| Autor: |
Yurong Zhu, Wei Song, Xiaohuan Wang, Yves Rybarczyk, Roger G. Nyberg, Benhua Fei |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Buildings, Vol 13, Iss 9, p 2151 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2075-5309 |
| DOI: |
10.3390/buildings13092151 |
| Popis: |
To maintain the life of building materials, it is critical to understand the hygrothermal transfer mechanisms (HTM) between the walls and the layers inside the walls. Due to the extreme instability of weather data, the actual data models of the HTM—the data being collected for actual buildings using modern sensor technologies—would appear to be a great difference from any theoretical models, in particular, for wood building materials. In this paper, we aim to consider a variety of data analysis tools for hygrothermal transfer features. A novel approach for peak and valley detection is proposed based on the discrete differentiation of the original data. Not to be limited to the measure of peak and valley delays for HTM, we propose a cross-correlation analysis to obtain the general delay between two daily time series, which seems to be representative of the delay in the daily time series. Furthermore, the seasonal pattern of the hygrothermal transfer combined with the correlation analysis reveals a reasonable relationship between the delays and the indoor and outdoor climates. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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