-physical properties that best reproduce the thermal behaviors of the original walls. Energy simulations showed a range of percentage difference of +/- 10% between the equivalent and original models for both energy demands and peak loads.
It is known that energy efficiency passes through the renovation of the built heritage. However, the technical data may be unknown, thus applying not always suitable assumptions. Documents may have been lost and uncertainties may occur. In this context, the description of multilayer walls through equivalent models could solve the information lack issues. In this study, an experimental campaign is conducted on two test rooms, and the measured data are used to generate equivalent homogeneous walls through an inverse approach. The comparison between the original and equivalent walls is performed, finding the equivalent thermo-physical properties able to best reproduce the thermal behaviors of the original walls and calculating the model efficiency index (EF). Finally, a building simulation code is used to perform a comparison on annual energy demands. The main results allow to obtain EF indexes higher than 0.93 in almost all the analyzed scenarios. The main issue is related to the experimental equivalent thermal conductivity, the determination of which is correlated to suitable measurement conditions. Considering the energy simulations, the comparison between the equivalent models and the original ones allows to obtain a range of percentage difference of +/- 10 % for both energy demands and peak loads. (c) 2021 Elsevier Ltd. All rights reserved.

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